ric widely used in performance evaluation. It is shown in [44] that the outage performance of NOMA is superior to the traditional OMA in a group of randomly deployed users. This chapter develops a precoding and power allocation strategy to further enhance the system performance in terms of sum rate. Similarly, both [171] and [170] apply NOMA into MIMO scheme. The algorithms in their studies can be applied with or without CSI. In [159] and [215] system-level performance of using NOMA in LTE and heterogeneous net- works is evaluated, and the results show promising improvements over existing radio access technologies (RATs). In [141], random beamforming together with intra-beam superposi- tion coding and SIC with BS cooperation is investigated. Relay cooperative communica- tion has been studied in the following studies. Men and Ge [129] uses a single-antenna amplified-and-forward (AF) relay to help the transmission between multi-antenna BS and users. Kim and Lee [96] uses relay to help the transmission to a poor-channel user. Ding et al. [46] investigates the system performance under a selection of multiple relays. As NOMA uses SIC at the receiver to decode multiple user information, the performance of SIC can greatly impact NOMA. Most existing studies assume perfect SIC in NOMA study with a few like [140] considering SIC error due to imperfect channel knowledge. One of our earlier studies [172] investigates the sum rate performance in a MIMO+NOMA system, and it considers error propagation in the SIC process. The idea was inspired by the decoding pro- cess in CDMA systems [8]. It assumes there is a residual power from previously decoded signals, and this residual power can arise due to channel estimation error, imperfect con- stellation mapping, or channel fading. SIC error propagation causes a chain effect and it affects the last decoded user most. 5G and Beyond Wireless Communication Networks, First Edition. Haijian Sun, Rose Qingyang Hu, and Yi Qian. © 2024 John Wiley & Sons Ltd. Published 2024 by John Wiley & So