## 6 Simulation Results
This means that the joint preprocessing (superposition coding) offers great preprocessing gain that benefits per-CEU and per-user (average) capacities. Recall that \(P_{E}=\alpha P_{C}\), where \(P_{C}\) is the CCU power. Due to the excellent preprocessing gain, the MU-network MIMO can use extremely small value of \(\alpha\) (i.e., very small CEU power) to achieve uniform data rate, say \(\alpha\cong 1.5\times 10^{-3}\) and \(\alpha\cong 4\times 10^{-3}\) for MU-JMMSE and MU-JZF, respectively. This is opposite to SU-network MIMO. Moreover, it is found that MU-JMMSE is better than MU-JZF. This is because MU-JZF completely eliminates the CCI at the cost of demanding higher transmitter power. However, MU-JMMSE makes an acceptable compromise between interference suppression and transmitter power efficiency. Figure 6: Per-CCU capacity comparison between the MU and SU-network MIMO. Figure 7: Per-CEU capacity comparison between the MU and SU-network MIMO. The numerical results above are obtained under the path loss exponent \(\gamma\) of 3. Changing the value of \(\gamma\) to a typical value of 4 does not influence the previous numerical results. For example, Figure 9 shows the same observations in SU-network MIMO for both path loss exponents (\(\gamma=3,\ 4\)), i.e., smaller \(K_{\max}\) yields better per-user (average) capacity than larger \(K_{\max}\). However, smaller \(K_{\max}\) produces bigger capacity gap between CCU and CEU than larger \(K_{\max}\). Likewise, in MU-network MIMO, the observed phenomena are also the same for different values of path loss exponent. Figures 10 and 11 show the capacity comparison between different values of path loss exponent \(\gamma\) with MMSE and ZF joint preprocessing, respectively. It is found that the per-CEU capacity is much better than the per-CCU capacity at \(\alpha=1\) because of taking advantage of joint preprocessing. It is worth mentioning that, however, although the path loss increases with a larger path loss exponent \(\gamma\), we need to allocate more power to CEUs by increasing the value of \(\alpha\) to achieve a uniform capacity as shown in Figures 10 and 11. Figure 8: Capacity comparison for joint preprocessing schemes in MU-network MIMO as a function of \(\alpha\). Figure 9: Capacity comparison between different values of path loss exponent \(\gamma\) for SU-network MIMO. Next, we show how the different ratios between cell-center and cell-edge area influence the result. Figures 12 and 13 are numerical results for the superposition-coding MU-MMSE and MU-ZF joint preprocessing schemes, respectively. Because the variation of CCU capacity is much less obvious than that of CEU capacity, we give a separate illustration for CEU capacity in Figure 14, where only the MMSE CCU capacity is shown because both MMSE and ZF are similar. The result of the orthogonal MU-TDMA joint preprocessing scheme is given in Figure 4.0 Finally, Figure 16 shows the result for the SU-network MIMO. With superposition-coding MU-MMSE and MU-ZF schemes, Figures 12 and 13 indicate that reducing the ratio (i.e., increasing the edge area, but decreasing the center area) significantly benefits the CEU capacity. For example, this can be found from the decrease in the value of  
Figure 4.1 Capacity comparison between different values of path loss exponent \(\gamma\) for MU-network MIMO with ZF joint preprocessing. Figure 4.2 Capacity comparison between different values of path loss exponent \(\gamma\) for MU-network MIMO with MMSE joint preprocessing. \(\alpha\) to achieve uniform data rate as shown in Figure 4.3 As for the CCU, while cell-center area is reduced, the interference from neighboring cells is decreased and thus there is also a slight increase in CCU capacity as shown in Figure 4.4 In Figure 15, the result of the orthogonal MU-TDMA joint preprocessing scheme is similar to the superposition-coding schemes, i.e., increasing the cell-edge area benefits the capacity for either CEU or CCU capacity.