Optimization of Cellular LiFi Network Deployment for Gaussian Mixture User Distributions

The long-term performance of LiFi networks significantly depends on the location of access points. The optimized placement can be determined based on the distribution of users in the room. In this paper, we investigate the placement optimization for average throughput maximization in the presence of asymmetric distributions. In particular, we represent users’ distribution in the indoor environment by the Gaussian mixture model, which is powerful and computationally convenient. Then we obtain the optimized deployment for different scenarios using gradient ascent algorithm. The results show that optimization of deployment significantly improves the average throughput of the network. As the variance of the mixture components increases, the optimized placement approaches a symmetric deployment.