Beamformer design based on non-linear reception in MIMO downlink system

Abstract

In thesis, we investigate beamformer design based on non-linear recption in MIMO downlink system for next wireless communication system. This thesis consists of three parts and its contents as follows. In the first part of the thesis, an efficient transmit beam design and user scheduling method are proposed for multi-user (MU) multiple-input single-output (MISO) non-orthogonal multiple access(NOMA) downlink, based on Pareto-optimality. The proposed beam design and user scheduling method groups simultaneously-served users into multiple clusters with practical two users in each cluster, and then applies spatical zero-forcing (ZF) across clusters to control inter-cluster interference (ICI) and Pareto-optimal beam design with successive interference cancellation (SIC) to two users in each cluster to remove interference to strong users and leverage signal-to-interference-plus-noise ratios (SINRs) of interference-experiencing weak users. The proposed method has flexibility to control the rates of strong and weak users and numerical results show that the proposed method yields good performance. In the second part of the thesis, a new transceiver architecture for K-user multiple-input singleoutput (MISO) broadcast channels (BCs) based on linear and non-linear mixture reception is proposed as an alternative to conventional fully linear zeroforcing (ZF) downlink beamforming. In the new transceiver architecture, some closely-aligned users are grouped, and sequential superposition coding and non-linear successive cancellation (SIC) reception based on Pareto-optimal design is applied toeach users in group to mitigate the performance degradation of fully linear beamforming due to high interference caused by closely aligned channel vectors, while ZF beamforming is maintained across roughly-orthogonal other groups. we prove that the proposed new transceiver design architercture increase diversity order for K-user MISO broadcast channels drastically. Numerical results show that the proposed new architecture yields non-trivial gain over conventional full ZF beamforming. In the last part of the thesis, adaptive training beam sequence design for efficient channel estimation in large millimeter-wave (mmWave) multiple-input multiple-output (MIMO) channels is considered. By exploiting the sparsity in large mmWave MIMO channels and imposing a Markovian random walk assumption on the movement of the receiver and reflection clusters, the adaptive training beam sequence design and channel estimation problem is formulated as a partially observable Markov decision process (POMDP) problem that finds non-zero bins in a two-dimensional grid. Under the proposed POMDP framework, optimal and suboptimal adaptive training beam sequence design policies are derived. Furthermore,a very fast suboptimal greedy algorithm is developed based on a newly proposed reduced sufficient statistic to make the computational complexity of the proposed algorithm low to a level for practical implementation. Numerical results are provided to evaluate the performance of the proposed training beam design method. Numerical results show that the proposed training beam sequence design algorithms yield good performance.