## 3 Results and Discussion  
### Experimental Conditions and Parameters  
For a room of 6 m \(\times\) 6 m \(\times\) 3 m, the parameters of the VLC scenario are indicated in Table 3. According to indoor UDN modeling, a high user density is 0.25 persons per square meter, so the critical value of the number of ultra-dense users is nine persons in the simulation scenario. For the probability distribution generation of QoS, the gamma distribution is selected to set the QoS expectation \((\alpha_{1}\cdot\beta_{1})\in\{1,10,20,30,40,50,60\}\) (Mbps), where \((\alpha_{1}\cdot\beta_{1})\in\{1\times 1,2\times 5,4\times 5,5\times 6,5 \times 8,5\times 10,6\times 10\}\). For the estimation of the outage probability, if we denote the number of users as \(K\), the normalization of the beta distribution is selected to set \(\alpha_{2}=K+1\) and \(\beta_{2}=k,k\leq K\). In the current research, NOMA PLS and NOMA FTPA are the typical power allocation strategies, and our proposed power allocation method is denoted as NOMA FL. To confirm that NOMA FL guarantees the QoS as much as possible, we regard the upper data rate bound of OMA as the QoS requirements of the NOMA system to reflect the data rate relationship among NOMA FL, PLS and FTPA. For verification that NOMA FL satisfies dynamic user priority, the comparisons include two aspects:  
* To determine the performance difference between static and dynamic user priorities, we performed comparisons among NOMA FL, NOMA PLS and NOMA FTPA. * To demonstrate the performance difference between NOMA and OMA, we measured NOMA FL and OFDMA FL with the same dynamic user priority. The measurement of advantages of the FL system did not uniquely involve the user data rate [25, 26], which may not synthetically reflect the performance of the FL system. For the measurement of adaptability to QoS guarantee in VLC networks, as shown in Table 4, we performed three simulation cases to analyse the performance of NOMA FL, NOMA PLS, NOMA FTPA, and OFDMA FL. The purpose of each case and the evaluation indicators are listed as follows. * Case 1 (analysis of FL dimensions): Without considering QoS requirements, PLS and FTPA can equivalently be regarded as two-dimension considerations of the channel gain and outage. For two dimensions of FL features, we performed experiments regarding the user data rate and user satisfaction in NOMA FL and OFDMA FL without QoS constraints. In this case, we discovered that PLS and FTPA cannot successfully guarantee the QoS, and that the maximization of throughput is not equivalent to the provision of QoS data rate. * Case 2 (analysis of the variety of QoS): For the three complete FL features, comparing PLS with FTPA, NOMA FL revealed the difference between dynamic and static user priorities. In regard to the comparison of NOMA FL with the dynamic user priority of OFDMA FL, NOMA FL was able to accommodate QoS requirements to show a difference in system performance. In this case, regarding the tradeoff between user data rate and QoS guarantee, we introduced the commonly used evaluation measure of QoS guarantee to demonstrate the clear advantages of FL. \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Symbol** & **Value** & **Symbol** & **Value** \\ \hline Received area & \(10^{-4}\) m\({}^{2}\) & Received height & \(L=1.8\) m \\ \(\psi_{FOV}\) & \(60^{\circ}\) & \(\Phi_{1/2}\) & \(60^{\circ}\) \\ \(P_{t}\) & \(8\) W & \(\gamma\) & \(0.47\) \\ Bandwidth & \(25\) MHz & \(N_{0}\) & \(10^{-19}A^{2}/\mathrm{Hz}\) \\ \(T_{f}\) & \(1\) & \(n\) & \(1.5\) \\ \(QoS\) & \(\sim\Gamma\left(\alpha_{1},\beta_{1}^{-1}\right)\) & \(outage\) & \(\sim Beta(\alpha_{2},\beta_{2})\) \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Experimental parameters. * Case 3 (analysis of VLC lighting): In different visible lighting conditions, we showed the relationship between the FOV angle of illumination and the performance of the communication schemes. In this case, combined with VLC UDN, we considered both high user density and area user traffic demands to show the advantage of FL.