an obtain a larger portion of power. This will benefit the whole system in terms of fairness and throughput. In [214], the concept of NOMA is discussed from the information theoretic perspective, and the conclusion is that NOMA can have a better performance compared with OMA in terms of both system sum rate and user individual rate, especially when the users channel gains are distinct. In [171] and [170], a similar downlink MIMO and NOMA system model is proposed, and the authors solved the optimization problem with bisection power search algorithm and applied the singular value decomposition (SVD) if the channel state infor- mation (CSI) is available at the BS, or equally distribute powers among different antennas if CSI is unknown for the precoding design. These works, however, all assume a perfect subtraction of previous user signals in SIC such that there's no residual interference which will affect the current decoding. This assumption turns out to be a strong one since various factors can actually cause errors, such as deep fading, imperfect decoding, and channel estimation errors [140]. In the case of decoding more users' signal, errors from previous will accumulate and greatly affect the next stage (we refer this as error propagation). In this chapter, we take error propagation into consideration, a concept that already exists in code division multiple access (CDMA) systems. Similar papers can be found in [8] and [9]. In fact, CDMA shares some common features with NOMA. Both of them exploit the multiuser interference to achieve a higher performance rather than simply avoid it. Performance gain also largely depends on some assumptions like perfect channel estimation and power allocation, and violations can cause 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 & Sons Ltd. 3 5G NOMA-Enabled Wireless Networks serious performance degradation. In this chapter, we propose a general error propagatio