ecoded the far user signal denoted by S far directly without using SIC, assuming that the near user signal was due to the low power allocated to the user. It is assumed that the signal will be faded and will not reach the far user side. The receiver system is shown in Figure 5.8. The flow chart of the decoding process is depicted in Figure 5.7. The received signals at the two users, namely the far and near users can be defined as: (5.17) Where h and g represents the Rayleigh channel vector which is a zero mean complex circular Gaussian with co-variance matrix R for i E { far, near}, and near and nfare additive white Gaussian noise (AWGN). Denoting 5 as the signal to interference plus noise ratio (SINR) to decode the far user message at the near user receiver signal near and Snear near denotes the signal to noise ratio (SNR) to decode the near user message at its receiver 'near* So, we will have, at the near user receiver: (5.18) Where h denotes the Rayleigh channel of the near user, and V1,V2 denote the power allocation to each user where r1 is stronger than r2 to make the decoding for the near user successful. At the far user, the message for the far user is decoded directly because the signal of the near user will be faded as the signal is weak. We will have the SINR denoted as V far to decode the far user signal as: (5.19) The achievable rates of decoding messages for far and near users are: 5G Wireless Communication System in Healthcare Informatics (5.20) Where B denotes the bandwidth, U denotes the number of users and G denotes the channel gain. 5.4.3.2 Simulation Results The bit error rate (BER) performance of near user S near and far user S far for the system shown in Figure 5.8 is calculated in different Eb/NO where the summation of power allocated to the two users must be equal to 1, which satisfies r2 +12 = 1. The number of users considered as NOMA is 24 users from Figure 5.14. We used binary phase shift keying modulation (BPSK) to modulate users' signals. The simulation result in Figure 5.15 shows the 