## 3 Results and Discussion
### Case 1: Experimental Analysis in FL dimensions  
When the MFs were set to (19) and (20) with the vector norm, \(\mathbf{h}\), including the channel gains of all users, Figure 3 shows that the local effectiveness of NOMA FL reached the data rate bound of PLS in the case of high user density. Without QoS features, the AUDR depends on channel gains and outages, which are prone to having a single target in throughput maximization.  
\[\left[a_{0}^{(G)},b_{0}^{(G)},c_{0}^{(G)},d_{0}^{(G)}\right]_{h,G\in[L,M,H]^{ \mathrm{T}}}=\left[\begin{array}{cccc}0&0.1&0.3&0.3\\ 0.1&0.3&0.6&0.8\\ 0.6&0.8&0.8&0.8\end{array}\right]\times\left|\mathbf{h}\right|_{\infty} \tag{19}\]  
\[\left[a_{0}^{(G)},b_{0}^{(G)},c_{0}^{(G)},d_{0}^{(G)}\right]_{outage,G\in[L,M,H ]^{\mathrm{T}}}=\left[\begin{array}{cccc}0&0.05&0.1&0.1\\ 0.1&0.15&0.2&0.25\\ 0.2&0.25&0.35&0.45\end{array}\right] \tag{20}\]  
\[\left[a_{0}^{(G)},b_{0}^{(G)},c_{0}^{(G)},d_{0}^{(G)}\right]_{QoS,G\in[L,LM, MH,H]^{\mathrm{T}}}=\left[\begin{array}{cccc}0&0&0.25&0.25\\ 0.05&0.25&0.5&0.5\\ 0.5&0.7&1.0&1.0\\ 1.0&1.5&2.0&2.0\end{array}\right]\times\left|\alpha_{1}\cdot\beta_{1}\right|. \tag{21}\]  
In Figure 3, PLS and FTPA are treated as two-dimension methods, and NOMA FL and OFDMA FL are related to two-dimension FL features. When the MF of the QoS requirements was set to (21), as shown in Figure 4, the holistic high QoS requirement may lead to unreasonable resource allocation and a decrease in the system throughput. Although the QoS parameters were set, the PLS and FTPA based on static user priority may, theoretically, not consider the QoS. Hence, the differences between 30 Mbps and 60 Mbps QoS expectations, based on PLS and FTPA, are caused by the channel gain distribution of different user positions.  
In this experiment, the critical value of high user density in indoor VLC UDN was nine users, which was obtained by 0.25 persons/m\({}^{2}\) and 36 square meters. Furthermore, when \(\psi_{FOV}=60^{\circ}\) and \(L=1.8\) m, as shown in Table 3, an optical AP covered a smaller area than 36 m\({}^{2}\), which is  
\begin{table}
\begin{tabular}{c c c c} \hline
**Description** & **Case 1** & **Case 2** & **Case 3** \\ \hline
**Influence factor** & FL dimensions & QoS, & Layout \\
**Features** & \(h_{k}\), \(P_{k}\)\({}^{out}\) & \(h_{k}\), QoS, \(P_{k}\)\({}^{out}\) & with light angles \\ \hline
**NOMA FL** & Dynamic (\(h_{k}\), \(P_{k}\)\({}^{out}\)) & Dynamic (\(h_{k}\), QoS, \(P_{k}\)\({}^{out}\)) & \(\psi_{FOV}\) \\
**NOMA PLS** & Static (\(h_{k}\), \(P_{k}\)\({}^{out}\)) & Static (\(h_{k}\), \(P_{k}\)\({}^{out}\)) & \(\psi_{FOV}\) \\
**NOMA FTPA** & Static (\(h_{k}\), \(P_{k}\)\({}^{out}\)) & Static (\(h_{k}\), \(P_{k}\)\({}^{out}\)) & \(\psi_{FOV}\) \\
**OFDMA FL** & Dynamic (\(h_{k}\), \(P_{k}\)\({}^{out}\)) & Dynamic (\(h_{k}\), QoS, \(P_{k}\)\({}^{out}\)) & \(\psi_{FOV}\) \\ \hline \end{tabular}
\end{table}
Table 4: Comparisons of different cases. The labels FL, FOV, FTPA, NOMA, OFDMA, PLS, and QoS are fuzzy logic, field of vision, fractional transmit power allocation, non-orthogonal multiple access, orthogonal frequency division multiple access, power law strategy, and quality of service, respectively.  
approximate to 27 m\({}^{2}\). In Figure 3, the peak value of high area traffic requirement is shown to reach 10 Mbps/m\({}^{2}\), which means that NOMA FL can handle indoor VLC cells. With different dimensions of Figures 3 and 4, we showed that the multi-dimension FL of NOMA outperforms other methods under VLC UDN conditions which are used in our proposed scenario.