 Modulator Far user Superposition Transmitted Signal Coding Messege Modulator Near user FIGURE 5.4 PD-NOMA transmitter. where H is the channel, x is the transmitted signal, and n denotes the AWGN with mean zero and variance 22. Two common receiver designs are minimum mean square error (MMSE) and zero- forcing (ZF) for the MIMO system [18]. The ZF detector only focuses on the elimin- ation of channel effect and has the form of Wzp="H"(HH") (5.3) where superscript "H" denotes the Hermitian transpose operation. The MMSE detector additionally considers the impact of additive noise, and improves the ZF detector with the form of 5G Wireless Communication System in Healthcare Informatics (5.4) Since the MMSE detector also depresses the noise effect, it has a better perform- ance than the ZF detector. For the purpose of improving the performance of the MMSE detector in interfer- ence cancellation, the authors in [19], proposed a novel modification of it, resulting in the so-called MMSE interference rejection combining (MMSE-IRC) detector. It is worth mentioning that the complexity of linear detectors is often lower than that of nonlinear ones, and hence they are more commonly employed in the SIC technique. SIC will be performed by the user with low power allocated to it to cancel the effect of other user interference. The nearby user with less interference in the channel decodes and cancels the distant user's signal first then decodes its signal, while the distant user decodes its signal directly due to fading of the other user's signal and will not need the use of SIC in its condition. Figure 5.5, shows the flow chart of the codeword-level SIC that we used in our system. In the receiver side, we only use SIC on the near user S because the far user will decode directly because of the low power allocated to the near signal Snear assumed that the signal will be faded and will not reach the far user S far The receiver system is shown in Figure 5.6. The received signals at the two users are Demodulation of Far User Signal De