Advanced MIMO technologies for future wireless communication

The future multiple-input multiple-output (MIMO) system design is demanding for ultra-reliable low-latency (URLLC) service as well as higher throughput. This brings challenges to MIMO downlink design in three ways. Firstly, to enable URLLC service, the single-shot reliability is of interest rather than the average throughput that was optimized in the conventional MIMO design. Secondly, to achieve higher throughput, the user antennas need to be increased. In this case, if the service-antennas are increased to keep a high ratio of transmit/receive antennas as in conventional massive-MIMO systems, the Rayleigh distance of the base station will increase. Then, the wireless channel is no longer independent and identically distributed (i.i.d.) Rayleigh fading. This leads to the design problem of extremely large aperture array (ELAA). Lastly, if the transmit-antennas are not increased, the MIMO structure becomes (near) symmetric, where the channel is extremely ill-conditioned. To handle this issue, nonlinear precoding (NLP) needs to be employed. However, current NLP techniques have serious scalability problem to support large number of data-streams. This thesis deals with each challenge mentioned above, respectively. To enable URLLC, a beamforming gain prediction approach, namely the Chernoff lower-bound (Cher-LB), is proposed to fulfill extreme single-shot reliability requirement when the transmitter has imperfect channel knowledge. Compared to the literature, the Cher-LB demonstrates good tightness. For ELAA systems, the investigation is focused on the network-ELAA, where multiple access points (APs) are placed on a line with equal distance. An optimal cluster size of APs is obtained to achieve the best beamforming gain. Using this optimal cluster size significantly improves the coverage of network-ELAA for both URLLC and eMBB services. For scalable NLP, the constellation-oriented perturbation (COP) is proposed to provide a better performance-complexity trade-off than the literature. Moreover, the complexity of COP is flexibly controlled and does not change with the MIMO size.