Optimized 3D Placement of LiFi Access Points towards maximizing Wireless Network Performance

Abstract

In the next generation of networks, the high data rate and large bandwidth offered by Light-Fidelity (LiFi) are expected to be fully exploited to satisfy the diverse Quality of Service (QoS) requirements of users. LiFi networks are expected to provide full data coverage while also satisfying illumination requirements in indoor environments. Thus, the optimized placement of LiFi Access Points (APs) is of utmost importance. Extending the commonly applied 2D placement, we include the height of the AP, which is an important factor to consider due to the short range of LiFi and limited Field of View (FoV) of the receivers. To this end, we propose a 3D LiFi Access Point placement framework that formulates the placement as a multi-objective optimization problem minimizing the number of APs and maximizing the sum rate while providing a guaranteed minimum rate and illumination level. Since the exact positions of users are unknown during network planning and change dynamically after deployment, the probability distribution of user occurrence is considered in the optimization. This results in the network performance being maximized in areas where users are likely to be present. This optimization problem is solved with the proposed multi-objective genetic algorithm. The framework is evaluated with simulations and the results show that the height of the AP greatly influences the network performance. We conclude that a free choice of the height of each AP results in an average rate that is significantly better than the rate achievable when all APs are placed at the same height.

PlaciFi: Orchestrating Optimal 3D Access Point Placement for LiFi-WiFi Heterogeneous Networks

“…This paper builds upon our previous work in [10], where we investigated the network planning of a LiFi-only communication and illumination network in an indoor environment. In our previous paper, we formulated an optimization problem with multiple objectives: minimizing the number of APs and maximizing the sum rate while satisfying constraints on the minimum guaranteed achievable rate and minimum illumination level.…”