SIC.) In our system model, if we assume H,HH HHH, here > means if A > B, then (A - B) is a positive definite matrix. This assumption implies UE n has a better channel condition 3 5G NOMA-Enabled Wireless Networks and hence can decode UE k's message. Thus, at UE n, we have Rn.k = (3.9) which is the maximum achievable rate for UE k at UE n. Considering the error propagation, the data rate for UE n's own message would be, (3.10) The error propagation factor B is assumed be a fixed value. While at UE k, the desired signal can be decoded directly. (3.11) In order for UE k to have a fairly small BER, the maximum allowable data rate for UE k is, (3.12) Here we normalize the bandwidth at the BS to 1. Next, we show that Rk = Rk.k the proof follows appendix A in [171] and can be briefly summarized as follows. Proof: Since HH , we can write Hn = MHk, where M is a N x N matrix and MMH > IN. Due to the property of determinant operation, we can rewrite Rn.k as Rn.k = (3.13) Define = Qk.k = then we substitute Hn = MHk in Qn,k. Qn.k = = Qk.k (3.14) Thus, log2 det (I+Qn.k) > log det (I+Qk.k), which means Rk.k. 3.3.2 Problem Formation In this chapter, we intend to maximize the system throughput by applying NOMA and MU-MIMO. The problem can be formed as following. max (Rn+Rk) (3.15a) Wn,Wk (3.15b) Rk R0. (3.15c) 3.4 Precoding and Power Allocation Equation (3.15b) is the constraint for maximum allowed power from the BS. 3.15c sets a minimum data rate for the weaker UE. Rn and Rk can be calculated based on (3.10) and (3.11), respectively. One note here is due to the error propagation, the stronger UE may suffer severe residual interference from the weaker one; thus, its data rate may be lower. However, we do not consider this situation in the chapter; the lower data rate limit is only for the weaker UE. When a resource block (RB) is available, the BS needs to determine the following: (i) How to properly design the precoding matrix; (ii) How to allocate the power to each UE. The above optimization problem is hard to solve, and the rea