LEE- Telekomünikasyon Mühendisliği-Doktora

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http://hdl.handle.net/11527/19470

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4.5G frekanslarında çok bantlı geniş geliş açısı aralığında etkili yeni bir frekans seçici yüzey tasarımı

(Lisansüstü Eğitim Enstitüsü, 2022-07-18) Balta, Şakir ; Kartal, Mesut ; 504132311 ; Telekomünikasyon Mühendisliği

Dünyada artan nüfüs ve gelişen teknolojiyle birlikte hücresel kablosuz sistemlerinin kullanımı artmakta, kısıtlı miktardaki frekans bantlarının yoğun bir şekilde kullanımı dolayısıyla artan işaretler arası girişimler, birçok hassas elektronik aygıtın çalışmasını etkileyebilmektedir. Bunun yanında, bu frekansları önlemeye yönelik herhangi bir sistem olmaması nedeniyle insanlar, günlük hayatlarında, evde, ofiste, her an her yerde bu frekanslara maruz kalmakta, bunun neticesinde sağlıklarını kaybederek yaşam kaliteleri düşebilmektedir. Bu nedenlerle böylesi sorunlara bir çözüm olabilmesi açısından bu tezde yer verilen çalışmalarla imalatı kolay, maliyeti düşük ve geniş bir kullanım alanına sahip olabilecek frekans seçici yüzey (FSY) kaplama ürünlerinin geliştirilmesi, teknolojinin insan sağlığına verebileceği zararların önlenerek insan yaşam kalitesinin artırılması açısından önemlidir. Günümüzde dünyada mobil haberleşme alanında IMT Advanced, ülkemizde de kısaca 4.5G olarak bilinen ve 800, 900, 1800, 2100 ve 2600 MHz frekans bantları içeren mobil haberleşme sistemi kullanılmaktadır. Tezin ana amacı bu frekans bantlarını engellemektir. Bu frekansların engellenmesi ile radyo dalgalarının insan sağlığına olan etkileri azaltılacak, mobil haberleşmenin olmasının istenmediği yerlerde bir engelleyici olarak kullanılabilecek, bunun yanında farklı frekanslardan gelecek işaretler arası girişimler de engellenebilecektir. Diğer bir amacımız da bir yandan bu frekansları engellerken, bir yandan da belirttiğimiz frekanslar aralığında kalan, ancak günlük hayatta oldukça yoğun kullanım alanı olan, örneğin 2.4 GHz kablosuz ağlar gibi serbest frekans bantlarını da engellememektir. Yakın gelecekte nesnelerin interneti kullanımı ile birlikte kablosuz ağların çok daha yoğun olarak kullanılacağı düşünüldüğünde, sadece ilgili frekansları engelleyen ama kablosuz ağları engellemeyen bu çalışmanın önemi giderek artacaktır. Bu nedenle yürüttüğümüz tez kapsamında, 4.5G frekans bantlarında oluşan radyo dalgalarını engelleyen aynı zamanda diğer frekans bantlarında herhangi bir engelleme yapmayan, bant durduran filtre görevi görecek yapısal yüzey malzemesi tasarlamak, bunun yanında bu frekans bantlarında ortaya çıkan işaret girişim etkilerini en aza indirmek hedeflenmiştir. Bunlara ek olarak çalışmayı yaparken tasarlanan FSY'lerin mümkün olduğunca farklı geliş açılarında etkinliğini koruması amaçlanmıştır. Bu malzemenin, durdurma bandında iletim katsayısının (S_21) minimum -10dB, iletim bandında iletim katsayısının (S_11) 0dB'e yakın bir değerde olması ve ayrıca elektromagnetik dalganın farklı geliş açılarında, ve farklı polarizasyonlarında da amaçlanan frekans karakteristiklerini sağlaması hedeflenmiştir. FSY'lerin frekans karakteristiği yüzeyi oluşturan periyodik eleman geometrilerine bağlı olduğundan çok çeşitli eleman geometrileri literatürde incelenmiştir. Benzer biçimde periyodik eleman geometrilerinin üzerine baskısının gerçekleştirildiği dielektrik tabakaların da yüzeyin frekans karakteristiği üzerine etkileri bulunmaktadır ve bu etkiler literatürde ayrıntılı olarak incelenmiştir. Tez çalışmasında FSY'lerin analiz yöntemleri de incelenmiştir. Dalga denkleminin analitik çözümü sadece bazı basit FSY geometrileri için görülmüştür. Dalga denkleminin diğer bütün FSY geometrileri için çözümü sadece sayısal çözüm yöntemleri ile elde edilebildiği görülmüştür. Bilgisayar teknolojisindeki hızlı gelişmeyle beraber sayısal analiz yöntemleri bu konuda uygulama alanı bulmaya başlamıştır. FSY geometrilerinin analizlerinde Sonlu Farklar Metodu (Finite Difference Time Method), Sonlu Eleman Metodu (Finite Element Method), Momentler Metodu (Method of Moments) gibi sayısal çözüm yöntemlerinin kullanıldığı, bunun yanında Eşdeğer Devre Modeli'nin de FSY yüzey analizlerinde kullanıldıkları literatürde görülmüştür. Yukarıda belirtilen sayısal analiz yöntemleri içinde tasarım aşamasında belirlenen FSY'lerin analizleri "Sonlu Elemanlar Metodu" ile gerçekleştirilmiş ve ilgilenilen frekans aralığında iletim ve yansıma katsayıları hesaplanmıştır. Ansoft HFSS programı "Sonlu Eleman Metodu" ile bu tür yapıların analizlerini yapabilmektedir. FSY'lerin eniyilemesi HFSS programında eşdeğer devre yönteminin yansıması ile, programın parametrik analiz özelliği kullanılarak gerçekleştirilmiştir. Tez aşamasında bu programdan aktif olarak faydalanılmıştır. Tasarımlarda mümkün olan en az sayıda rezonans ile frekans bantları arasındaki girişimler azaltılmaya çalışılarak, birden fazla frekans karakteristiğine sahip olan üç farklı tasarım geliştirilmiştir. Bunun yanında da durdurmak istenilen frekansların haricinde kalan çalışma frekanslarını engellememek amacıyla mümkün olan en dar durdurma bantlarını sağlayan, oldukça keskin kenarlı bant durduran filtreler oluşturulması için çaba harcanmıştır. Tüm bunları yaparken tasarlanan FSY'lerin mümkün olduğunca farklı geliş açılarında ve farklı polarizasyonlarda etkinliğini koruması hedeflenmiş, bu amaçla simetrik ve dalga boyuna göre çok küçük boyutlardaki geometriler kullanılmıştır. Birden fazla bandı durduran FSY tasarımlarında karşılaşılan en büyük problemlerden biri herbir frekans bandı için tasarlanan farklı geometrilerin birbirlerine olan girişim etkileri olmuştur. O nedenle birçok geometri üzerinde araştırmalar yapılmış ve problemin çözümü için farklı yaklaşımlar getirilmiştir. Tasarımlarda düşük maliyetli ürün geliştirmek amacıyla, 1mm kalınlığında, dielektrik sabiti 4.54 ve kayıp tanjant değeri 0.02 olan tek katlı FR4 tabaka üzerinde gerçeklenmiş, radyo frekanslarına FR4 tabakanın tepkisi kötü olmasına rağmen istenilen hedefler gerçekleştirilebilmiştir. Tasarımların analizleri ve eniyileştirme çalışmaları Ansoft HFSS programında yapılmış, yüzey akım yoğunluk grafikleri çıkarılarak herbir frekans bandı için geometrilerin etkinlikleri gösterilmiştir. FR4 tabakalar üzerine gerçeklenen tasarımların ölçümleri alınmış ve benzetim sonuçlarıyla karşılaştırılarak tasarımlar doğrulanmıştır. Geniş bir literatür taraması yapılmış ve 4.5G frekansları üzerinde etkin olan, çoklu rezonans gösteren böyle bir çalışmaya literatürde rastlanmamıştır. Bu çalışma bu alanda yapılmış ilk ve tek başarılı çalışma olması nedeniyle litaratüre katkı sağlamıştır.
A new antenna design methodology based on performance analysis of MIMO and defining novel antenna parameters

(Graduate School, 2024-05-08) Yussuf, Abubeker Abdulkerim ; Paker, Selçuk ; 504122305 ; Telecommunications Engineering

The rapid growth of wireless technology has created a significant demand for the design of Multiple-Input Multiple-Output (MIMO) antennas for wireless devices. MIMO antennas play a crucial role in meeting the requirements of current and future wireless standards, as they can maximize data rates in wireless communication systems by utilizing multiple channels within the same bandwidth. However, designing MIMO antennas for compact devices presents considerable challenges. The limited space between antennas leads to increased coupling and high correlation, which can negatively impact their performance. To address these challenges, this thesis proposes a new antenna design methodology based on MIMO performance metrics and defining antenna parameters. Existing metrics for conventional antenna systems are insufficient for fully assessing MIMO antenna performance. This methodology provides a systematic approach to optimize antenna configurations, mitigate mutual coupling, and achieve desired performance characteristics, paving the way for enhanced system capacity. The thesis introduces a novel methodology for designing MIMO antennas that relies on crucial performance metrics and defining parameters. These parameters include factors such as antenna spacing, slot dimensions, strip placements, and parasitic element sizes, which are important for meeting the requirements of modern wireless standards within the LTE and sub-6 GHz 5G bands. The research presents five distinct MIMO antenna designs, each optimized for specific requirements and validated through simulations and experimental measurements. Firstly, the dual-band Vivaldi-shaped MIMO antenna covers the 5G NR bands n78 and n79, boasting gains of over 7.63 dBi and 8.5 dBi respectively, while maintaining mutual coupling below -30 dB. Secondly, the concentric octagonal-shaped MIMO antenna is designed for 5G UE applications in the n38 band, achieving a gain of over 5 dBi and mutual coupling below -25 dB. Thirdly, the compact quad-element MIMO antenna is designed for LTE/Wi-Fi applications, exhibiting high isolation exceeding 17 dB and a channel capacity loss lower than 0.6 b/s/Hz. Fourthly, the wideband MIMO antenna is a single-element design with quad-ports, operating in the 2.1/2.3/2.6 GHz and 2.4 GHz bands. It offers an operating bandwidth of 2-3.0 GHz, reflection coefficients below -10 dB, isolation under -25 dB using synthesized pi-networks TL-based decoupling network, and a diversity gain of approximately 10 dB. Finally, a quad-element MIMO antenna utilizing a modified Apollony fractal, designed for 5G wireless communications, achieves S11 below or equal to -10 dB within the impedance bandwidth, with low mutual coupling below -20 dB. The thesis explores various decoupling strategies to mitigate mutual coupling and enhance antenna performance. These strategies include antenna placement and orientation, parasitic elements, neutralization, and synthesized Pi-networks TL-based decoupling network topology. Each design is thoroughly evaluated through simulations and experimental measurements, with performance metrics including S-parameters, envelope correlation coefficient (ECC), channel capacity, total active reflection coefficient (TARC), and diversity gain. The research demonstrates the feasibility and effectiveness of the proposed methodology for designing compact MIMO antennas that offer improved performance metrics, making them well-suited for use in 5G and beyond wireless communication systems.
A new approach to satellite communication: Harnessing the power of reconfigurable intelligent surfaces

(Graduate School, 2024-01-22) Tekbıyık, Kürşat ; Kurt Karabulut, Güneş ; 504192305 ; Telecommunications Engineering

It is widely accepted that user-centric and ubiquitous connectivity, which are desired by both end users and operators for the 6th generation (6G) and beyond communication technologies, can be achieved through the unique orchestration of terrestrial and non-terrestrial networks (NTNs) in next-generation communication systems. This vision is also described by the 3rd Generation Partnership Project (3GPP) in Technical Report (TR) 38.821 for the operation of New Radio (NR) in NTNs. According to the definition by the 3GPP, an NTN basically consists of unmanned aerial vehicles, high-altitude platform stations (HAPS) systems, and dense satellite deployments. Low-Earth orbit (LEO) satellites and HAPS systems are considered to be the key enablers for NTNs due to their unique features, which include longer operating times and wider coverage areas. The most important pillars of non-terrestrial networks are ultra-dense satellite constellations. Although satellite networks are considered a prominent solution, many challenging open issues remain to be addressed. The most prominent ones are the size, weight, and power (SWaP) constraints, high path loss, and energy efficiency. As known, multi-antenna technologies are used to mitigate high path loss by taking advantage of its beamforming capacity. However, the hardware and signal processing units of multi-antenna systems are quite complex and costly. These costs are much higher in satellite networks. Recently, it was shown that a passive antenna solution with reconfigurable smart surfaces can reduce these costs and help increase communication performance. In this regard, we propose the use of reconfigurable intelligent surface (RIS) to improve coordination between these networks given that RISs perfectly match SWaP restrictions of operating in satellite networks as a main focus of this thesis. A comprehensive framework of RIS-assisted non-terrestrial and interplanetary communications is presented that pinpoints challenges, use cases, and open issues. Furthermore, the performance of RIS-assisted NTNs under environmental effects, such as solar scintillation and satellite drag, is discussed in light of simulation results. First, we propose a novel architecture involving the use of RIS units to mitigate the path loss associated with long transmission distances. These RIS units can be placed on satellite reflectarrays, and, when used in broadcasting and beamforming, it can provide significant gains in signal transmission. This study shows that RIS-assisted satellites can provide a severe improvement in downlink and achievable uplink rates for terrestrial networks. Although RIS has the potential to increase efficiency and perform complex signal processing over the transmission environment instead of transceivers, RIS needs information on the cascaded channel in order to adjust the phase of the incident signal. Consequently, channel estimation is an essential part of RIS-assisted communications. A study presented in the thesis evaluates the pilot signal as a graph. It incorporates this information into the graph attention networks (GATs) to track the phase relation through pilot signaling. The proposed GAT-based channel estimation method investigates the performance of the direct-to-satellite (DtS) networks for different RIS configurations to solve the challenging channel estimation problem. It is shown that the proposed GAT demonstrates a higher performance with increased robustness under changing conditions and has lower computational complexity compared to conventional deep learning (DL) methods. Moreover, based on the proposed method, bit error rate (BER) performance is investigated for RIS designs with discrete and non-uniform phase shifts under channel estimation. One of the findings in this study is that the channel models of the operating environment and the performance of the channel estimation method must be considered during RIS design to exploit performance improvement as far as possible. We show that RIS can improve energy efficiency in ground-to-satellite com munications. To complete the puzzle of overall satellite communications, we investigate RIS-assisted inter-satellite communication performance in terms of BER and achievable rate as well since broadband inter-satellite communication is one of the key elements of satellite communication systems that orchestrate massive satellite swarms in cooperation. Thanks to technological advancements in microelectronics and micro-systems, the terahertz (THz) band has emerged as a strong candidate for inter-satellite links (ISLs) due to its promise of wideband communication. In particular, multi-antenna systems can improve the system performance along with the wideband supported by the THz band. However, multi-antenna systems should be considered due to their SWaP constraints. On the other hand, as a state-of-the-art multi-antenna technology, RIS is able to relax SWaP constraints because of its passive component-based structures. However, as similar reflection characteristic throughout the wideband is challenging to meet, it is possible to observe beam misalignment. In the thesis, we first provide an assessment of the use of the THz band for ISLs and quantify the impact of misalignment fading on error performance. Then, to compensate for the high path loss associated with high carrier frequencies, and to further improve the signal-to-noise ratio (SNR), we propose using RISs mounted on neighboring satellites to enable signal propagation. Based on a mathematical analysis of the problem, we present the error rate expressions for RIS-assisted ISLs with misalignment fading. Also, numerical results show that RIS can leverage the error rate performance and achievable capacity of THz ISLs as long as a proper antenna alignment is satisfied. As the misalignment error seems one of the challenges on the path toward practical RIS-assisted NTN, the acquisition of a reliable direction of arrival (DoA) estimation becomes more of an issue in achieving promised improvements in RIS-assisted communication systems. For that reason, we address DoA estimation problem in RIS-assisted communication systems in the thesis. For this aim, we use a single-channel intelligent surface whose physical layer compression is achieved using a coded-aperture technique, probing the spectrum of far-field sources that are incident on the aperture using a set of spatiotemporally incoherent modes. This information is then encoded and compressed into the channel of the coded-aperture. The coded-aperture is based on a metasurface antenna design and it works as a receiver, exhibiting a single-channel and replacing the conventional multi-channel raster scan-based solutions for DoA estimation. The GAT network enables the compressive DoA estimation framework to learn the DoA information directly from the measurements acquired using the coded-aperture. This step eliminates the need for an additional reconstruction step and significantly simplifies the processing layer to achieve DoA estimation. We show that the presented GAT integrated single-pixel radar framework can retrieve high-fidelity DoA information even under relatively low signal-to-noise ratio (SNR) levels. Along with above work, in this thesis we analyse the performance of the main communication pillars of an end-to-end RIS-assisted satellite communication system and focus on the development of solutions to open problems that are essential in practical application.
A novel antenna configuration for microwave hyperthermia

(Graduate School, 2022-11-28) Altıntaş Yıldız, Gülşah ; Akduman, İbrahim ; Abdulsabeh Yılmaz, Tuğba ; 504182309 ; Telecommunications Engineering

Breast cancer affects approximately 2.5 million women each year and the consequences can be fatal. When treated correctly, however, the survival rates are very high. Surgical operation such as lumpectomy or mastectomy are invasive techniques that remove the partial or the whole breast. With early diagnosed cancers and the post-surgical patients, the most used therapy techniques are the radiotherapy, chemotherapy and the use of other anti-cancer agents. The economic and the psychological repercussions may be minimized by the increase efficiency of the treatments. It has been shown that with the artificial hyperthermia, elevated temperature levels at the cancer regions, the effectiveness of these modalities increase. Microwave breast hyperthermia (MH) aims to increase the temperature at the tumor location over its normal levels. During the procedure, the unwanted heated regions called hotspots can occur. The main aim of the MH is to prevent the hotspots while obtaining the necessary temperature at the tumor. Absorbed heat energy per kilogram at the breast, specific absorption rate (SAR), needs to be adjusted for a controlled MH. The choice of the MH applicator design is important for a superior energy focus on the target. Although hyperthermia treatment planning (HTP) changes for every patient, the MH applicator is required to be effective for different breast models and tumor types. In the first part of the thesis, the linear antenna arrays are implemented as MH applicators. We presented the focusing maps as an application guide for MH focusing by adjusting the antenna phase values. Furthermore, these focusing maps put forward the basic principle of focusing the energy at the breast. Sub-grouping the antenna, we obtained two phase main parameters that control the horizontal and vertical focus change. By adjusting these two phase values, we could focus the energy onto the target locations and we showed that with this simple structure, there is no need for optimization methods. However, the linear applicator performance was not successful for some target points, especially when the target is far away from both of the arrays. In the second part of the thesis, we improved the linear MH applicator. We concluded that the reason for the low performance of the linear applicator is mainly due to non-symmetrical geometry of the applicator and the resulting poor coverage. we proposed to radially re-adjust the position of the linear applicator for a better focusing ability while fixing the breast phantom. This generates multiple different applicator scheme without actually changing the applicator design. Particle swarm optimization (PSO) method is used for antenna excitation parameter selection. For the examined two targets, 135° rotated linear applicator gave 35-84% higher T BRS and 21-28% higher T BRT values than the fixed linear applicator, where T BRS stands for the target-to-breast SAR ratio and T BRT stands for the target-to-breast temperature ratio. Not only the rotated linear applicator gave higher performance, but also the circular array is rotated and the results were improved for one target. One of the main results of this study is that, for one target, the rotated linear applicator gave better results than the circular array, which is the state of the art. For the deep-seated target, 135° rotated linear applicator has 80% higher T BRS and 59% higher T BRT than the circular applicator with the same number of antennas. For the other target, the results of the linear and circular were comparable. However, the results obtained with the PSO were not robust. With different initial values (random in our study), the results were very different from each other, and we did 10 repetitions and took the best performing results. In the third part of the thesis, we presented deep-learning based antenna excitation parameter selection method. This method utilizes the learning ability of convolutional neural networks (CNN), rather than searching the solution space from random initial values as PSO does. The data set for CNN training was collected by superposing the electric fields obtained from individual antenna elements. We implemented a realistic breast phantom with and without a tumor inclusion. We used linear and circular applicators to validate the method. CNNs were trained offline with the data sets created first for the phase and then for the amplitude of the antennas. A mask of 1s and 0s is used to define the target region to be focused. This mask was given as the input to CNN models, and the corresponding phase and the amplitude values are calculated within seconds from the CNN models. The proposed approach outperforms the look-up table results, as the phase-only optimization and phase–power-combined optimization show a 27% and 4% lower hotspot-to-target energy ratio, respectively, than the look-up table results for the linear MH applicator
Analytical models and cross-layer delay optimization for resource allocation of noma downlink systems

( 2020) Gemici, Ömer Faruk ; Çırpan, Hakan Ali ; Hökelek, İbrahim ; 648904 ; Telekomünikasyon Mühendisliği Bilim Dalı

5G is introduced by 3rd Generation Partnership Project (3GPP) to satisfy the stringent delay and reliability requirements of 5G services such as industrial automation, augmented and virtual reality, and intelligent transportation. Non-orthogonal multiple access (NOMA) is one of the promising technologies for low latency services of 5G, where the system capacity can be increased by allowing simultaneous transmission of multiple users at the same radio resource. The resource allocation in NOMA systems including user scheduling and power allocation determine the mapping of users to radio resource blocks and the transmission power levels of users at each resource block, respectively. In this thesis, we first propose a genetic algorithm (GA) based multi-user radio resource allocation scheme for NOMA downlink systems. In our set-up, GA is used to determine the user groups to simultaneously transmit their signals at the same time and frequency resource while the optimal transmission power level is assigned to each user to maximize the geometric mean of user throughputs. The simulation results show that the GA based approach is a powerful heuristic to quickly converge to the target solution which balances the trade-off between total system throughput and fairness among users. The most of the resource allocation studies for NOMA systems including our GA based approach assumes full buffer traffic model where the incoming traffic of each user is infinite while the traffic in real life scenarios is generally non-full buffer. As the second contribution, we propose User Demand Based Proportional Fairness (UDB-PF) and Proportional User Satisfaction Fairness (PUSF) algorithms for resource allocation in NOMA downlink systems when traffic demands of the users are rate limited and time-varying. UDB-PF extends the PF based scheduling by allocating optimum power levels towards satisfying the traffic demand constraints of user pair in each resource block. The objective of PUSF is to maximize the network-wide user satisfaction by allocating sufficient frequency and power resources according to traffic demands of the users. In both cases, user groups are selected first to simultaneously transmit their signals at the same frequency resource while the optimal transmission power level is assigned to each user to optimize the underlying objective function. In addition, the GA is employed for user group selection to reduce the computational complexity. When the user traffic rate requirements change rapidly over time, UDB-PF yields better sum-rate (throughput) while PUSF provides better network-wide user satisfaction results compared to the PF based user scheduling. We also observed that the GA based user group selection significantly reduced the computational load while achieving the comparable results of the exhaustive search. The low latency objectives of URLLC services such as industrial control and automation, augmented and virtual reality, tactile Internet and intelligent transportation requires delay analysis which cannot be possible using the rate limited traffic demands. The packet based traffic model with random inter-arrival times and packet sizes have to be utilized. New analytical models using packet based traffic model with random inter-arrival times and packet sizes are of paramount importance to develop high performance resource allocation strategies satisfying the challenging latency requirements of 5G services. As the third contribution, we propose an analytical model to characterize the average queuing delay for NOMA downlink systems by utilizing a discrete time M/G/1 queuing model under a Rayleigh fading channel. The packet arrival process is assumed to be Poisson distributed while the departure process depends on network settings and resource allocation. The average queuing delay results of the analytical model are validated through Monte Carlo simulation experiments. One of the main results is that the ergodic capacity region of NOMA is a superset of OMA indicating that the NOMA can support higher service rate and lower latency using the same resources such as transmission power and bandwidth. Furthermore, the proposed analytical model is applied for the performance evaluation of the 5G NR concept when the NOMA is utilized. The model accurately predicts that the average queuing delay decreases when wider bandwidth and shorter time slot duration are employed in 5G NR. The outage probability becomes an important metric that should be minimized to address the reliability aspect of the URLLC services. We utilize the common outage condition such that the user fails either decoding its own signal or performing SIC for the signals of other users at the receiver when the SINR is lower than a predefined outage threshold. As the fourth contribution, the optimum power allocation for a single resource block that minimizes the system outage probability under Rayleigh fading channel, where a common signal to interference plus noise ratio (SINR) level is utilized as an outage condition, is provided as a closed form expression. The accuracy of the proposed optimum power allocation model is validated by the Monte Carlo simulations. The numerical results show that the outage probability of OMA with the fractional power allocation is lower than NOMA with the optimum power allocation. The results indicate that the trade-off between the outage and spectral efficiency in NOMA should be carefully controlled to meet higher throughput and lower latency objectives of 5G. The last contribution considers the reliability and latency aspects jointly such that the discrete time M/G/1 queuing model of a NOMA downlink system is extended by taking the outage condition into account. The departure process of the queuing model is characterized by obtaining the first and second moment statistics of the service time that depends on the resource allocation strategy and the packet size distribution. The proposed model is utilized to obtain the optimum power allocation that minimizes the maximum of the average queuing delay (MAQD) for a two-user network scenario. The Monte Carlo simulation experiments are performed to numerically validate the model by providing MAQD results for both NOMA and orthogonal multiple access (OMA) schemes. The results demonstrate that the NOMA achieves lower latency for low SINR outage thresholds while its performance is degraded faster than OMA as the SINR outage threshold increases such that OMA outperforms NOMA beyond a certain threshold. Another important result is that the latency performance of NOMA is significantly degraded when the 5G NR frame types having wider bandwidth are utilized. The results provide powerful insights for 5G ultra-reliable low-latency communication (URLLC) services.
Antenlerin hızlı ve doğru tasarımı için esnek hesaplamaya dayalı sayısal karma yöntemler

(Lisansüstü Eğitim Enstitüsü, 2023-07-11) Yiğit, Mahmud Esad ; Günel, Tayfun M. ; 504142305 ; Telekomünikasyon Mühendisliği

Mikrodalga devre ve sistemlerin karmaşıklığındaki artıştan dolayı basitleştirilmiş teorik modeller, yapının performansının doğru şekilde tespit edilmesinde artık yeterli gelmemektedir. Bu yüzden tasarım güvenilirliğini garantiye almak için tam-dalga elektromagnetik analizin kullanımı zaruri olmuştur. Bunun yanında simülasyon (benzetim) yazılımları ve bilgisayar donanımlarındaki gelişmelere rağmen nümerik optimizasyon algoritmaları hala yüksek hesaplama yükü ve maliyetine sahiptir. Yüksek kalitede modellemeler mikrodalga sistemlerinin daha iyi ve verimli şekilde tasarımını mümkün kılmıştır. Anten analizi ve sentezi için de bu modellemeleri kullanan elektromagnetik tabanlı bazı simülasyon yazılımları geliştirilmiştir. Böylece daha büyük ve karmaşık sistemler tasarlanabilmektedir. Fakat elektromagnetik simülasyonların hesaplama yükleri çok fazladır. Tasarım parametreleri arttıkça yazılımlar ile yapılan analizlerde işlem yükü ve harcanan zaman artmaktadır. Antenlerde istenilen cevabı almak için fiziksel yapısındaki değişiklikler için optimizasyon işleminin uygulanması gerekir. Tasarımcının bilgi ve tecrübesi yeterli olsa da deneme yanılma yöntemiyle tekrarlı olarak yazılımların çalıştırılması tasarım süresini uzatmaktadır. Tasarım karmaşıklığı arttıkça daha yüksek doğrulukta ve hızda tasarım yöntemleri gerekmektedir. Bu çalışmada, anten tasarımı için hesaplama süresini kısaltmak ve sonuçları yüksek doğrulukla elde etmek için yeni karma yöntemlerin geliştirilerek kullanılması amaçlanmıştır. Hesaplama süresini kısaltmak ve istenilen performansa en yakın performansı veren anten yapısını tasarlayabilmek için de Esnek Hesaplamaya (EH) dayalı sayısal karma yöntemlerin geliştirilmesi ve daha sonra anten tasarımda kullanılması hedeflenmiştir. "Esnek Hesaplama", 1994 yılında Lotfi A. Zadeh tarafından ortaya atılmıştır. EH, kesin olmayan ve belirsiz koşullar içeren problemler için gözlenebilir, güvenilir ve düşük maliyetli çözümler sağlayan bir grup yöntemi ifade eder. EH tekniklerinde elde edilen sonuçlar matematiksel olarak kesin değildir ve yaklaşık optimum sonuçlar elde edilir. EH, çeşitli hesaplama tekniklerinin toplamıdır. Bazı EH teknikleri ve uygulamaları arasında bulanık mantık, evrimsel algoritmalar, Yapay Sinir Ağları (YSA) ve Destek Vektör Makineleri (DVM) gibi yöntemler yer alır. Bu tez çalışmasında literatürde verilen ve sık kullanılan evrimsel algoritmaların yanında yeni karma optimizasyon algoritmaları da geliştirilmiş ve anten tasarımlarında kullanılmıştır. Bu tezin birinci bölümünde tezin amacı ortaya koyulmuş, bu konuda literatürde yapılan çalışmalara kısaca değinilmiştir. İkinci bölümde ise anten tasarımı için gereken önemli parametreler ve tanımları verilmiştir. Ayrıca literatürde yaygın olarak kullanılan bazı elektromagnetik simülasyon yazılımları anlatılmıştır. Üçüncü bölümde tez çalışmasında kullanılan esnek hesaplama yöntemlerinden bahsedilmiştir. YSA, Destek Vektör Regresyonu (DVR) yöntemlerinin yanında Genetik Algoritma (GA), Parçacık Sürü Optimizasyonu (PSO) ve Taguchi Algortiması (TA) gibi literatürde verilen bazı evrimsel algoritmaların akış diyagramları verilerek ayrıntılı olarak anlatılmıştır. Daha sonra bu tez çalışmasında yeni geliştirilen Konveks-Genetik-Taguchi Algoritması (KGTA), Hibrit (Karma) Parçacık Sürü Taguchi Optimizasyonu (HPSTO) ve Taguchi-Genetik-Parçacık Sürü Optimizasyonu (TAGAPSO)'nun detayları açıklanmış ve akış şemaları verilmiştir. Yeni geliştirilen bu karma yöntemlerin performansları literatürde verilen bazı test fonksiyonları yardımıyla incelenmiştir. Test sonuçları, yeni geliştirilen karma yöntemlerin içerdikleri yöntemlere göre üstünlüklerini göstermiştir. Dördüncü bölümde ise tez çalışmasında geliştirilen EH tabanlı karma yöntemler ile literatürde verilen bazı yöntemler birlikte veya ayrı ayrı kullanılarak özgün mikroşerit antenlerin, konformal antenlerin ve anten dizilerinin tasarımları yapılmıştır. Tasarım işlemleri için HFSS ve MATLAB yazılımları kullanılmıştır. HFSS ve MATLAB ile elde edilen simülasyon ve optimizasyon sonuçlarıyla karşılaştırmalar yapılmıştır. Yapılan karşılaştırmalar sonucunda önerilen karma yöntemlerin üstünlükleri ortaya konulmuştur. Ayrıca tasarımı yapılan antenlerden bir tanesi gerçeklenerek teorik yaklaşımla elde edilen sonuçların doğruluğu gösterilmiştir. İlk olarak bir silindirik dikdörtgen mikroşerit konformal antenin tasarımı GA tabanlı YSA yaklaşımı, GA tabanlı DVR yaklaşımı ve HFSS'in optimizasyon aracı kullanılarak yapılmıştır. GA tabanlı YSA, GA tabanlı DVR ve HFSS optimizasyonun sonuçları gereken süre ve doğruluk yönünden karşılaştırılmış ve DVR'nin üstünlüğü görülmüştür. Daha sonra silindirik dikdörtgen halka mikroşerit konformal anten tasarımında PSO tabanlı YSA ve DVR yaklaşımları kullanılmıştır. DVR'de kernel fonksiyonu olarak Radyal Temelli Fonksiyon (RTF)'nin yanında dalgacık kernel fonksiyonları da kullanılmıştır. Bilindiği kadarıyla dalgacık kernel fonksiyonları DVR ile anten tasarımında ilk defa kullanılmıştır. Anten tasarımında eğitim süresi ve doğruluk bakımından dalgacık kernel fonksiyonlarının RTF ve YSA'ya olan üstünlükleri gösterilmiştir. Anten tasarımı PSO tabanlı yaklaşımla yapılırken dalgacık kernelleri kulanıldığına RTF kerneline göre daha az iterasyon ve zaman gerekmiş ayrıca daha doğru sonuçlar elde edilmiştir. Bir sonraki çalışmada, WLAN'ın iki frekans bandında da çalışacak çift yarıklı bir mikroşerit anten tasarımı DVR yaklaşımı ile yapılmıştır. Bilindiği kadarıyla iki bantta çalışacak antenin DVR ile tasarımı ilk defa yapılmıştır. Çift yarıklı dikdörtgen mikroşerit antenin oluşturulan DVR modeli istenen rezonans frekansını veren yarık boyutu değerlerini bulmak için kullanılmıştır. DVR modeli tersine bir şekilde çalıştırıldığı için ilave bir optimizasyon yöntemi kullanılması gerekmemiştir. Aynı yama boyutları ve taban malzemesine sahip analitik fonksiyonlar kullanılarak tasarlanan klasik dikdörtgen mikroşerit anten (DMA)'e göre antenin performans çıktılarındaki iyileşmeler gösterilmiştir. Diğer bir çalışmada, DVR modeli yaklaşımıyla anten yamasına birden fazla yarık ve yay-kesiği uygulanarak, istenen rezonans frekansları ve kazanç değerlerine sahip üç bantlı özgün bir mikroşerit anten tasarlanmıştır. Bilindiği kadarıyla üç bantta çalışacak anten ilk defa DVR yaklaşımı ile tasarlanarak gerçeklenmiştir. DVR yaklaşımı ile tasarlanan antenin HFSS simülasyon sonuçları ve gerçeklenen antenin ölçüm sonuçları verilmiştir. Gerçeklenen antenin performansı literatürde verilen üçlü bant özelliğine sahip antenler ile karşılaştırılmıştır. Ayrıca, karşılaştırma amacıyla HFSS'deki optimizasyon aracı kullanılarak anten yeniden tasarlanmıştır. DVR model yaklaşımı ve HFSS optimizasyonu ile tasarım, sonuçlarının doğruluğu ve tasarım süresi bakımından karşılaştırılmıştır. Daha sonra doğrusal anten dizilerinin YDS ve YGDG'lerini istenilen değerlerde elde etmek için yeni geliştirilen KGTA, HPSTO ve TAGAPSO karma optimizasyon algoritmaları kullanılmıştır. Yeni geliştirilen karma algoritmalar ile elde edilen sonuçlar içerdikleri diğer algoritmalarla elde edilen sonuçlarla karşılaştırılarak üstünlükleri ortaya koyulmuştur. Son bölümde ise tez çalışması genel olarak özetlenerek elde edilen sonuçlar kısaca açıklanmış ve gelecekteki çalışmalar için öneriler sunulmuştur.
Clinical assessment of the microwave imaging system forbreast cancer screening and early detection

(Graduate School, 2023-04-26) Janjic, Aleksandar ; Çayören, Mehmet ; Akduman, İbrahim ; 504182310 ; Telecommunication Engineering

Female breast cancer has surpased lung cancer, as the most diagnosed cancer in women population, with around 2.3 million cases arising each year. If diagnosed in late stages, it can be highly lethal, with the survival rate of only 25%. Thus, detecting the cancer in an early stage can have a major impact on decreasing the death rate of the patients. Nowadays, mammography is considered as a gold standard for breast cancer screening and diagnostics. Beside mammography, ultrasound, and magnetic resonance imaging can be used to detect the cancer. However, there are several risk factors that are limiting mentioned imaging modalities, such as: ionizing radiation exposure, pain induced by breast compression, overdiagnosis, false-positive examinations, falsenegativity in dense breasts, operator dependancy, prolonged procedures, high hospital costs, and special facility requirements. Microwave breast imaging emerged as a promising novel imaging technology that can, potentially, contribute to the field of breast cancer early screening and diagnostics, mostly because of its non-ionizing and non-invasive nature. Harmless radiation offers the opportunity of frequent scanning, even for the women of an early age, such as 18. Early-age and routine tests are crucial, especially for women with hereditary genetic mutations, where there is a considerable risk of breast cancer appearance. Beside its non-ionizing, and non-invasive nature, microwave imaging offers fast and painless scans, which can significantly increase the number of breast check-up tests, consequently increasing the number of detected early-stage cancers. Consequently, microwave breast imaging can have can substantially impact on the long-term breast cancer survival rate. The technology itself utilizes the difference in electromagnetic properties of healthy and cancerous tissue, as well as the dielectric difference between different type of cancerous tissues (benign or malignant), to detect the presence of anomalies inside the patient's breast and provide their pathology. In the first part of the thesis, we integrated inverse scattering algorithm to acquire the microwave images, and provide information about breast cancer location (detect the breast cancer), from the data collected with the microwave breast imaging device, namely SAFE, developed by the joint work of Mitos Medikal Technologies A.S. and the Medical Device Research, Development, and Application Laboratory of Istanbul Technical University. Dataset used in the study (scans from 115 patients), was acquired through the clinical trials performed by the Marmara University School of Medicine. In addition to the breast lesion detection, we analyzed the effect of the factors of interest, such as: breast density and size, tumor size, as well as patient's age, on the SAFE clinical capabilities. Results show, that we were able to detect 63% of breast lesions, where the breast size had a high impact on the overall score. Significantly lower number of lesions were detected in smaller breasts (51%), compared to the large ones (74%). Density also influenced our inverse scattering approach, as the overal rate of 76%, we achieved in fatty breasts, decreased to 56% in dense breasts. Second part of the thesis is reserved for the machine learning approach, namely adaptive boosting, we implemented on the SAFE dataset, to classify breast lesions, based on their pathology. We used the same dataset as in the first part of the thesis. As in the previous study, we analyze the effect of breast density and size, tumor size, and patient's age, on the used data. In addition, we perform statistical analysis (two-sample t-test) to determine if the difference between the benign and malignant dataset exists. In the existing dataset, 70 benign, and 43 malignant lesions were present. We exclude two cases, due to the unknown pathology. Our machine learning approach achieved the accuracy of 78%, sensitivity of 79% and specificity of 77%. The results indicate that we were able to classify both, benign and malignant lesions, at similar rate. Participant's age was the only factor that highly affected our approach outcome, where the overall rate (accuracy) of the device in young patient group was 84%, compared to the 76% achieved in older patient group. In the third part of the thesis, we implement another machine learning approach, namely Gradient Boosting, to distinguish benign from malignant lesions, considering new dataset, acquired from latest SAFE clinical trials. Additionally, compared to the previous studies, we changed the measurement unit component of the device. Fiftyfour patients were analyzed, where 29 of them had benign, and 25 malignat findings. As in the previous study, we apply statistical analysis (two-sample t-test), to determine if the difference between the benign and malignant dataset exists. Sensitivity, specificity and accuracy we achieved were 80%, 83% and 81%, showing that, in this study as well, we were able to classify both benign and malignant lesions at similar rate, despite of the hardware and software changes implemented. Contrary to the previous studies, multiple factors (breast size, density and age) affected our approach outcome. We achieved significantly higher accuracy in larger breasts (86%), compared to the smaller ones (78%). Additionally, accuracy acquired in dense breast (67%) was significantly lower than in fatty ones (93%). At the end, our method accuracy was 88% in older patient group, compared to the 71% in younger group.
Compressive sensing of cyclostationary propeller noise

(Graduate School, 2023-09-12) Fırat, Umut ; Akgül, Tayfun ; 504122303 ; Telecommunication Engineering

This dissertation is the combination of three manuscripts -either published in or submitted to journals- on compressive sensing of propeller noise for detection, identification and localization of water crafts. Propeller noise, as a result of rotating blades, is broadband and radiates through water dominating underwater acoustic noise spectrum especially when cavitation develops. Propeller cavitation yields cyclostationary noise which can be modeled by amplitude modulation, i.e., the envelope-carrier product. The envelope consists of the so-called propeller tonals representing propeller characteristics which is used to identify water crafts whereas the carrier is a stationary broadband process. Sampling for propeller noise processing yields large data sizes due to Nyquist rate and multiple sensor deployment. A compressive sensing scheme is proposed for efficient sampling of second-order cyclostationary propeller noise since the spectral correlation function of the amplitude modulation model is sparse as shown in this thesis. A linear relationship between the compressive and Nyquist-rate cyclic modulation spectra is derived to utilize matrix representations for the proposed method. Cyclic modulation coherence is employed to demonstrate the effect of compressive sensing in terms of statistical detection. Recovery and detection performances of sparse approximation algorithms based on greedy pursuits are compared. Results obtained with synthetic and real data show that compression is achievable without lowering the detection performance. Main challenges are weak modulation, low signal-to-noise ratio and nonstationarity of the additive ambient noise, all of which reduce the sparsity level causing degraded recovery and detection performance. Higher-order cyclostationary statistics is introduced to characterize propeller noise due to its non-Gaussian nature. The third-order cyclic cumulant spectrum, also known as the cyclic bispectrum, is derived and its sparsity is demonstrated for the amplitude modulated propeller noise model. Cyclic modulation bispectrum is proposed for feasible approximation of the cyclic bispectrum based solely on the discrete Fourier transform. Additionally, compressive sensing of the cyclic modulation bispectrum is suggested. Numerical results are presented for acquisition of the propeller tonals using real-world underwater acoustic data. Tonals estimated by third-order cyclic modulation bicoherence are more notable than the ones obtained by second-order cyclic modulation coherence due to latter's higher noise floor. Sparse recovery results show that frequencies of the prominent tonals can be obtained with sampling significantly below the Nyquist rate. The accurate estimation of tonal magnitudes, on the other hand, is challenging even with large number of compressive samples. Compressive sensing can be extended to solve underdetermined system of equations which appears in direction-of-arrival estimation with uniform linear arrays. An estimator is proposed based on the compressive beamformer for cyclostationary propeller noise. Its asymptotic bias is derived, which is inherited from the conventional beamformer when there are multiple sources. Squared asymptotic bias and the finite-sample variance, also derived explicitly, constitute the mean-squared error. Spectral averaging is suggested to mitigate this error by decreasing the adverse effect of the spatial Dirichlet kernel. For low signal-to-noise ratios, averaging enables the proposed estimator to outperform the methods that assume stationarity. This is achieved even under weak cyclostationarity, numerous closely-spaced sources and few sensors. The proposed methods are not only suitable for compressive sensing of propeller cavitation noise but also for general class of cyclostationary signals. Relevant research areas include but are not limited to communication, radar, acoustics and mechanical systems with applications such as spectrum sensing, modulation recognition, time difference of arrival estimation, time-frequency distributions, compressive detection and rolling element bearing fault diagnosis.
Deep learning for inverse problems in imaging

(Graduate School, 2024-02-15) Karaoğlu, Hasan Hüseyin ; Ekşioğlu, Ender Mete ; 504162310 ; Telecommunication Engineering

Efforts to solve inverse imaging problems with deep learning techniques have increased the performance results of the algorithms. However, it has been observed that the increase in the performance of deep networks is mostly directly proportional to their more advanced and powerful architectural design. Acting with a pure architectural design leads researchers to dead end in the development of new solutions. On the other hand, in the classical era before deep learning, inverse imaging problems have been solved by making use of clean image models. Among model-based methods from classical period, the brightest results belong to the algorithms based on sparsity in transform domain. Contrary to this known fact, the common habit in deep learning literature to solve inverse problems is to find a model (map) on pixel domain rather than transform domain. Only a few studies have addressed training of deep networks in transform domain. In image denoising problem, deep networks that prefer training in transform domain have mostly chosen the discrete wavelet transform. The major factor in such a choice is that the wavelet transform produces image-like spectrum coefficients (subband images). Convolution layer is widely used in architecture of networks which are proposed for inverse imaging problems and it searches for a relationship between neighboring values of the input data of a convolution layer. In other words, it is reasonable to use wavelet transform coefficients in deep networks. Therefore, these wavelet-based networks have given effective results for inverse imaging problems. However, transforms such as DCT, which are known to provide good energy compaction property for most images in solving inverse problems, have not been preferred in deep networks. This is because they do not produce spectra such as wavelet subband images. In JPEG compression artifact removal problem, the primary source of compression artifact is the quantization of the transform coefficients of an image. During the quantization, transforms which have high compression ability such as the DCT are chosen. However, the majority of compression artifact removal algorithms have used deep neural networks that find a map in pixel domain. Based on these observations above, in this thesis study, novel transform based approaches are presented for image denoising and JPEG compression artifact removal problems. DCTNet is a deep convolutional neural network that utilizes the DCT for image denoising problem. In DCTNet, DCT coefficients of image patches extracted overlappingly from noisy image are calculated. Then, the spectral coefficients of all the patches are ordered to form a channel, which are suitable for subsequent processing in convolution layers. It has been shown mathematically that such a usage corresponds to the process of convolution of 2D DCT basis images with noisy image. Similarly, it has been shown that the calculation of inverse DCT coefficients can be done by a convolution operation with the same basis images. In this way, effective training of CNN networks in the DCT domain is carried out and it is shown that the proposed DCTNet give successful results in image denoising problem. Harmonic Nets are proposed by utilizing the DCTNet structure for JPEG compression artifact removal problem. In addition to the DCT, sine and Hartley transforms are also utilized to remove compression artifacts. These two transforms having high compression capability, which have not been discussed in the context of JPEG until now, are used in deep networks for the first time. Architectural changes have occurred in designing the proposed Harmonic Nets due to some differences between all three transforms. Experimental study have shown that although the proposed networks have fewer parameters and a simpler network topology, they surpass some of the advanced deep networks with the highest performance results and lag behind the others by a small margin. Within the scope of this thesis, compressed sensing MRI problem, which is a common technique in reconstructing magnetic resonance images, is also discussed. Over the past decade, it has been shown theoretically and empirically that the solution of additive white Gaussian noise removal problem is important not only for denoising problem but also for other inverse imaging problems. In plug-and-play methods, additional constraints are added to the cost function of any inverse problem. Since one step of the resulting new problem is similar to Gaussian denoising problem, this step is attempted to be solved with any Gaussian denoiser iteratively. In this study, inspired by PnP research wave, a simple and vanilla convolutional neural network for Gaussian denoising problem is proposed for CS MRI problem. In the experiments where convergence analysis of the proposed scheme is performed, we confirmed that our algorithm is successful for MR image reconstruction.
From media-based modulation to reconfigurable intelligent surfaces: Novel index modulation solutions

(Graduate School, 2022-11-11) Yiğit, Zehra ; Altunbaş, İbrahim ; Başar, Ertuğrul ; 504172313 ; Telecommunication Engineering

. In these studies, we adapt the classical Hurwitz-Radon family of matrices and the new circular matrix-based STBC design to MBM in order to achieve various orders of transmission diversity gains over a single RF chain. Moreover, through extensive analyses, we obtain the theoretical bit error rate (BER) and capacity performance of the proposed schemes, which are supported via comprehensive computer simulations. In the subsequent study, we deploy an RIS with passive reflecting elements, which are capable of inducing plain phase shifts to assist the classical multiple-input multiple-output (MIMO) and IM-based MIMO transmission systems. In this study, in order to maximize the signal-to-noise (SNR) of the overall cascaded system, without applying computationally complex beamforming techniques, we propose a cosine similarity theorem-based low-complexity algorithm for adapting the phase shifts of the RIS reflecting elements. Moreover, a semi-analytical probabilistic approach is developed to derive the theoretical average bit error probability (ABEP) of the system. Furthermore, the validity of the theoretical analysis is supported through extensive computer simulations. Although a massive literature has grown up around passive RIS-aided studies, most recently, the potential of active RISs that are capable of achieving ultimate capacity gains at the expense of additional power constraints stimulates novel research domains. In that sense, we develop a novel IM scheme in which a hybrid RIS with both active and passive reflecting elements acts as a transmit information unit. In this study, according to incoming information bits, the corresponding RIS is divided into sub-groups which consist of either passive elements with simple phase shifts or active elements with adjustable amplitudes and phases in a way that each RIS realization creates a signal with clearly distinguishable magnitude. In other words, the proposed scheme constitutes a virtual amplitude shift keying (ASK) modulation. Moreover, through comprehensive theoretical analyses and computer simulations, the BER, achievable rate and energy efficiency performance of the proposed scheme are compared with existing fully passive RIS, fully active RIS and reflection modulation (RM) systems. In the last study of this thesis, in order to simplify transceiver complexity of classical multi-user transmission schemes, we propose a new over-the-air beamforming concept that completely transfers the inter-user interference cancellation duties of the transmitter to an active RIS. In the proposed concept without resorting to any hardware-complex pre/post signal processing techniques at the transmitter and the receiver, the amplitudes and phases of the active reflecting elements at the RIS are optimized to maximize sum-rate gains of a multi-user downlink transmission system. Moreover, taking inspiration from this over-the-air beamforming concept, a new receive IM scheme that transmits additional information bits to specify the index of the effective received antenna is also proposed. Contrary to the existing receive IM system designs that conduct transmit beamforming to steer the overall information to the specified received antenna, in the proposed receive IM scheme, without applying any transmit beamforming techniques, the reflection coefficients of the active RIS are adjusted to orient the overall reflected signal in direction of the effective received antenna. In these proposed over-the-air beamforming concepts, to optimize the reflection coefficients of the active RISs, two distinct semidefinite relaxation (SDR)-based optimization problems are formulated, which can be effectively solved through the CVX convex optimization toolbox. Moreover, through comprehensive simulation results, the sum-rate and BER performance of the proposed designs are investigated. In summary, this thesis presents novel IM-based physical layer solutions for future generation networks in various facets starting from the classical MBM to the emerging RIS-aided systems. Through this process, we resort to different approaches including STBC techniques, low-complexity algorithms, convex optimization, physical channel models, etc. Moreover, in order to demonstrate the performance of the systems, through comprehensive computer simulations, we compare our all system designs with the classical systems and their state-of-the-art competitors. Then, in order to support these results, we attempt to derive theoretical performance analyses.
Homojen olmayan ortamlara ilişkin green fonksiyonları ve çeşitli uygulamaları

(Lisansüstü Eğitim Enstitüsü, 2022-09-14) Arıcı Konakyeri, Eda ; Yapar, Ali ; 504102300 ; Telekomünikasyon Mühendisliği

Elektromanyetik teoride homojen olmayan ortamlara veya homojen olmayan ortamların içerisinde yer alan saçıcı cisimlere ilişkin düz ve ters saçılma problemleri üzerine yapılan araştırmalar literatürde çok önemli bir yer tutmaktadır. Gerçekte pratik hayattaki tüm elektromanyetik uygulamalarda karşılaşılan ortamlar doğrudan bu türden homojen olmayan yapılardır. Bu kapsamda gerek düz saçılma gerekse ters saçılma olsun herhangi bir elektromanyetik probleminde ortam ve saçıcıların herhangi bir yaklaşıklık yapılmadan olduğu gibi gerçek profillerinin göz önüne alınması yüksek doğruluk ve hassas analizler için oldukça önemlidir. Saçılma problemleri genel olarak diferansiyel denklemler içerir. Bilindiği üzere bu denklemlerin çözümünde Green fonksiyonları hayati öneme sahiptir. Temel olarak Green fonksiyonları, saçılma problemlerinde karşılaşılan diferansiyel denklemleri veya denklem sistemlerini yüzey veya hacim integral denklemlerine dönüştürmek için kullanılır. Green fonksiyonu, verilmiş bir diferansiyel denklem için sağ tarafın normalize edilmiş noktasal kaynak (iki boyutta çizgisel kaynak), başka bir deyişle Dirac delta genelleştirilmiş fonksiyonu olması halindeki çözüm olup sistemin birim dürtü (impuls responce) cevabı olarak düşünülebilir. Klasik saçılma problemlerinde saçıcının içerisinde yer aldığı arka plan uzayı çoğu zaman homojen basit bir ortam, bazı özel problemlerde de tabakalı ortamlar olarak düşünülür. İlk halde Green fonksiyonlarının doğrudan analitik ifadeleri mevcuttur. İkinci durumda (tabakalı ortamlar) ise Fourier teorisine dayanan integral gösterimler veya sonsuz seri ifadeler yardımıyla Green fonksiyonları kolaylıkla hesap edilebilir. Oysa saçıcıyı barındıran arka plan uzayı homojen değilse ya da doğrudan saçıcının kendisi ve arka plan uzayının bir arada homojen olmayan bir ortam olarak modellenmesi durumunda Green fonksiyonu doğrudan analitik olarak ifade edilemez. Gerçekte böyle bir problemin kendisi de normalize bir noktasal (iki boyutta çizgisel) kaynakla aydınlatılmış homojen olmayan bir cisme ilişkin bir düz elektromanyetik saçılma problemine karşı düşer. Böyle genel bir konfigürasyona diğer bir deyişle homojen olmayan ortamlara ilişkin Green fonksiyonlarının hesabı ancak sayısal yöntemlerle gerçekleştirilebilir. Sözü edilen bu problemin bilinmeyeni Green fonksiyonu olduğundan kaynak noktası uzayın herhangi keyfi bir noktası olabilmelidir. Tüm uzay, arka planı homojen bir ortamın içerisindeki homojen olmayan bir yapı olarak düşünüldüğünde, kaynağın homojen olmayan bölge dışarısında olduğu durum için Green fonksiyonu bilinen yöntemlerle elde edilebilir. Burada klasik düz saçılma problemi noktasal kaynak halinde sayısal olarak çözülür ve doğrudan sonuca gidilebilir. Ancak kaynak noktası (Dirac delta kaynağın yerleştirildiği nokta) homojen olmayan bölgenin içinde kaldığında kaynak ve gözlem noktalarının üst üste gelmesi halinden (çakışmasından) dolayı yüksek dereceden tekillikler meydana gelir ve problem klasik yaklaşımlarla çözülemez. Bu tez çalışmasında bu tekilliğin çözümüne ilişkin momentler yöntemine dayanan orijinal bir sayısal yöntem önerilmiştir. Böylelikle kaynak noktasının konumuna bağımlı olmaksızın herhangi bir kaynak-gözlem konfigürasyonu için herhangi bir homojen olmayan ortama ilişkin Green fonksiyonunun sayısal olarak hesaplanabileceği gösterilmiştir. Uygulanan yöntemin ana yaklaşımı ilgili Green fonksiyonunu tekil ve tekil olmayan iki ayrı fonksiyonun toplamı olarak ifade etmeye dayanmaktadır. Bu dekompozisyon öncelikle ilgili noktadaki tekilliği başarılı bir şekilde yansıtmakta daha sonra da tekil olmayan kısmın uygun bir integral denklem yardımıyla sayısal olarak çözülmesini sağlamaktadır. Önerilen bu yeni yaklaşımda ilgili homojen olmayan bölge dikdörtgen formda küçük alt bölgelere (hücrelere) ayrılarak her bir hücre için analitik hesaplar yapmaya elverişli eşdeğer dairesel hücre yaklaşımı kullanılmıştır. Bu hücrelerin boyutlarının yeteri kadar küçük seçilmesi halinde, hücre içerisinde ortama ilişkin ilgili parametrelerin yaklaşık olarak sabit olduğu kabul edilerek çözüme gidilmiştir. Bu nedenle yeteri kadar hücre sayısı olması önemlidir. Green fonksiyonunun tekil olmayan bu parçası ile ilgili sayısal çözümü elde etmek için kurulan integral denklem, yüksek dereceden tekillikler içerir. Bu aşırı-tekil (hyper-singular) integral denklemde eşdeğer hücreler üzerindeki integraller analitik olarak hesaplanarak oldukça basit ve güvenilir bir çözüm elde edilmiştir. Hücre integralleri analitik olarak hesaplanabildiğinden eşdeğer hücre ve hücre içinde elektromanyetik parametrelerin sabit kabul edilmesi dışında fazladan bir yaklaşıklık yapılmamıştır. Bu nedenle oldukça yüksek doğrulukta sonuçlara erişilmiştir. Sonuç olarak homojen olmayan ortamlara ilişkin Green fonksiyonu kaynağın konumundan bağımsız olarak önerilen yöntem ile elde edilmiştir. Bu sonuç düz ve ters saçılma problemi araştırmaları için oldukça önemlidir. Daha önce belirtildiği üzere, yukarıda özetlenen yöntem ile bulunan homojen olmayan ortam Green fonksiyonlarının doğrudan uygulama alanı bulabileceği temel alan elektromanyetik saçılma problemleridir. Bu kapsamda bu tez çalışmasında öncelikle düz saçılma problemlerine ilişkin uygulamalar yapılmış ve elde edilen sonuçlar analitik sonuçlarla kıyaslanarak yöntem ve yaklaşımların doğruluğu ispatlanmıştır. Ayrıca literatürde yer alan bir çalışma ile kıyaslama yapılarak yöntemin etkinliği ve doğruluğu bağımsız bir örnekle de desteklenmiştir. Devamında gerçek homojen olmayan ortamlarda yöntemin işlerliğini görmek adına insan beynine ilişkin bir kesit ele alınmış ve kaynak hem kesit içerisine hem de kesit dışarısına ayrı ayrı yerleştirilerek Green fonksiyonu ve alan dağılımı incelenmiştir. Bu tip yüksek kontrasta sahip ortamlarda yapılan analizlerde gelen dalganın ortam içerisine yeteri kadar nüfuz etmesi için uygun bir arka plan uzayı gereksinimine dikkat çekilmiş ve bununla ilgili sonuçlar paylaşılmıştır. Ayrıca önerilen yöntemle elde edilen Green fonksiyonu kullanılarak bir saçılan alan ifadesi verilmiştir. Bu saçılan alan hesabının, klasik olarak bilinen ve toplam alanı içeren saçılan alan ifadesine göre hesaplama yükü açısından daha verimli olduğu söylenebilir. Bu durum, literatürde yer alan birçok yinelemeli yöntem açısından önemlidir. Düz saçılma problemi analizinde elde edilen etkili sonuçlar ve yapılan analizler bu yöntemin etkinliğini açık bir şekilde ortaya koymaktadır. Homojen olmayan ortamlara ilişkin Green fonksiyonlarının bir diğer uygulama alanı olan ters saçılma problemlerinde öncelikle düz saçılma problemi çözümünden sağlanacak verinin yüksek derecede doğru olması kritiktir. Bu tez çalışmasında düz saçılma problemleri için yapılan kıyaslamalı uygulamalar yöntemin ters saçılma problemlerinde güvenilir bir şekilde kullanılabileceğine bir kanıttır. Yöntemin ters saçılma problemlerinde etkinliğini görmek adına ise iki farklı ters saçılma problemi analizi yapılmıştır. Bunlardan ilki mikrodalga beyin görüntüleme uygulaması olup kanamalı bir beyindeki kanamanın yer tespiti çalışmasıdır. Sağlıklı ve sağlıksız beyinlerden saçılan alanların farkından yola çıkarak elde edilen kontrast fonksiyonunun hesaplanması ile sağlıksız beyinde yer alan kanamalı bölgenin yer tespiti yapılmıştır. Burada sağlıklı ve sağlıksız beyin Green fonksiyonlarının birbirlerine çok benzer olması sebebiyle fark saçılan alan ifadesinde sağlıklı beynin Green fonksiyonu kullanılmıştır. Problem kötü oluşturulmuş bir sistem olduğundan Tikhonov regülarizasyon yöntemine başvurulmuştur. Bu özel görüntüleme probleminde daha iyi sonuç elde etmek amacıyla çoklu aydınlatma kullanılmıştır. Ayrıca özellikle dalgaların beyin içine nüfuz edebilmesi için uygun arka plan uzayı seçimi bu problemin çözümü için önemlidir. Önerilen yöntem ile farklı büyüklük, adet ve elektromanyetik özelliklerdeki kanamalı bölgelerin tespiti yapılmıştır. Kanamalı bölge ile beynin elektromanyetik özellikleri arasındaki fark arttıkça görüntülemede netlik bir miktar azalmaktadır. Bu durumda kanamalı bölge için arka plan uzayı beynin kendisi olduğundan bu beklenen bir sonuçtur. Bu yöntemin kullanılabilmesi açısından en kritik konu, görüntülenecek beynin kanama olmadan önceki saçılan alan analizinin biliniyor olmasıdır. Bir diğer ters saçılma problemi uygulaması olarak mevcutta uygulamaları olan Ters Zaman Göçü yöntemi incelenmiştir. Homojen olmayan ortamlara ilişkin Green fonksiyonu bu yöntemde kullanılmış ve klasik Green fonksiyonu ile elde edilen sonuçlarla kıyaslama yapılmıştır. Yapılan incelemeler sonucunda önerilen yöntemin bu ters saçılma problemi uygulamasında da etkili olduğu görülmüştür. Klasik Green fonksiyonu ile elde edilen sonuçlar kıyaslandığında önerilen yöntemin birçok uygulamada görece daha net sonuçlar verdiği görülmüştür. Bu yöntemde uygulamalar basit kanonik yapılar üzerinde yapılmış, daha yüksek kontrasta sahip yapılara ilişkin yapılan analizler sonraki çalışmalarda incelenmek üzere plana alınmıştır. Sonuç olarak önerilen yöntemle elde edilen homojen olmayan ortamlara ilişkin Green fonksiyonu hem düz hem de ters saçılma problemlerinde etkin sonuçlar vermektedir. Özellikle düz saçılma problemleri için yapılan kıyaslamalı uygulamalar yöntemin doğruluğunu net bir şekilde ortaya koymaktadır. İlgili yöntem saçılan alanın hesaplama verimliliği açısından mevcuttaki yinelemeli yöntemlere göre avantajlıdır. Yöntem uygulanırken ilgili ortamın hücre sayısının yeteri düzeyde belirlenmesi önemlidir. Mikrodalga beyin görüntüleme alanında önerilen ters saçılma problemi yaklaşımı bu tip problemlere basit ve etkili bir yöntem sunmaktadır. Bu problemde uygun arka plan uzayı seçimi son derece önemlidir. Ayrıca mevcutta kullanılan bir ters saçılma problemi ile yapılan kıyaslama sonucunda da önerilen yöntemin etkinliği incelenmiş ve basit kanonik yapılarda uygulanabilir olduğu görülmüştür. Bu yönteme ilişkin daha geniş incelemeler yapılabilir. Homojen olmayan ortamlara ilişkin Green fonksiyonunun moment tabanlı sayısal bir yöntem ile elde edilmesi sonucunda literatüre özgün bir çalışma kazandırılmış, bu alandaki düz ve ters saçılma problemlerine katkılar sağlanmıştır.
Imaging in layered media

(Graduate School, 2023-05-18) Yarar, M. Lütfi ; Yapar, Ali ; 504132303 ; Telecommunication Engineering

Detection and imaging of obstacles embedded in a stratified medium find a wide application area including underground imaging and through-wall imaging (TWI) as two-layered and three-layered medium applications, respectively. Despite the fact that both subsurface imaging and TWI have been a widespread area of research, in-wall imaging has remained a relatively untouched area. The literature on this topic is very limited indicating the difficulty level of the problem, that is, the main concern of this thesis. In addition to radar techniques and inversion algorithms, direct methods to probe a structure stand out as a field of study that many applications are clustered around. Direct methods include the multiple signal classification (MUSIC) method, the linear sampling method (LSM), the factorization method, the point source method, and several others. Also, it is proven that the reverse time migration (RTM) method is of use in imaging applications. In this thesis, the RTM method is applied to the single-frequency reconstruction of embedded obstacles in a wall to perform an introductory study for in-wall imaging. The aim is to determine the geometrical properties of an object embedded in a wall by the use of an information function provided via the RTM method. The method is based on the computation of that information function separately at each point on a reconstruction domain. It is defined as the correlation levels between the incident fields emitted from the sources and the back-propagation of the scattered field. Reporting the level of achievement of the RTM method in in-wall imaging based on a single test would be misleading. It should be tested under different circumstances. For this purpose, the problem is taken from a broader perspective in order to show and confirm the effectiveness of the method. Numerical experiments within a fundamental scenario are determined in a particular order to perform an essential Monte Carlo simulation. The method is tested for different material types, locations, and structural properties of the embedded object. Both dielectric and perfect electric conductor (PEC) scatterers are taken into consideration. In other words, both weak and strong scatterers are studied. Also, different acquisition lines, operating frequencies, and noise levels are used. A comparative study should be conducted to make an objective evaluation of the achievement level of the method. In line with this, the performance level in in-wall imaging is shown in comparison with free space imaging to make a proper evaluation of the feasibility level of the method. A mathematical model is proposed to make an overall quantitative evaluation. Thus, it will be possible to make a general conclusion. Inverse crime is a challenge to be avoided which may occur in inverse scattering applications. It can be briefly described by the philosophical norm as "two wrongs do not make a right" that implies trivial solutions and meaningless achievements. It could be a sneaky trap while acquiring the data synthetically. In order to avoid inverse crime, the problem must be modeled properly. It is verily known that one usual suspect in inverse crime is the computation of mathematical expressions. Those are mostly the integral representations of field quantities and the Green's functions. Precision and accuracy must always be guaranteed at an acceptable level since the computation step is the weakest link that may lead to occur an inverse crime.
Index modulation based designs, error performance and physical layer security analyses for unmanned aerial vehicle networks

(Graduate School, 2024-07-22) Büyükşar, Ayşe Betül ; Altunbaş, İbrahim ; 504172302 ; Telecommunication Engineering

Current 5G networks will not be able to meet emerging communications demands. As a result, research has begun on 6G wireless communication networks, which are expected to be deployed after 2030. 6G wireless communication networks will further improve mobile broadband, extend coverage and enable networks to include more and more smart devices. Reconfigurable front-ends for dynamic spectrum access, the Internet of Space Things enabled by CubeSats and Unmanned Aerial Vehicles (UAVs), cell-free massive multiple-input multiple-output (MIMO) communication networks, and intelligent communication environments that enable a wireless propagation environment with active signal transmission and reception are key technology advances to meet the requirements of 6G networks. Therefore, 6G will introduce new technical requirements and performance metrics driven by new application needs. 6G networks using terahertz and optical radio bands could reach $1-10$ terabytes per second. Moreover, high-frequencies can provide data rates that can reach gigabytes per second for user experience. Spectrum efficiency can be increased by a factor of $3-5$, while energy efficiency can be increased by a factor of about $10$ through the use of artificial intelligence for better network management compared to 5G. Other key performance indicators, such as cost-effectiveness, security capacity, coverage, intelligence levels, etc., should also be established to provide a more complete assessment of 6G networks. To provide global coverage, 6G wireless communication networks will expand from terrestrial communication networks in 1G-5G to integrated space-air-ground-sea networks, including satellites, UAVs, terrestrial networks, and marine communications. Over the past few years, a wide range of applications for UAVs has been established due to the advantages of their flexible design, rapid deployment, and low cost. A UAV can be used as aerial base stations (BS), user equipment (UE), or relay terminal in the 6G network because of their flexible design. UAVs can also be used in satellite networks which are another potential communication platform for 6G. In spite of the significant progress made in UAV technology, there are still several challenges. To enable UAV-based communication systems, extensive research is needed to accurately model the channel as UAV channels are unique due to their 3D deployment, high mobility, spatial and temporal instability, and aircraft shadowing. In addition to channel modeling challenges, UAV-based communications face several challenges, including security and regulatory issues, limited battery life, and seamless integration with existing networks. Index modulation (IM) can be considered as a potential technique to increase the spectral efficiency of UAV-based communications. IM uses information about the main building blocks of the wireless communication network to increase spectral efficiency and due to its advantages it has attracted considerable interest from the academia over the past decade. One of the common IM techniques, spatial modulation (SM), maps the information bits to the antenna indices. Similar to the concept of SM, distributed spatial modulation (DSM) allows the transmission of information bits using relay indices in a cooperative system. The DSM technique increases the aggregate throughput of the system and improves source reliability through distributed diversity. Another common IM technique, media-based modulation (MBM), embeds information in the selection of a particular transmission channel from a variety of channel states created by integrating parasitic elements such as radio frequency (RF) mirrors and PIN diodes in a reconfigurable antenna (RA). Similar to the external parasitic elements in MBMs, intelligent reflective elements in reconfigurable intelligent surfaces (RIS) enrich the propagation environment and perform proper phase shifts to modify the channel. This improves overall signal-to-noise ratio (SNR) quality by utilizing low-cost PIN diodes or varactors. Although MBM and RIS are based on similar structures, the MBM technique is designed to transmit additional information bits, while RIS increases the overall system reliability. 6G communication networks are designed for full connectivity with high operational flexibility and autonomy. Despite these advantages, the heterogeneity of the 6G network with UAVs and satellites makes it more vulnerable to security threats. For this reason, physical layer security (PLS) can act as an additional layer of security to enhance the trustworthiness of the radio access network. Traditional PLS solutions, like using active relays or friendly jammers (FJs) which use artificial noise (AN) to provide security, can result in increased hardware costs and power consumption. In this thesis, first the UAV channels are investigated with measurements. Then, in order to meet the high reliability requirements of future generation networks, integrated UAV systems are considered and novelties with solid theoretical foundations are proposed using DSM, and MBM. After reliability analysis for UAV systems, security problems are considered and novel system designs with non-orthogonal multiple access (NOMA), SSI-based UAV relay selection, joint transmit-receive pattern selection (JTRPS), and RIS are analytically investigated. In the first part of this thesis, we have measured the air-to-ground (AtG) channel by exploiting its statistics in realistic outdoor channel conditions for the UAV. In this study, the path loss exponent is found with curve fitting and fading statistics are estimated using the maximum likelihood (ML) decision rule. Practical measurements showed that the AtG channel is likely to be modeled with Nakagami and Rician distributions. In the second part of this thesis, DSM technique, one of the IM techniques, is considered for both ground-to-ground (GtG) communication with UAV relays and UAV BS included AtG communication from error performance perspective due to the increased throughput advantage of DSM. By considering inherited characteristics of UAVs such as limited power, we proposed a cyclic redundancy check (CRC) aided UAV-relays. In this way erroneous UAV activation, error propagation and futile power consumption are prevented. Furthermore, DSM is generalized by using relay indices and modulated symbols for UAV BS to transmit information. As a continuation study of IM techniques for UAVs, MBM technique is realized by using RAs with mirror activation patterns (MAPs), which depend on the different on-off situations of RF mirrors. By this way the higher capacity gains can be achieved since the channel coefficients received from multiple paths are independent and identically distributed (i.i.d.). Therefore, a novel RA-embedded UAV relay-aided dual-hop communication system is proposed, combining SSI-based MAP selection at the first hop with the MBM technique at the second hop. As only one RF chain is required in this system, RA-embedded UAVs are cost-effective. In addition, SSI-based MAP selection improves spectral efficiency by eliminating a high data rate feedback channel carrying fast channel state information (CSI). For the purpose of simplifying the theoretical analysis and taking into account the standardization parameters, the AtG channel is modeled with a double Nakagami distribution. Theoretical bit error probability (BEP) analysis and asymptotic expressions are obtained and validated with simulation results. Besides the spectrum efficiency and high reliability {\color{Green}concerns}, PLS is also a significant concept for 6G networks. Especially, the intrinsic broadcast nature of UAVs and satellites makes them more susceptible to security threats. In particular, UAV eavesdroppers or UAV jammers have a physical channel advantage because of the high line-of-sight (LOS) probability with ground users. Motivating from this point, security threats are investigated for UAV networks. In the first part of the PLS analysis, NOMA based UAV BS aided terrestrial networks are investigated with secrecy analysis. In the second part of the PLS analysis, passive and active eavesdropper (PE/AE) {\color{Green}UAVs are} considered in space-air-ground-integrated network (SAGIN) that includes full-duplex (FD) UAV relays. Furthermore, the received SNR is increased with SSI-based relay selection, which improves the outage probability (OP). One of the PLS improving methods, FJ, is deployed in SAGIN by selecting from the FD-UAV relays. The proposed system operates in one transmission slot, unlike its half-duplex (HD) counterparts. Transmission secrecy outage probability (TSOP) expressions are derived to comprehensively evaluate the reliability and security performance of the SAGIN. In the third part of the PLS analysis, RIS, {\color{Green}which} favorably adapts the propagation environment by using low-cost reflective elements (REs), is considered for aerial communication in the existence of UAV eavesdropper to enhance security performance. To improve the received SNR both JTRPS and ideal phase shifting at RIS are proposed. Moreover, capacity-based secrecy outage probability (SOP) and TSOP expressions are derived and theoretical results are validated by simulations. In summary, this thesis presents novel UAV-included communication systems for future-generation networks by considering realistic channel models and channel parameters in standardization studies. Through this process, we deployed DSM, relay and pattern selection, MBM, NOMA techniques to UAV-based systems. Moreover, we initially investigated BEP, symbol error probability (SEP) to evaluate the reliability of the UAV systems. To investigate the secrecy performance of UAV systems, SOP, and TSOP expressions are studied with detailed comprehensive analysis.
Microwave imaging of breast cancer with contrast agents

(Fen Bilimleri Enstitüsü, 2020) Yıldırım, Sema ; Çayören, Mehmet ; 648935 ; Elektronik ve Haberleşme Mühendisliği Ana Bilim Dalı

The prevalence of breast cancer is seen in both sexes worldwide, however, it is the second type of cancer, which is diagnosed especially in women and results with a fatal outcome among cancer types. Breast cancer like other types of cancer manifests itself by changing breast cells for various reasons, firstly spreading to the surrounding cells and then to the tissues in the body. The spread of other cells under the influence of changing breast cells causes malignant tumors to appear. Hence, it is great of importance to control or stop the spread of from breast cells to other cells in the body. For this purpose, early-stage diagnosis studies for breast cancer have been a working area in which researchers showed great interest. In other words, early diagnosis techniques play a key role in determining the course of the disease. In this point, mammography technologies containing ionizing x-ray radiation are most frequently used for the early-stage breast cancer detection. The usage of x-ray radiation can damage to the body tissues. These technologies, which contain x-rays that can ionize tissues, bring along various limitations during measurement due to the prevalence of the disease especially in elderly people. The disadvantages of mammography techniques exhibit the need for new and alternative imaging methods. In recent years, many researchers have worked on breast imaging systems to handle the particular disadvantages of mammography technologies. In this context, the non-ionizing microwave imaging (MWI) method, reducing the risk of patient health, is seen as a more reliable and alternative imaging technology for the early-stage breast cancer detection. The breast imaging with MWI methods is based on the reconstruction of the dielectric permittivity profile of cancerous and healthy breast tissues. After completed the breast reconstruction, the cancerous tissues are diagnosed due to illustrate a higher dielectric permittivity profile than other healthy tissues in the breast. The purpose of these methods is to diagnose and display any cases other than normal that occur in the body. The most important feature of MWI methods is to carry a low-level risk of harm to the patient because of using non-ionizing electromagnetic waves. In addition to this, it can be used in ambulances and many other emergency points for early diagnosis. Notwithstanding all these advantages, the clinical acceptance of MWI methods for breast cancer has not been realized yet. Hence, MWI methods need to improve with new approaches to receive clinical acceptance. The process of imaging or reconstructing the electromagnetic properties of tissues is based on the inverse scattering theory, and there are several quantitative and qualitative imaging methods developed in this area. Benefit from these methods, the positions, shapes, and electromagnetic properties of diseased tissues in the body are obtained in two or three dimensions. The qualitative imaging methods generally give information about the positions and shapes of diseased tissues. The scattered fields from tumors are higher than other normal tissues allows the qualitative imaging methods to be easily applied. While the quantitative imaging methods provide information about the geometric shapes and positions of tumors, as well as numerical information about the dielectric properties. The most widely used the quantitative imaging methods available in the literature are contrast source inversion (CSI) and Newton-based methods. Within the scope of this thesis, all studies have been realized mainly on the solution methods of the inverse scattering problems. In other words, the alternative methods based on enhanced contrast agents are recommended for scatterer objects with different relative dielectric permittivity and magnetic permeability constants, especially for the microwave imaging methods used in breast cancer. The main purpose of these studies is to eliminate the resolution limitation of microwave imaging methods by using dielectric and magnetic contrast agents and to enable the proposed method to be used more efficiently for the diagnose of early-stage breast cancer. All studies can be categorized under three main headings: i) the reconstruction of dielectric permittivity profile based on quasi-Newton method ii) the enhanced-dielectric contrast agents based on the quasi-Newton method for microwave imaging, ii) the enhanced-magnetic contrast agents based on factorization method for microwave imaging. are higher than other normal tissues allows the qualitative imaging methods to be easily applied. While the quantitative imaging methods provide information about the geometric shapes and positions of tumors, as well as numerical information about the dielectric properties. The most widely used the quantitative imaging methods available in the literature are contrast source inversion (CSI) and Newton-based methods. Within the scope of this thesis, all studies have been realized mainly on the solution methods of the inverse scattering problems. In other words, the alternative methods based on enhanced contrast agents are recommended for scatterer objects with different relative dielectric permittivity and magnetic permeability constants, especially for the microwave imaging methods used in breast cancer. The main purpose of these studies is to eliminate the resolution limitation of microwave imaging methods by using dielectric and magnetic contrast agents and to enable the proposed method to be used more efficiently for the diagnose of early-stage breast cancer. All studies can be categorized under three main headings: i) the reconstruction of dielectric permittivity profile based on quasi-Newton method ii) the enhanced-dielectric contrast agents based on the quasi-Newton method for microwave imaging, ii) the enhanced-magnetic contrast agents based on factorization method for microwave imaging. In the second part of the thesis, all studies on the use of dielectric contrast agents for breast cancer have been conducted. Unlike the first part here, the QN-CSI method by using the dielectric contrast agents is explored in more different and realistic cases. Firstly, a canonical breast model is designed using the HFSS electromagnetic 3-D simulation program. The designed breast model consists of structures had different dielectric permittivity and conductivity values, which are lined up from the outermost muscle, skin, glandular breast tissue, and tumor respectively. Firstly, the breast model is simulated to generate the forward scattering solution for two different cases, which are the presence and absence of dielectric contrast agents. After that, the scattered fields from the breast model are collected from different illumination angles and the field difference is calculated by using these two simulation results. The proposed QN-CSI method realizes the inverse scattering solution with this difference dataset and in this manner, the tumorous tissues placed in the breast model are imaged. Within the scope of this section, the image acquisition skill of the proposed method for different status parameters is examined. In this context, all simulations are operated at f = 2GHz, and two spherical tumors with radius of 1cm are located at (x1, y1,z1) = (3cm,4cm,−2cm) and (x2, y2,z2) = (3cm,4cm,2cm). The dielectric permittivity and conductivity constants of the placed tumors are selected as εr = 43 and σ = 1S/m. Later, the values of these dielectric constants are increased up to 37% under the assumption of using contrast agents at the second simulation. After completed these two simulations, the difference dataset is calculated and the tumors are imaged by the QN-CSI method. The fact notwithstanding that this image is not an anatomical breast model, it contains the expected tumorous tissues. At the end of this section, several simulations according to different status parameters are performed by changing the number of plane waves, the radiuses of tumors, and the conductivities of tumors In this chapter, all numerical results are given by comparison with the CSI method. In the third and last part of the thesis, the magnetic contrast agents are carried out instead of the dielectric contrast agents. Similar to the second part, but here, the changing of magnetic permeability constant (µr) depended on the frequency and the effect of an externally applied magnetic field are taken into account. Namely, magnetic nanoparticles(MNPs) are employed for the magnetic contrast enhancement. The different types of MNPs such as superparamagnetic iron oxide nanoparticles (SPIONs), which are most often preferred, are used to detect abnormality in several medical imaging methods. Since the biocompatible SPIONs are functionalized by the effect of the polarized magnetic field externally applied from the outside. While normal tissue cells do not react to the external magnetic fields, the magnetic nanoparticles nonlinearly behave depending on the value of the applied magnetic field. As a result of this, the changing of magnetic contrast is displayed. In this thesis, UWCEM numerical breast phantom repository, which includes several realistic experimental breast models, is used as a database to investigate the enhanced magnetic contrast agents. The phantom repository consists of numerical breast phantoms produced from anatomically realistic magnetic resonance imaging (MRI) for breast cancer detection and treatment applications. Here, the third phantom in ACR class 3, which contains heterogeneously dense fibroglandular breast phantom is selected and embedded into a 3D electromagnetic simulation program adding two tumors with a diameter of 0.5cm located into the model. The relative dielectric permittivity εr = 4 is chosen for the background medium. In the following step, the simulations are performed for two different cases over the 1.91GHz − 2.04GHz frequency band with N = 18 dipole antennas. After both simulations are completed for the given frequency range, the difference between the multi-static response matrices included reflection coefficients are calculated and the inverse problem solution is realized. In this part of the thesis, the factorization method is chosen to reconstruct the breast model. Eventually, the locations and shapes of the tumors are easily determined by the factorization method based on SPIONs contrast agents.
Moleküler haberleşme sistemlerinde alıcı kestirim yöntemleri

(Lisansüstü Eğitim Enstitüsü, 2023-03-22) Aslan, Ergin ; Çelebi, M. Ertuğrul ; 504152307 ; Telekomünikasyon Mühendisligi

Nanoteknoloji atomik, moleküler veya makromoleküler seviyelerdeki teknolojilerin incelenmesi, geliştirilmesi ve uygulanması olarak tanımlanır. Nanoteknolojinin temel fonksiyonel birimi nanomakinelerdir. Nanomakineler birkaç nanometreden birkaç mikrometreye kadar değişen boyutlarda olabilen otonom makinelerdir. Nanomakineler algılama, hesaplama, haberleşme ve çalıştırma gibi basit görevleri yapabilen nano ölçekte bileşenlerden oluşmaktadır. Tek bir nanomakine, boyutu ve basit yapısından dolayı sadece sınırlı görevleri yerine getirebilmektedir. Öte yandan, bir kaç nanomakine daha karmaşık görevleri yerine getirebilmek için bir ağ üzerinden iş birliği yapabilir. Bu ağlar nano ağlar olarak adlandırılmaktadır. Nano ağ, nanomakinelerin birbirleri ile haberleşerek iş birliği yaptığı ve bu sayede sağlık ölçümü, akıllı ilaç gönderimi, nano ölçekteki çevrelerde biyolojik ve kimyasal saldırıların tespiti gibi daha karmaşık görevlerin yerine getirilebildiği bir sistemdir. Enerji, sağlık, çevre, gıda ve tekstil gibi birçok kullanım alanına sahip olan nanomakineler, karmaşık görevleri yerine getirebilmek için birbirleri ile haberleşmeye ihtiyaç duymaktadırlar. Nanomakineler için literatürde mekanik, akustik, elektromanyetik ve moleküler haberleşme sistemleri gibi birçok haberleşme sistemi önerilmiştir. Bu sistemlerden çoğu nano ölçekli rejim ile ilgili güç, boyut ve karmaşıklık kısıtlamaları sebebiyle uygulanamaz olarak tanımlanmıştır. Öte yandan moleküler haberleşme nanomakineler için en uygun çözüm olarak öngörülmüştür. Moleküler haberleşme, nanomakinelerin akışkan bir ortamda kimyasal işaretler veya moleküller kullanarak haberleşebildiği bir sistemdir. Moleküler haberleşmede gönderici nanomakine, bilgiyi moleküllere kodlayarak akışkan ortama gönderir. Ortamda yayılan bilgi molekülleri alıcı nanomakine ile etkileşime girer. Alıcı nanomakine bilgi moleküllerini sezerek bilgiyi çözer ve uygulamaya yönelik görevleri yerine getirir. Nanomakineler için iyon işaretleşmesi, aktif taşıma, bakteri tabanlı haberleşme ve difüzyon tabanlı haberleşme gibi çeşitli moleküler haberleşme sistemleri araştırılmıştır. Bu haberleşme sistemlerinden difüzyon tabanlı moleküler haberleşme enerji-verimli bir haberleşme sistemidir. Difüzyon tabanlı moleküler haberleşme, moleküllerin akışkan ortamda difüzyon ile pasif bir şekilde yayıldığı moleküler haberleşme sistemlerinden biridir. Difüzyon tabanlı moleküler haberleşme sistemlerinde, moleküllerin rastgele difüzyon yayılımından dolayı, klasik radyo frekansı (RF) tabanlı haberleşmeye göre semboller arası girişim daha fazladır. Bu da haberleşme sisteminin güvenirliğini azaltmaktadır. Bunun yanı sıra, nanomakineler nano ölçekli otonom makineler olduğundan, enerji, boyut, hesaplama kabiliyeti açısından belirli kısıtlamalara sahiptirler. Nanomakinelerin sahip olduğu bu kısıtlamalar ve difüzyon tabanlı moleküler haberleşme sistemlerindeki yüksek semboller arası girişimden dolayı, difüzyon tabanlı moleküler haberleşme sistemlerinde, güvenilir ve uygulanabilir bir haberleşme için düşük hesaplama karmaşıklığına ve yüksek bit hata oranı performansına sahip alıcı kestirim yöntemleri gerekmektedir. Bu tezde, difüzyon tabanlı moleküler haberleşme sistemlerinde model tabanlı ve yapay zeka tabanlı alıcı kestirim yöntemleri araştırılmaktadır. Bu kapsamda, difüzyon tabanlı moleküler haberleşme sistemi için literatürde önerilen alıcı kestirim yöntemleri verilmiş, model ve yapay zeka tabanlı alıcı kestirim yöntemleri önerilmiştir. Literatürde önerilen en büyük olabilirlik dizi kestirim yöntemi, göz ardı edilen ISI terimlerinin oluşturduğu DC yanlılık hesaba katılarak değiştirilmiş ve bit hata performansı açısından daha iyi olan Viterbi dal metrikleri elde edilmiştir. Değiştirilmiş Viterbi algoritmasının, literatürde önerilen klasik Viterbi algoritması ile aynı hesaplama karmaşıklığına sahip olduğu gösterilmiştir. Öte yandan, değiştirilmiş Viterbi algoritması, klasik Viterbi algoritmasına göre daha iyi bit hata oranı performansı göstermektedir. Değiştirilmiş Viterbi algoritması önerilen alıcı kestirim yöntemlerinin bit hata oranı performansları için temel ölçüt olarak kullanılmıştır. İşarete bağımlı gözlem gürültüsünün varyansı yerine bu varyansın istatistiksel ortalaması kullanılarak durağan kanallarda geçerli olan Wiener filtre difüzyon tabanlı moleküler haberleşme sistemi için bir alıcı kestirim yöntemi olarak önerilmiştir. Durağan ve doğrusal olmayan kanallarda kullanılabilen genişletilmiş Kalman filtre, difüzyon tabanlı moleküler haberleşme için ilk kez bir alıcı kestirim yöntemi olarak önerilmiştir. Literatürde önerilen en az ortalama kareler hatası (MMSE) alıcı kestirim yöntemi, Wiener ve Kalman filtrelerinin bit hata oranı (BER) performansları için temel ölçüt olarak kullanılmıştır. Önerilen alıcı kestirim yöntemlerinin BER performansları ayrıca literatürde önerilen uyarlamalı eşik ve sabit eşik kestirim yöntemleri ile karşılaştırılmıştır. Diğer yandan, hesaplama karmaşıklığı Viterbi algoritmasına göre daha düşük olan genişletilmiş Kalman filtrenin, alıcı ve verici arasındaki uzaklık azalırken yada vericiden gönderilen molekül sayısı yüksekken Viterbi algoritmasından daha iyi BER performansı gösterdiği gözlemlenmiştir. Dahası, genişletilmiş Kalman filtre, Viterbi algoritmasından daha az durum sayısına sahipken bile, Viterbi algoritmasından daha iyi BER performansı göstermiştir. Wiener filtre, uyarlamalı eşik değeri kestirim yönteminden daha iyi BER performansı gösterirken, belirli koşullar altında sabit eşik değeri kestirim yöntemi ile benzer BER performansına sahip olduğu görülmüştür. Wiener filtrenin daha düşük hesaplama karmaşıklığı ile MMSE kestirim yönteminden daha iyi bir BER performansına sahip olduğu gösterilmiştir. Dahası, belirli bir bit süresi için sadece iki uzunluklu sonlu dürtü yanıtlı (finit impulse response, FIR) Wiener filtre yeterli bir BER performansı göstermiştir. Öte yandan, genişletilmiş Kalman filtre, ortalama kare hatasını minimize eden diğer alıcı kestirim yöntemleri MMSE ve Wiener filtreden daha iyi BER performansı göstermiştir. Sonuç olarak, lineer hesaplama karmaşıklığına sahip Wiener filtre ve karesel hesaplama karmaşıklığa sahip Kalman filtre moleküler haberleşme için yüksek BER performansı gösteren alıcı kestirim yöntemleri olarak önerilmiştir. Model tabanlı alıcı kestirim yöntemlerinin bir çoğu alıcıda kanal durum bilgisine (channel state information, CSI) ihtiyaç duymaktadır. Moleküler haberleşme kanalında gözlem gürültüsü vericiden gönderilen işarete istatistiksel olarak bağımlıdır. Bundan dolayı moleküler haberleşme kanalının durumu zamanla değişmektedir ve kanal durum bilgisinin alıcıda kestirimi zordur. Ayrıca, kanal durum bilgisinin alıcıdaki kestiriminin hassasiyeti, model tabanlı alıcı kestirim yöntemlerinin performansını etkileyebilmektedir. Öte yandan, yapay zeka tabanlı alıcı kestirim yöntemleri, alıcıda kanal durum bilgisine (CSI) ihtiyaç duymamakta, sadece alıcıya gelen işareti kullanarak kestirim yapmaktadır. Makine öğrenmesi ve derin öğrenme modelleri alıcıda kanal durum bilgisine ihtiyaç duymadan difüzyon tabanlı moleküler haberleşme sistemi için yapay zeka tabanlı alıcı kestirim yöntemi olarak kullanılabilir. Bu tezde, karar ağacı, çok modelli rastgele örnekleme, karar ağacı ormanı ve uyarlamalı takviyeli sınıflandırma makine öğrenmesi algoritmaları difüzyon tabanlı moleküler haberleşme sistemi için önerilmiş ve BER performansları literatürde önerilen sabit eşik kestirim yöntemi ve ileri beslemeli tam bağlantılı yapay sinir ağı alıcı kestirim yöntemi ile karşılaştırılmıştır. Tek bir karar ağacı kullanıldığı zaman, yapay sinir ağı ve sabit eşik değeri kestirim yöntemlerinin karar ağacı algoritmasından daha iyi BER performansına sahip olduğu görülmüştür. Öte yandan, çok modelli rastgele örnekleme, karar ağacı ormanı ve uyarlamalı takviyeli sınıflandırma gruplama yöntemlerinin yapay sinir ağı ve sabit eşik değeri kestirim yöntemlerinden daha iyi BER performansına sahip olduğu görülmüştür.
New combined non-orthogonal multiple access techniques for wireless networks

(Graduate School, 2023-03-23) Gavas Üstünbaş, Seda ; Aygölü, Hasan Ümit ; 504172309 ; Telecommunication Engineering

Thanks to orthogonal multiple access (OMA) schemes, connectivity is provided to multiple users, different services, or diverse applications by allocating non-overlapping hence orthogonal resource blocks (time, frequency, and code) in today's networks. The orthogonal resource allocation urges the exploitation of higher frequency bands toward visible light to provide wider bandwidths that accommodate the massive connectivity and the tremendous data traffic volume offered by the next-generation mobile networks. As 5G technology becomes available worldwide and 6G technology appears on the horizon, the only characteristic remaining unchanged is the need for the wider bandwidths. However, spectrum as an inherently scarce resource is already inefficiently used and the use of higher frequency bands causes coverage problems even if sensitive coverage planning is accomplished. Hence new techniques enhancing spectral efficiency and enabling hyper-connectivity are required for future networks. Non-orthogonal multiple access (NOMA) constitutes a promising solution for spectral efficiency and hyper-connectivity by allowing multiple users simultaneously to share the same resource block. NOMA benefits from multiplexing the signals from different sources by the nature of the wireless medium, where superposition coding is performed at the transmitter side leading to inter-user interference on purpose. To distinguish the different users at the receiver, successive interference cancellation (SIC) is applied. NOMA can be implemented in both downlink (DL) and uplink (UL). In downlink NOMA (DL-NOMA), a base station (BS) transmits the superposition coded signal to the users, contrary to the uplink NOMA (UL-NOMA), where the information flow is from the users to the BS. Hence, DL-NOMA differs from UL-NOMA in terms of the received superposition coded signal. The received signal is only affected by the respective channel fading coefficient in DL-NOMA. On the other hand, in the UL-NOMA where the signals of users are multiplexed over the air, the received superposition coded signal is not only the weighted sum of users' signals but also includes the respective channel fading coefficients of all users. Therefore adaptive SIC techniques are required to avoid error floor characteristics in the performance curves of UL-NOMA. In this thesis, NOMA has been studied in combination with other emerging technologies such as cooperative communication, full-duplex (FD) technology, cognitive radio (CR), energy harvesting (EH), and transmit diversity to further enhance spectral and energy efficiencies as well as to provide massive connectivity in a fair manner. Cooperative communication provides diversity by creating a virtual antenna array with the help of an intermediate relaying node in the lack of multiple antennas. Higher data rates and diversity gains are obtained, furthermore, coverage can be extended to unserved or underserved areas. CR is another promising solution to the inefficient use of spectrum, where unlicensed (secondary) users (SUs) can access the licensed (primary) users (PUs) band via dynamic spectrum access techniques. In the thesis, a cooperative NOMA (C-NOMA) scheme adopting a cognitive butterfly network design is considered, where far user's transmitter-receiver pair is assumed as PU and the near user's transmitter-receiver pair along with a relay is considered as SU. Butterfly network design involves both UL-NOMA and DL-NOMA transmission steps. Transmission from transmitter to the relay is according to the UL-NOMA principles while relay conveys the superposition coded signal to the receivers according to the DL-NOMA principles. Since the transmitter of each user is close to the receiver of other user while its receiver is near the other user's transmitter, the information from the side short links is also exploited to improve SIC performance. Although UL-NOMA has rarely found a place in the NOMA literature, it is a part of the end-to-end connection between transmitter-receiver pairs in this study and to the best of our knowledge, this is the first study combining UL-NOMA and DL-NOMA in one system configuration to investigate bit error probability (BEP) performance. Since the power allocation is of most importance and has a direct impact on performance, power allocation for both UL-NOMA and DL-NOMA steps of the end-to-end connection is investigated and the end-to-end BEP analyses are provided. A similar C-NOMA scheme adopting cognitive butterfly network design is examined by assuming that the relay has the ability to harvest energy from the radio frequency (RF) signals in the environment as a difference. It is assumed that energy harvesting can be applied by relay according to two energy harvesting architectures namely power splitting and ideal receiver. BEP analyses for both users in each energy harvesting architecture are performed. This study fills another gap in the NOMA literature, since a combination of C-NOMA, EH, and CR has not been investigated in terms of BEP performance yet. For both architectures, the comparisons between reference OMA schemes are also provided for the same energy and spectral efficiency to show their superiority. Although C-NOMA has advantages, cooperation degrades the spectral efficiency, which is the most significant advantage of NOMA, due to the need for an extra time slot. The potential of NOMA can be fulfilled thanks to FD technology providing the ability of simultaneous transmission and reception to relaying node. In the thesis, an UL C-NOMA network adopting FD technology is considered in the presence of a direct link between BS and the far user. It is assumed that there are multiple uniformly distributed near users within a disc seeking the opportunity to access the frequency band and the distance between BS and the far user determines the diameter of the disc. Since NOMA is not effective for more than 2 users, a user pairing strategy is performed to select a near user, which has the ability to work in FD mode. To eliminate the error floor in the performance curves, adaptive decoding order, namely hybrid SIC, is applied and compared to two SIC schemes, namely, channel state information (CSI)-based and quality-of-service (QoS)-based SIC, to show its superiority. CSI-based SIC has been widely studied in the NOMA literature, where decoding order is defined according to the CSIs of the users. In QoS-based SIC, the near user can access the band if the QoS requirement of the far user is ensured, otherwise, OMA is adopted. It is shown by the outage performance curves that hybrid SIC as a combination of CSI-based and QoS-based SIC eliminates the error floor characteristic in UL-NOMA networks and is robust to the self-interference caused by FD mode contrary to the other two SIC schemes. The computational complexity is also investigated and compared to that of the half-duplex NOMA scheme. Instead of the virtual antenna array, multiple antennas can be located at the transmitter to improve capacity and reliability. In this thesis, a transmit diversity scheme, coordinate interleaved orthogonal design (CIOD), is applied to DL-NOMA. CIOD performs an interleaving procedure where coordinates of the modulated signals experience independent channel fading coefficients resulting in modulation diversity. Two cell-edge users are served by two BSs from adjacent cells, hence multiple antenna technique is implemented in a distributed manner. BSs simultaneously transmit desired signals to both users according to the CIOD transmission principle, a $2\times2$ CIOD-NOMA matrix is emerged where the desired signals of users are located at reverse diagonals. BEP analyses are provided for both users. It is shown that full diversity is obtained at full rate for both users and significant coding gains are achieved. Power allocation is also investigated in terms of the tradeoff between fairness and BEP performance. Satisfactory fairness performance is achieved in return for an acceptable BEP degradation. Furthermore, another transmit diversity scheme is studied in the scope of this thesis. A two-stage transmit antenna selection (TAS) scheme where one among multiple antennas is chosen at BS, is investigated for DL-NOMA. The selection is based on the adopted performance criteria, which is chosen as the sum rate maximization in this study. In the first stage, an antenna subset maximizing sum rate is selected. In the second stage, Jain's fairness indices are obtained according to the individual achievable rates of the users and the antenna maximizing the fairness index is selected. With this scheme, the sum rate is maximized while fairness is ensured. Although the sum rate maximization by considering user fairness is significant, a working system requires an acceptable error performance. In NOMA, the users' signals can be distinguished at the receiver side thanks to the differences in their received signal powers. As the power difference between the signals increases, it becomes easier to distinguish them, which improves the SIC performance. Therefore, in this study a power allocation scheme is also considered to fix the difference between power allocation parameters which otherwise tend to be equal with the increasing signal-to-noise ratio (SNR). The power allocation scheme involves the maximization of the sum rate under the constraint of a target data rate for the far user. NOMA is recognized as an enabler for the next generation of mobile networks thanks to allowing massive connectivity and enhancing spectral efficiency and fairness between users. In the scope of this thesis, NOMA has been combined with above-mentioned emerging technologies, and the proposed protocols have been investigated in terms of BEPs and/or outage probabilities to fill the gaps in the NOMA literature.
New deep learning based approaches for land cover classificationin satellite images

(Graduate School, 2025-03-10) Awad, Bahaa ; Erer, Işın ; 504182301 ; Telecommunications Engineering

This dissertation provides an in-depth examination of strategies for improving agricultural monitoring through remote sensing. It focuses on three main contributions: the development of FAUNet for delineating parcel boundaries, a novel technique that combines the Segment Anything Model (SAM) with principal component analysis (PCA) to refine segmentation, and the use of thermal time modeling to enhance crop classification across different climates. Parcel boundary delineation serves as a crucial step in agricultural monitoring, ensuring precise segmentation of land parcels for applications such as yield forecasting and land-use planning. To address limitations in existing models, this study presents FAUNet—an innovative dual-headed U-Net specifically tailored for boundary detection in agricultural imagery. FAUNet employs a high-frequency attention module (based on high-pass filters) and a dual-path design that predicts both edge and extent masks. When compared to leading models like U-Net, ResUNet-a, SEANet, and BsiNet, FAUNet delivers the highest object-level F1 score (0.7734) and exhibits notably low over-segmentation (0.0341) and under-segmentation (0.1390) rates. Building on these insights, the dissertation introduces a new method to enhance segmentation by coupling SAM—a foundational segmentation model originally trained on diverse natural images—with PCA. Since SAM's training data do not include specialized remote sensing imagery, its performance in this domain can be limited. To address this issue, SAM's high-dimensional embeddings are first extracted, then reduced with PCA, followed by guided filtering to refine the inputs. This iterative feedback loop helps SAM generate more precise boundary delineations, ultimately improving segmentation results in challenging remote sensing scenarios. The thesis then turns its attention to the challenge of generalizing crop classification models in regions with varying climates. Standard machine learning models (e.g., Random Forest, Gradient Boosting, XGBoost, SVM, and MLP) often encounter difficulties when facing the temporal shifts driven by different local growing conditions. To mitigate this, thermal time modeling based on Growing Degree Days (GDD) is introduced. By aligning crop phenological stages and smoothing out timing discrepancies, GDD helps these models adapt to spatial variability more effectively. Experiments on datasets from Turkish regions with diverse climates show that incorporating GDD boosts classification performance, allowing models to generalize more reliably across geographically distinct environments. Overall, this dissertation tackles significant obstacles in agricultural remote sensing, ranging from accurate parcel boundary detection to robust crop classification under complex environmental conditions. The proposed FAUNet framework streamlines boundary delineation, the SAM modification allows it to perform better in boundary delineation, and thermal time modeling underscores how classification can be adapted for real world agricultural scenarios.
New edge computing offloading methods for next generation wireless networks

(Graduate School, 2023-07-17) Atan, Beste ; Durak Ata, Lütfiye ; 504142307 ; Telecommunications Engineering

The increasing number of mobile applications and massive deployment of connected IoT devices cause computation load due to intensive task requests coming from devices. Computing these tasks by fulfilling the latency requirements of the features or applications are one of the big argument in the next generation of networks. Although mobile or IoT devices provide us with various kinds of functionalities such as entertainment, social networking, or smart home or transportation, but they are not sufficient to process huge data thyself in an effective way due to their storage, computation, and energy limitations. Besides, traditional cloud computing systems that are currently used in the networks are deployed with high distant from the user environments. Therefore, they are not appropriate to provide low-latency required services. One of the promising methods to address the aforementioned problems is offloading the task computing process to edge servers that are in close proximity to the users. This solution is defined by The European Telecommunications Standards Institute (ETSI) and called multi-access edge computing (MEC). According to the task execution requirements, MEC offers more storage and compute power while meeting stringent performance criteria like low latency, low energy consumption, or increased bandwidth. Even if edge computing is a key solution, the task execution decision process between devices and edge servers is a complex decision problem that conventional optimization algorithms struggle to solve to meet the execution requirements. In recent years, the development of learning methods in artificial intelligence (AI) technology helps to create new methods for resolving these kinds of challenging problems. Additionally, both academies and industries have a significant interest to integrate machine learning (ML) and deep learning (DL) methods into next-generation wireless networks. By integrating AI algorithms into edge network environments, it is possible to accelerate the task execution decision-making process and answer the latency-sensitive task execution demands of mobile and IoT devices. In this thesis, AI-based learning methods are mainly considered for task offloading strategy and we propose an intelligent task execution decision framework to accelerate the edge computation offloading process. In this framework, we take into account the capacity of edge servers, channel conditions, delay and energy consumption of devices, and mobility of users. The system model utilized in this study is built to be feasible for serving a variety of smart connected devices with latency-sensitive applications such as online gaming by consoles, virtual reality (VR) or augmented reality (AR)-based applications, live video streams from unmanned aerial vehicles (UAVs), connected car or smartphone applications. In the first section, task offloading decision methods are investigated for mobile networks by utilizing machine learning (ML) algorithms. In the second section, the study is enhanced to serve multi-device environments for mobile and IoT networks and the AI-empowered task classification framework is designed to respond delay sensitive task execution requests. Comprehensive performance results demonstrate that the proposed AI-empowered framework is substantially fast and precise in the decision-making of the edge computation offloading process while maintaining the quality of user experience compared to conventional optimization methods. We believe that the proposed AI-enabled task classification framework could provide prominent solutions for new applications by running at the network edge.
Novel complex dielectric permittivity measurement methods with open ended coaxial probes

(Graduate School, 2022-12-02) Dilman, ismail ; Çayören, Mehmet ; 504162313 ; Telecommunications Engineering

Nowadays, microwave dielectric spectroscopy is a popular research topic for scientists with use in a broad area. Microwave dielectric spectroscopy is realized with various methods. The most commonly applied methods are coaxial probe methods, transmission line methods, free space methods, resonant methods, and parallel plate capacitor methods. The open-ended coaxial probe method differs from microwave dielectric spectroscopy by being broadband, non-destructive technique. In addition, it is suitable for measuring lossy materials. The open-ended coaxial probe techniques are based on retrieving the complex dielectric permittivity (CDP) from the aperture admittance of the probe. This process is carried out by using the reflection coefficients from the vector network analyzer. These are realized in two steps. In the first step, real reflection coefficients are determined from the measured reflection coefficients from the calibration procedure. Next step, by using the relation between the aperture admittance and CDP, electrical properties are obtained. The main weakness of the technique is a high error rate that prevents accurate and stable results. This thesis first gives a brief overview of the realization of microwave dielectric measurement with an open-ended coaxial probe. It will then describe one of the previous methods, the rational functional model, for an open-ended probe technique. Validation of the method is tested in both simulation and measurement setups. Moreover, the effectiveness of methods is shown in retrieving the biological sample. In addition, the mentioned technique for a commercial probe improved in the third section. In the following section, a new method to reduce the error rate of dielectric measurements of the open-ended coaxial probe has been developed. This method takes advantage of the observation that electrical properties of materials variations are continuous functions of frequency. In particular, we derive a mathematical model that enforces spectral continuity by directly incorporating the Debye relaxation model. In addition, the robustness of the proposed methods is tested with a low-sensitive pocket network analyzer. Finally, a novel approximation in which measurement uncertainty and experimental noise are addressed in determining the CDP processes is presented. However, these effects are not considered in previous open-ended coaxial probe measurement studies. Take advantage of this extra information to enhance the improving measurement accuracy and results in similar problems. Benefit from statistical information; we define a new cost function based on maximum-likelihood estimation. The obtained results have been compared with the values given in the literature. The results of that studies demonstrated that mentioned methods are achievable in reducing errors. In addition to the open-ended coaxial probe, the proposed approach can accurately obtain the Debye parameters of the MUT. Furthermore, extending the method for different relaxation models is straightforward by introducing additional partial derivatives of the new parameters.
Physical layer security performance of satellite networks

(Graduate School, 2022-07-06) Yahia, Ben Olfa ; Kurt Karabulut, Zeynep ; Erdoğan, Eylem ; 504162314 ; Telecommunications Engineering

A vision of a three-layer Vertical Heterogeneous Network (VHetNet) is being discussed in the state-of-the-art Sixth Generation (6G) network design. This concept is in line with the 3rd Generation Partnership Project (3GPP)'s non-terrestrial network (NTN) activities. A satellite (space) network, an aerial network, and a terrestrial network represent the three levels. The space layer includes geostationary Earth orbit (GEO) satellites and non-GEO satellites including low Earth orbit (LEO) and medium Earth orbit (MEO) satellites. This layer will provide orbit or space Internet services in applications including space travel as well as wireless coverage for unserved and underserved areas not served by terrestrial networks by densely deploying LEO, MEO, and GEO constellations. By intensively utilizing flying base stations (BS), including unmanned aerial vehicles (UAV), and floating BSs, such as high altitude platform systems (HAPS), the aerial layer would enable a more flexible and better quality of service for critical events or in inaccessible areas. For most human activities, the terrestrial layer will continue to be the primary method for delivering wireless coverage. Satellite communication (SatCom) systems are typically radio frequency (RF)-based, with multiple frequency bands employed for different applications. However, RF channels suffer from spectrum congestion, license issues, interference with other frequency bands, and security threats. To address these issues, free-space optical (FSO) communication has lately been recommended for use in SatCom links because of its capacity to provide exceptionally large bandwidth, unlicensed spectrum, better security, low interference, ease of deployment, and other features over its RF counterpart. Nevertheless, similar to RF channels, FSO communication presents several drawbacks related to atmospheric effects, including atmospheric turbulence, scattering, and attenuation. Furthermore, FSO communication suffers from beam wander, beam divergence, and pointing issues. Different techniques have been proposed in the current literature to reduce these effects and enhance the overall performance including the incorporation of the RF link with the FSO to benefit from their complementary characteristics. This combination includes two possible architectures: mixed RF-FSO and hybrid RF/FSO communications. In mixed RF-FSO communication, a dual-hop network is considered, in which an RF channel is employed at one hop and an FSO channel is used at the other. For hybrid RF/FSO communication, RF and FSO channels are used in parallel. These combinations may reap all the advantages of both RF and FSO communications while minimizing weather-related issues. On the one hand, hybrid RF/FSO communication has received much attention in the recent literature. On the other hand, for satellite networks, there is a substantial gap in hybrid RF/FSO communication. In addition, there are a few works about mixed RF-FSO networks in NTNs while sending the same information to a group of users on a particular multicast group address, known as multicast services. Due to the broadcasting nature of the wireless channel, security is the most critical issue and challenging concern in NTNs. Unlike conventional methods, which often handle security at the application layer, physical layer security (PLS) guarantees information-theoretic security by extracting the variations in the physical properties of channels such that a degraded signal at an eavesdropper is always assured and therefore the original message can be hardly obtained regardless of how the signal is processed at the illegitimate receiver. PLS has been investigated as a good alternative to provide a solid form of security. Many studies have been conducted up to date to determine the fundamental performance limits of PLS under various wiretap channel models. It's worth noting that none of the available studies have investigated PLs in NTN systems. This Ph.D. research has been motivated by these key challenges involving future networks. In this thesis, our work sheds light on the PLS performance in NTNs. Therefore, understanding the outage and error performance of the physical layer for future networks from the communication point of view is of great importance to studying the security aspect. In the first part of the thesis, we study the hybrid RF/FSO transmission and mixed RF-FSO approaches for SatCom motivated by the complementary characteristics of RF and FSO communication. In the first proposed model, we assume a single-hop SatCom system where the satellite selects RF or FSO links based on weather conditions collected from sensors and employed for context awareness. We obtain the outage probability (OP) expressions by considering various weather situations to assess the performance of the proposed network. In addition, asymptotic analysis is carried out to determine the diversity order. We also consider the effects of non-zero boresight pointing errors and show how aperture averaging can significantly mitigate the effects of misalignment and atmospheric turbulence. The results reveal that the suggested technique outperforms dual-mode traditional hybrid RF/FSO communication in terms of OP while providing some power gain. Then, we present a novel downlink dual-hop SatCom model using an intermediate HAPS node. FSO communication is adopted between the LEO satellite and the HAPS node, whereas a hybrid FSO/RF transmission mechanism is considered between the HAPS node and the ground station (GS). The satellite chooses the HAPS node with the best signal-to-noise ratio in the initial phase of transmission. The signal is decoded and forwarded to the GS in the second phase by the designated HAPS. To examine the proposed system's performance, OP expressions for exponentiated Weibull and shadowed-Rician fading models are obtained, by considering atmospheric turbulence, scattering, stratospheric attenuation, path loss, and pointing errors. Aside from that, asymptotic analysis and diversity gain are obtained. The effect of the aperture averaging technique, wind speed, and temperature are also explored. Finally, the results show that using a HAPS node increases system performance and that the suggested model outperforms all other models currently in use. Thereafter, we investigate the performance of a multiple-hop mixed RF-FSO communication-based decode-and-forward protocol for multicast networks. So far, delivering real-time applications to a large number of users at the same time has been seen as a promising technique to deal with high data traffic demands. Thus, we present two realistic use-cases. In the first model, we propose a mixed RF/FSO/RF communication strategy assisted by a HAPS node, in which a terrestrial node communicates with a cluster GSs via two HAPS systems. In the second model, we consider that due to substantial attenuation produced by wide propagation distances, we consider that line of sight (LOS) connectivity between the two HAPS systems is unavailable. As a result, we propose a mixed RF/FSO/FSO/RF communication system supported by an LEO satellite. Closed-form expressions of OP and bit error rate are obtained for the given scenarios. In addition, diversity gains are derived to show the asymptotic behavior of the proposed models. For both scenarios, ergodic capacity and energy efficiency (EE) are also presented. Finally, simulation results are presented in order to verify the theoretical derivations. The obtained results demonstrate that the satellite-assisted mixed RF/FSO/FSO/RF model outperforms the HAPS-assisted mixed RF/FSO/RF model in terms of OP, whereas the HAPS-assisted mixed RF/FSO/RF scenario achieves better EE. From the security perspective, we propose different wiretap models and analyze the PLS performance. At first, for a HAPS-aided SatCom system, we study the secrecy performance of RF eavesdropping. In the proposed architecture, FSO communication is used between HAPS and the LEO satellite, while RF communication is used between HAPS and the GS as LOS communication cannot be established. Closed-form of secrecy outage probability (SOP) and probability of positive secrecy capacity (PPSC) expressions are derived to interpret the overall secrecy performance of the proposed approach. We also consider the impact of the pointing error and shadowing severity parameters. In what follows, we introduce optical eavesdropping in NTNs for different practical scenarios. In this context, we consider that a HAPS eavesdropper node is seeking to collect sensitive data from an LEO satellite, and a UAV eavesdropper is attempting to intercept confidential data from a HAPS node. We obtain closed-form SOP and PPSC expressions and validate them with Monte Carlo (MC) simulations to evaluate the overall performance of both scenarios. Secondly, a satellite eavesdropping strategy is presented, in which an attacker spacecraft trying to intercept optical communications established between an LEO satellite and a HAPS node. We assume satellite-to-HAPS (downlink) and HAPS-to-satellite (uplink) optical communications, in which the eavesdropper spacecraft can capture either the transmitted or received signal. The average secrecy capacity and SOP expressions are obtained and validated with MC simulations to quantify the secrecy performance. We also investigate secrecy throughput performance. Finally, according to our findings, turbulence-induced fading has a considerable impact on the secrecy performance of FSO communication.

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