p between two precoding matrices is small with UE n; this is because as the SINR increases, the water-filling algorithm has a similar performance compared with equal power distribution. Figure 3.2 shows the sum rate of UE n and UE k as Pn changes when B = 0.05. We can see that the sum rate increases while Pn increases. From Figure 3.1, it has been shown that the rate of UE n increases faster than the decreasing speed of rate of UE k when Pn increases. Therefore, the sum rate of UE n and UE k increases while Pn increases. Figure 3.2 also shows the proposed precoding design performs better than identity matrix precoding method with respect to sum rate. Figure 3.3 shows the rates of UE n and UE k as Pn changes when B is set to be 0.65 for error propagation. We can still see that the rate of UE n increases when Pn increases, while the rate of UE k decreases when Pn increases. However, the rate of UE n increases faster than the decreasing speed of rate of UE k when Pn increases. The rate of UE n increases Proposed precoding design Identity matrix precoding Power for UE n (B = 0.05) Figure 3.2 Sum rate with different precoding matrix as Pn increases (B = 0.05). 3.5 Numerical Results Rn with identity matrix precoding Rk with identity matrix precoding Rn with proposed precoding Rk with proposed precoding Power for UE n (B = 0.65) Figure 3.3 UE rate with different precoding matrix as P n increases (B = 0.65). Proposed precoding design Identity matrix precoding Power for UE n (B = 0.05) Figure 3.4 Sum rate with different precoding matrix as Pn increases (B = 0.65). slower than the decreasing speed of rate of UE k when Pn n > 0.76. The reason is that when Pn < 0.76, the interference from UE n is smaller than the noise; therefore, the SINR decreases slowly. However, when P > 0.76, the interference becomes dominant and causes the SINR to decrease rapidly. Compared with Figure 3.1, the rate of UE n increases slower than that in Figure 3.1. Since a bigger B is used in this case, residual interference from UE k has a bigger effe