Multi-user beamforming, fairness and device-to-device channel state information sharing in downlink non-orthogonal multiple access systems - Abdulhussein, Mohanad Mohammed (2021)
Non-orthogonal multiple access (NOMA) has been proposed in the past few years to be a key technology for the fifth-generation (5G) cellular networks due to its capability of achieving high spectral efficiency. The feature of NOMA is to serve multiple users at the same time/frequency/code, but with different power levels, which yields a significant spectral efficiency gain over conventional orthogonal multiple access (OMA) techniques. This thesis aims to provide fair resource allocation algorithms for downlink NOMA with multi-user beamforming systems in addition to provide new techniques for interference cancellation to boost the performance of this system in the case of perfect channel state information at the transmitter (perfect CSIT) and limited feedback. The contribution of this thesis can be divided into three main parts: The first part focuses on enhancing the user fairness with minimum throughput degradation (i.e., enhancing the throughput-fairness trade-off) for downlink NOMA with zero-forcing beamforming (ZFBF) in the case of perfect CSIT. To this end, a fair user clustering algorithm with two stages is proposed, wherein the strong and weak users are selected in the first and second stages, respectively. The algorithm stages are based on integrating the principle of proportional fairness (PF) with semiorthogonal user selection (SUS) in the first stage and with maximum signal to interference ratio (SIR) in the second stage (PF-SUS-SIR). We focus on short term fairness, where short term refers to the minimum time window in which a specified fairness is guaranteed and evaluated using Jain’s index. A fixed transmit power allocation then applied to enhance the throughput of NOMA system. Simulation results show that the proposed PF-SUS-SIR clustering algorithm significantly improves user fairness with at least 38.96% over conventional SUS-SIR clustering algorithm while maintaining the total system throughput (near maximum). In the second part, two user clustering algorithms are proposed. These algorithms are alternatives to the PF-SUS-SIR and can achieve better throughput-fairness trade-off in case of perfect CSIT and limited feedback. The first algorithm is based on integrating the maximum product of effective channel gains and the maximum SIR with the PF principle (PF-MPECG-SIR) to select strong users in the first stage and weak users in the second stage. This algorithm is designed to maximize the throughput with moderate fairness enhancement. Whereas, in the second algorithm, the MPECG and the maximum correlation are combined within the PF selection criterion (PFMPECG- CORR) in order to maximize the user fairness with a slight degradation in the total throughput. In addition, a new optimal power allocation is proposed which can achieve high sum-rate for the total system without sacrificing the sumrate of weak users. Simulation results show that the proposed PF-MPECG-CORR can significantly improve the fairness up to 50.82% and 44.90% with only 0.42% and 1.13% degradation in the total throughput with perfect CSIT and limited feedback cases, respectively. All these performance gains are achieved without increasing the computational complexity. In the third part of this thesis, the problem of imperfect inter-cluster interference (ICI) cancelation at weak users resulted from sharing a single beamforming vector between strong and weak users is addressed. To solve this problem, a new cooperative NOMA system is introduced, in which we first, propose a receiver equalizer at weak user known as weak user beam-matching (WBM) equalizer based on deviceto- device (D2D) channel state information (CSI) sharing between the nearby strong and weak users. With WBM, the ICI can be effectively eliminated at weak users. Second, based on WBM principle, strong user beam-matching (SBM) equalizer is proposed at strong users in order to eliminate the generated ICI in case of limited feedback. Third, a new power allocation strategy is proposed to improve weak users’ performance by considering the gained throughput from interference cancellation. Finally, besides the sum-rate, which is adopted as the performance metric by most of the existing NOMA works, the bit error rate (BER) of NOMA users in cooperative NOMA is calculated with those in other schemes. Simulation results show that our cooperative NOMA with the proposed equalizers achieves significant sum-rate and BER improvements over non-cooperative schemes with both perfect CSIT and limited feedback scenarios.