LEE- Telekomünikasyon Mühendisliği Lisansüstü Programı

Bu topluluk için Kalıcı Uri

http://hdl.handle.net/11527/19468

Gözat

Yazar "Akıncı, Mehmet Nuri" ile LEE- Telekomünikasyon Mühendisliği Lisansüstü Programı'a göz atma
  • Öge
    A doherty power amplifier for 5G applications
    (Graduate School, 2023) Konanç, Hasan ; Savcı, Hüseyin Şerif ; Akıncı, Mehmet Nuri ; 900834 ; Telecommunication Engineering Programme
    The ever-increasing need for high data rates and low latency steered modern communication systems toward massive MiMo architectures. In this architecture, each antenna element requires its amplifier unit. Smaller cell sizes and more user service have forced a significant increase in antenna elements, so the Power Amplifier units. Each amplifier is a substantial contributor to the power consumption budget. Therefore, efficiency is a primary concern in Power Amplifiers of cellular infrastructure systems. This study focuses on an architectural solution for Power Amplifier efficiency by demonstrating a Doherty PA (DPA) design in a widely used 5G sub-6GHz band of n78. This thesis focuses on the efficient RF output power generation of 5G base stations from an architectural perspective. A Doherty Power Amplifier is designed using for n78 5G band that is prioritized for the upcoming deployment. The design is optimized for an operation between the 3.6 - 3.8 GHz frequency band. The output power of 43 dBm (20 W) was obtained by using two of the 10W GaN HEMT transistors and a drain efficiency of 73% was obtained. The Doherty region starts at 38 dBm output power which allows an efficient operation with 6 dB power back off. A drain efficiency of up to 53% was obtained in the Doherty region and a gain of 10 dB is obtained over the entire band. The requirement of unconditional stability at all frequencies under small and large signal conditions demands a thorough analysis at different phases of design. For multi – stage stability analysis, the Ohtomo approach was also utilized in this study, for its convenience of being based on S – parameters and not requiring access to the transistor's internal components. Nyquist method is used in Ohtomo approach. Nyquist method was applied for frequencies between 10 MHz and 10 GHz. As a result, the proposed DPA is stable because there is no loop gain surrounding the 1+ j∗0 point. The prototype of the proposed DPA was fabricated and real-time small and large signal tests were performed. During the tests, it was found that the prototype DPA did not work only in the desired frequency range of 3.6 - 3.8 GHz during the design period, and after the tuning process, Doherty drain efficiency characteristics were obtained in the frequency range of 3.2 - 4 GHz (n77 5G band). Accordingly, The output power of 41.6 dBm (approximately 15 W) was obtained by using two of the 10W GaN HEMT transistors and a drain efficiency of 67% was obtained. The Doherty region starts at 32 - 38.2 dBm output power, allowing an efficient operation with 0.5 - 7.8 dB power back off. A drain efficiency of up to 67 % was obtained in the Doherty region, and a gain of 3.5 - 7.9 dB was obtained over the entire band.
  • Öge
    Qualitative microwave imaging in non-destructive testing and evaluation applications
    (Graduate School, 2023-04-05) Doğu, Semih ; Akıncı, Mehmet Nuri ; 504172312 ; Telecommunications Engineering
    Microwave imaging is an inspiring research topic in which the goal is to obtain constitutive properties of inaccessible targets using measurements of the scattered electric field or scattering parameters. The phrase microwave refers to the frequencies of the electromagnetic fields used in this technology, which can range from several hundred MHz to several hundred GHz. The wavelength of the fields allowed us to analyze the materials without causing any damage within this frequency bandwidth. Because of this characteristic, this research area has discovered various non-destructive testing and evaluation applications in applied sciences, such as biomedical imaging, moving target detection, food imaging, subsurface imaging, concealed weapon detection, and through-the-wall imaging. Instead of reconstructing the electrical parameters, one technique for dealing with microwave inverse scattering problems is to compute an indicator function that holds the information of the targets. These techniques are known as qualitative microwave imaging methods (Q-MWM), and they are typically thought to be linear and non-iterative techniques that are computationally less expensive than their quantitative counterparts. The most extensively researched Q-MWM representatives are truncated singular value decomposition (TSVD), linear sampling method (LSM), and factorization method (FM). The singular sources method (SSM) and the nearfield orthogonality sampling method (NOSM) are comparatively new, yet they have a promising future in microwave imaging. In the first part of the thesis, the problem of microwave imaging of an impedance cylinder is investigated using Newton's approach. To achieve this goal, the scattered field from a circular cylinder with homogenous impedance is determined for plane wave illumination. At this stage, the scattering configuration is considered to be in the form of a TMz scenario. In this scenario, the impedance cylinder is supposed to be infinite along the z-axis, and the electric fields are assumed to be parallel to the same axis. The incident plane wave is assumed to be decomposed into a summation of Bessel functions, whereas the scattered field is assumed to be expressed as a sum of Hankel functions, according to these assumptions. After that, the boundary conditions on the surface of the impedance cylinder are utilized in order to acquire the unknown coefficients in the scattered field. After then, during the inverse scattering phase, it is necessary to make estimates concerning the target's impedance as well as its radius. To achieve this aim, the scattered field of the impedance cylinder is collected at a number of frequencies on a single point surrounding the target. Following this, an initial value is given to both of the variables, and the evaluation of the scattered field that corresponds to these initial values occurs. To arrive at an estimate of the updated amount for each parameter, the difference in the scattered fields is first divided into a matrix. This matrix then contains the derivative of the scattered field with respect to the unknown variables. Then, both of the parameters are updated, and this procedure is repeated as many times as necessary until the difference between the measured and estimated fields falls below a certain threshold that has been established. As a result, we are able to derive an estimate of the impedance as well as the radius of the cylinder. According to the findings, the method that is now suggested is capable of reconstructing the unknown parameters using only a limited aperture and several frequency observations. In the second part of the thesis, we examined differential through-the-wall microwave imaging with several formulations of the TSVD method in a non-anechoic experiment. Past studies have used TSVD with a single transmitting/measuring antenna, whereas we show how to use it with a moving linear transmitting/measuring antenna array. Particularly, for repeated measurements, an averaging procedure is adopted. Three TSVD approaches are tested: TSVD on Contrast Source, TSVD on Contrast and multi frequency TSVD on Contrast. The dimension of the inverted matrix in TSVD on Contrast Source method is comparatively small. Following the solution of equations, a normalization scheme is suggested to eliminate the noise. TSVD on Contrast technique produces better reconstructions than TSVD on Contrast Source method because measured data for all excitations are inverted simultaneously. TSVD on Contrast, however, takes a long time than TSVD on Contrast Source because the inverted matrix becomes larger. Finally, in order to avoid further calibration simulations/measurements in multi frequency TSVD on Contrast, we use TSVD on Contrast solutions to obtain the calibration information. The contrasts are then computed for all frequencies and excitations at the same time. Thus, for multi frequency TSVD on Contrast, the inverted matrix is the largest, the accuracy is the best, and also the computational burden is the greatest. A metallic scatterer is placed behind a wall to evaluate the proposed techniques. The results demonstrate a trade-off between accuracy and computational time when selecting an appropriate inversion approach. Furthermore, each method's norm type selection is evaluated. In the third part of the thesis, the imaging of moving objects with Q-MWM is addressed. The necessity of background measurement is a troublesome aspect of Q-MWM. To avoid this, the total electric field collected at distinct time instants (say, Etotn, Etotl are the total electric fields measured at nth and lth time instants) are implemented to Q-MWM. Thus, the outcome of the Q-MWM can be considered to be the sum of the indicators at these time instants (i.e. Etotn-Etotl produces the differential indicator Inl=In+Il, where In, Il are the indicators at nth and lth time instants). An equation system is developed for indicator values at different time instants using this information for all possible time couples. Without performing any background measurements, the indicator of Q-MWM for each time frame is derived by solving this equation system. The proposed algorithm's performance is validated using 3D and 2D (both transverse magnetic (TM) and transverse electric (TE)) experimental measurements, which are done in a non-anechoic environment, for the LSM, which is an example of Q-MWM. In the fourth part of the thesis, SSM, a qualitative imaging method, is investigated for two-dimensional transverse magnetic electromagnetic (2D-TM EM) inverse scattering cases. Qualitative microwave imaging approaches allow for the rapid and accurate reconstruction of target shapes from scattered electric field measurements. This section's contribution can be stated as follows: (i) The SSM was originally introduced for the far-field scenario; here, we extend the SSM in the near field - inhomogeneous background configuration. Each stage of the extension (which involves an integral equation) is discussed using the linearity and reciprocity principles to provide physical insights. (ii) A relationship is established between the electrical properties of the scatterers and the SSM indicator. (iii) The suggested method is examined for monitoring hyperthermia treatment problems with a realistic breast model to evaluate the performance of SSM in real-world scenarios. The obtained results demonstrate that the SSM is capable of handling realistic breast phantoms for monitoring hyperthermia problems. In the fifth and last part of the thesis, a range-migration technique is presented for near-field microwave imaging using monostatic and bistatic measurement configurations. Calibration measurements are critical for enhancing the precision of both qualitative and quantitative microwave imaging. A calibration measurement should ideally be taken at each desired range (or depth) position in three-dimensional (3-D) near-field imaging, which can be time-consuming. The calibration effort can be reduced to a single measurement at a reference range position if the range behavior of the resolvent kernel of scattering can be predicted analytically. Analytical formulations for range-translation (or range-migration) are already commonly utilized in far-zone radar and acoustic imaging; nevertheless, their accuracy suffers dramatically in near-field situations. The magnitude and phase of the system point-spread function (PSF) are accurately estimated at any desired range position based on a single measurement of the PSF. The proposed migration is conducted in real space, but it can also be implemented with Fourier-domain (or k-space) inversion methods. It is used in simulation-based and experimental examples to confirm its performance and demonstrate its limitations with quantitative microwave holography.
  • Öge
    Time difference of arrival based passive sensing and positioning system integrated into moving platforms
    (Graduate School, 2024-07-12) Çelebi, Burak Ahmet ; Akıncı, Mehmet Nuri ; 504211305 ; Telecommunication Engineering
    The ability to locate the source of information has been a fundamental need for humanity since its earliest days. This necessity even explains why living beings have evolved to have two ears: to determine the position of a sound source, which is a form of information. As sound propagates, it reaches our ears at different distances, creating an interaural time difference (ITD). The brain uses this time difference, along with the intensity of the sound, to estimate the location of the sound source. This thesis explores the principle of localization using ITD, which has existed in nature for millions of years, from the perspective of a communications engineer. Specifically, it examines the application of this principle to locate a source emitting radio frequencies. There are various methods for locating a signal source. These methods primarily rely on the signal's strength, arrival time, frequency, phase, or a combination of these factors to determine the position. The strength of the incoming signal depends directly on the terrain, the signal's frequency, and its output power. Since these variables are often unpredictable, using signal strength for positioning usually yields low accuracy results. Measuring the signal's phase requires multiple antennas and RF stages, which can only estimate the target's angle, not its precise location. However, by determining the arrival times of signals received by multiple receivers and analyzing the time differences, the position of the target can be estimated. To solve for the unknown x, y, and z coordinates in a 3D space using only time difference of arrival (TDOA) information, at least three equations are necessary. These equations provide the minimum amount of information required for position determination. However, obtaining three linearly independent TDOA equations necessitates a minimum of four receivers. Among these receivers, one is designated as the reference, and the time differences between this reference and the other three receivers are used to create linearly independent equations. These equations are then utilized to determine the target's position. However, because the equations are typically nonlinear, achieving a quick and highly accurate solution is not always straightforward. Additionally, factors such as hardware imperfections and noise can prevent a clear solution to the equation system. Various methods can be employed to address these challenges and improve the accuracy of the results. This study compares algebraic methods such as Least Squares (LS) and heuristic methods like Particle Swarm Optimization (PSO) for signal source localization. LS methods solve the system of equations directly to estimate the target position, while PSO methods optimize a target function to find the best location. Heuristic methods, including PSO, can yield effective results even with nonlinear equations or in noisy environments. In this research, we utilized a variant of the PSO algorithm known as the Firefly Algorithm. The Firefly Algorithm begins by distributing fireflies randomly across a cost function map. The fireflies move towards the solution with the lowest cost, switching to the new best fireflies as lower-cost solutions are found. This approach is advantageous for several reasons: it uses an infinite number of TDOA measurements rather than just three equations, minimizes the likelihood of getting stuck in local minima on the cost map, and achieves high-accuracy localization. Although the Firefly Algorithm requires more computational power compared to algebraic solutions, modern computers can handle this demand effectively. While signal source localization in a 3D environment using time difference of arrival (TDOA) information has often been tested with a 4-receiver system model, successful localization can also be achieved with different system models. Unlike traditional methods, where TDOA data is collected simultaneously from fixed receivers, we propose a system where two receivers are moved to collect TDOA data at different time instances, followed by localization using the collected data. Practical issues encountered with such a system model were investigated through simulation and measurement setups. One challenge was accurately estimating the time differences of arrival of signals received by the receivers. Due to the slow variation of signals in time, time estimation is affected by noise. Another potential problem arises when the sampling frequency of the system is narrower than the signal's bandwidth, causing the cross-correlation of received signals to not yield peak values at the delay samples, making time differences difficult to discern. To address this, we decided to operate the system with the highest possible sampling rate when the bandwidth of the target signal is unknown. Ensuring reliable signal sampling, both receivers are synchronized to the same frequency and time using a GPS-disciplined oscillator. Furthermore, 1 Pulse Per Second (PPS) from GPS is used for time synchronization. Apart from these technical considerations, the trajectory of the receiver stations plays a crucial role in system performance. As the distance between the target receivers increases, so does the distance they need to cover for accurate localization. Additionally, ensuring a high-reliability and high-capacity communication network between receiver stations and the base unit is crucial during system implementation. Without this network, communication disruptions between the receivers and the base station would prevent TDOA data collection and, consequently, localization algorithms from functioning. Lastly, challenges were observed when there are multiple sources emitting signals at the same frequency or when environmental factors cause signal reflections and changes in direction, affecting TDOA measurements by the receivers. Before finalizing the system setup, creating a realistic simulation environment is crucial. In the fourth section, we introduced a simulation environment designed in MATLAB to anticipate potential scenarios before the measurement setup. The simulation environment was designed to be consistent with real measurements, including terrain features using the WGS84 geolocation method. Since the system was anticipated to be tested in the TÜBİTAK-BİLGEM Gebze campus area, tests in the simulation environment were conducted accordingly. After creating the simulation environment, the first test was to examine the hyperbolas formed when different receiver paths were created. It was observed that when the target was far from the receiver paths, the hyperbolas intersected each other over a wide area. Conversely, when a receiver rotated around the target, the hyperbolas intersected each other from all directions within a small area. A small intersection area of hyperbolas is crucial for the successful operation of localization algorithms like the firefly algorithm. Secondly, the formation of hyperbolas was observed when the bandwidth of the target signal and the system's sampling frequency were reduced. With low sampling frequency, the resolution of hyperbolas was significantly reduced, spreading over a very small space. When the bandwidth dropped below a few hundred MHz, the hyperbolas generally did not pass near the target. As the sampling frequency and bandwidth increased, the hyperbolas gradually approached the target and began to intersect over it. In the third simulation, a cost function was generated for the firefly algorithm, and costs in the solution space for different receiver paths were examined. As expected, as the target moved away from the receivers, the slope of the cost function around the target decreased, allowing for wider areas to be estimated as solutions. Based on these simulations, two suitable options for receiver paths were identified for the TÜBİTAK-BİLGEM Gebze campus. Finally, the average error in position determination was investigated for different sampling frequencies of sampled target signals for the identified two paths using the firefly algorithm. As expected, errors were significantly higher at low sampling frequencies, decreasing as the sampling frequency increased. The fifth chapter illustrates the measurement setup devised from the insights gleaned from simulations, deductions, and experiences presented thus far in the thesis. It starts by delineating the hardware and software of the ground station, followed by those of the receiver units, and then narrates the measurements encompassing various scenarios. The ground station hardware comprises a simple setup, consisting of a powerful computer and a modem supporting Wi-Fi 6 for communication with the receiver unit. The user interface software enables control of the receiver units from the ground station, allowing adjustments to frequency bandwidth and gain configurations. Additionally, signals received by each unit can be individually represented in time and frequency space for adjusting gains to account for signal visibility variations. Moreover, the interface facilitates data collection, time difference calculation, and execution of the firefly algorithm, with results visualized on a map. The hardware design of the receiver unit has been the most multidisciplinary aspect, given its need for lightweight deployment on UAVs while meeting power requirements throughout the flight. The design considerations for the receiver unit include power needs for communication, computation, and GPS, with antennas strategically positioned on the UAV. Extensive efforts resulted in reducing the system weight to below 3 kilograms when integrated with the protective casing. The software running on the receiver unit operates at a lower level compared to that on the ground station, directly transferring GPS-derived position, time, and frequency information to the SDR and computer hardware, then transmitting it to the ground station via Wi-Fi 6 using the SSH interface. At the TÜBİTAK-BİLGEM Gebze campus test site, various measurements were conducted to evaluate the performance of the system hardware and software. Two receivers were mounted on drone and ground vehicle setups for different test scenarios. Different signal types and receiver paths were tested. Initially, to assess system performance under optimal conditions, a 20 MHz bandwidth high-autocorrelation M-sequence signal was transmitted from a vector signal generator, attempting to locate it with drones. Subsequently, a 20 MHz bandwidth LTE downlink signal was examined. In the third measurement, the focus shifted to existing real LTE signal sources after discontinuing the use of the signal generator. The fourth measurement pushed system boundaries by utilizing a ground vehicle and stationary receiver to locate a narrowband and intermittently available LTE uplink signal. The system performed better than expected, locating the LTE uplink signal source with a 12-meter margin of error. In the final measurement, a pulse-type modulation radar was positioned to test the system's applicability in military settings. In conclusion, this thesis demonstrated the integration of two RF receivers utilizing the TDOA principle onto drones. Simulation environments were initially created to examine system performance, followed by the implementation of the system and localization of various signal sources. These efforts illustrated that the localization accuracy varies based on the type of radio signals emitted and the trajectories followed by the drones. Moreover, the feasibility of performing localization by placing TDOA-based receivers on moving units was established.