# Joint Interference and Phase Alignment among Data Streams in Multicell MIMO Broadcasting
## 7 Simulation Results and Analysis
### Convergence Time Delay Error CSI  
When configured as [2; 2; 4; 13; 8], Figure 5 shows the relationship between the average system capacity and the number of iterations when the transmitted power of each user is 5 dB. As can be seen from the figure, in the time delay error CSI the user sends when the output power is 5 dB, the average system capacity of the proposed algorithm and that of literature [11] are convergent for about 20 iterations, while the MAX-SINR-SCEK algorithm converges approximately 23 times. It can be seen that the proposed algorithm improves the performance of the system without increasing the number of iterations and further confirms the convergence and feasibility of the algorithm.  
Average System Capacity and BER under Time Delay Error CSI with Different Number of Cells and Users Configurations  
As shown in Figure 6, in nonideal CSI, the capacity of several typical algorithms is compared when configured as [7; 10; 4; 13; 8] and [3; 4; 4; 13; 8]. In time delay error CSI, the proposed algorithm has more room for handling interference and delay error, and minimizes the effects of interference and delay errors, further combining power allocation and phase alignment to improve signal quality. So, the proposed algorithm is better than the literature [17] MAX-SINR-SCEK algorithm. The literature [11] adopts MMSE and LSE high-order predicting channel, and although it can improve the channel quality under the delay error CSI to a great extent, the improvement is relatively limited and its performance is inferior to the proposed algorithm. Furthermore, it is obvious from Figure 5 that the proposed algorithm with [7; 10; 4; 13; 8] configuration has high sum rate as compared to its other configuration [3; 4; 4; 13; 8]. Moreover, both configurations of the proposed IA algorithm outperform Literature [11; 17] algorithms which clearly indicates its benefits over the existing algorithms.  
Figure 5: Average system capacity against the number of iterations under time delay error CSI.  
Figure 7 simulates the BER performance of several typical algorithms when configured as [7,10,4,13,8] and [3,4,4,13,8]. When using QPSK for modulation, the proposed algorithm uses power allocation and aligns the phase of the transmitter and receiver signals to reconstruct the interference into a green energy source, which enhances the power of the desired symbol, and BER is greatly improved. The BER of the proposed algorithm is lower than the algorithms of literature [11,17]. Furthermore, the BER of the proposed algorithm when configured as [7,10,4,13,8] has much better performance in both ideal and delay error CSI as compared with its other configuration [3,4,4,13,8] and Literature [11,17]. Both configurations show overall better BER performance than the existing algorithms which makes it an attractive candidate for reducing the interference among user data streams in MIMO systems.  
Figure 6: Sum rate comparison under time delay error CSI for multiple cells and users.  
Figure 7: BER comparison under time delay error CSI for multiple cells and users.