Channel-quality-driven high-performance receivers for next generation wireless communication systems

Abstract

Multi-input multi-output (MIMO) technology greatly improves the spectral efficiency and reliability of wireless communication systems. As the demand on spectral efficiency keeps increasing, large MIMO has been proposed for next generation wireless systems, where tens or hundreds of antennas are equipped at either or both ends of the communication link. Thus, it becomes critical to design high-performance receivers with affordable complexity. In this dissertation, we develop efficient channel-quality-driven high-performance receivers for various MIMO systems. For large MIMO systems where similar numbers of antennas exist at both sides of the communication link, several lattice reduction (LR) algorithms have been proposed to enhance the channel quality within reasonable complexity. In such case, we study the maximum information rate of MIMO transmission with LR-aided linear equalizers and apply LR techniques to improve the performance of two specific multiuser MIMO systems. We also design learning-based LR algorithms that efficiently improve channel quality according to pre-defined objectives. For large MIMO systems where the number of antennas at one side of the link is much greater than that at the other side, we study the impact of MIMO size and propagation conditions on the channel quality and the performance of linear detection. In the end, we propose channel-assisted strategies for the automatic repeat request process at linear receivers to improve the reliability of the receiver while reducing its latency and complexity. The effectiveness of our proposed schemes is verified by extensive simulations.