## 6 Simulation Results
It is shown that the uniform capacity occurs at a smaller \(\alpha\), (\(\alpha=1.42\)), as compared with \(\alpha=2.15\) associated with the smaller \(K_{\max}\) in Figure 4. By making a comparison between Figures 4 and 5, it is found that the per-user (average) capacity with smaller \(K_{\max}\) is always better than that with larger \(K_{\max}\), although it yields larger capacity gap than that of larger \(K_{\max}\). Nevertheless, while achieving uniform capacity (zero capacity gap), the smaller \(K_{\max}\) still yields better average capacity (about \(2.143\times 10^{5}\) bits/sec) than that with the larger \(K_{\max}\) (about \(2.132\times 10^{5}\) bits/sec). Therefore, with \(K_{\max}=0.25\), SU-network MIMO offers \(1.1\times 10^{3}\) more bits per second than that with \(K_{\max}=0.4\). In conclusion, with uniform capacity, smaller \(K_{\max}\) can generally provide the SU-network MIMO with larger average capacity. Figure 4: Capacity comparison as a function of \(\alpha\) for a small \(K_{\max}(=0.25)\) in SU-network MIMO. Figure 3: Curves of power reduction factors associated with Figure 2.  
Uniform capacity makes sure that users have uniform data rate regardless of their position. According to the previous results, we found that uniform data rate comes at the price of reducing the average capacity. Studies on wireless usage show that more than 50% of all voice calls and more than 70% of data traffic originate from indoors (i.e., immobile conditions) [24]. As a result, the uniform capacity is only important for the small part of truly mobile users. For example, as a mobile user with SU-network MIMO moves from cell center to cell border, the cell-edge capacity will drop a small percentage as compared with cell-center capacity, and thus the user may be deficient in capacity. Thus, uniform data rate is essential for this scenario. Now we turn our attention to the MU-network MIMO and in the meantime, make comparison with SU-network MIMO. In terms of the number of per-sector CEUs (\(y\)), Figure 6 presents the per-CCU capacity comparison for three MU-network MIMO schemes and the SU-network MIMO. Recall that three cooperative BSs in a CCS collectively serve a group of \(N_{CEU}\) CEUs using a whole out sub-band. Thus, we have \(N_{CEU}=3y\) for MU-network MIMO. In MU-network MIMO, both MU-JMMSE, and MU-JTDMA have soft CEU capacity, but MU-JZF does not, because it is subject to the usage constraint \(N_{CEU}N_{R}\leq 3N_{T}\) as shown in Section 4.2. In general, it is found that MU-network MIMO is better than SU-network MIMO in CCU capacity, except for MU-JZF at \(y=5\), whose CCU capacity is slightly less than SU-network MIMO. Figure 7 gives the per-CEU capacity comparison. Except for the orthogonal scheme (MU-JTDMA), it is found that the superposition-coding schemes (MU-JMMSE and MU-JZF) have obvious CEU capacity improvement over the SU-network MIMO [25]. In addition, since there are just 5 sub-channels in an outer frequency sub-band, the SU-network MIMO only can serve up to 5 CEUs per sector. By contrast, the MU-network MIMO has a soft capacity for CEUs, except for MU-JZF because it is subject to the usage constraint \(N_{CEU}N_{R}\leq 3N_{T}\). For example, as increasing two additional CEUs from 5 CEUs to 7 CEUs in each sector, we calculate that the MU-JMMSE only drop about 0.9% and 15.2% for per-CCU and per-CEU capacity, as shown in Figures 6 and 7, respectively. Figure 5: Capacity comparison as a function of \(\alpha\) for a large \(K_{\max}(=0.4)\) in SU-network MIMO. Figure 8 shows the capacity comparison for both superposition-coding schemes (MU-JMMSE and MU-JZF) as a function of \(\alpha\). It is found that the per-CEU capacity is much better than the per-CCU capacity (at \(\alpha=1\)) because of joint preprocessing. By contrast, for SU-network MIMO with \(\alpha=1\), its per-CEU capacity is still distinctly worse than the per-CCU capacity, as shown previously in Figures 4 and 5.