LEE- Telekomünikasyon Mühendisliği-Doktora
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ÖgeAnalytical 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 Dalı5G 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.