MobiFi: Mobility-Aware Reactive and Proactive Wireless Resource Management in LiFi-WiFi Networks

Abstract

This paper presents MobiFi, a framework addressing the challenges in managing LiFi-WiFi heterogeneous networks focusing on mobility-aware resource allocation. Our contributions include introducing a centralized framework incorporating reactive and proactive strategies for resource management in mobile LiFi-only and LiFi-WiFi networks. This framework reacts to current network conditions and proactively anticipates the future, considering user positions, line-of-sight blockages, and channel quality. Recognizing the importance of long-term network performance, particularly for use cases such as video streaming, we tackle the challenge of optimal proactive resource allocation by formulating an optimization problem that integrates access point assignment and wireless resource allocation using the alpha-fairness objective over time. Our proactive strategy significantly outperforms the reactive resource allocation, ensuring 7.7% higher average rate and 63.3% higher minimum user rate for a 10-user LiFi-WiFi network. We employ sophisticated techniques, including a Branch and Bound-based Mixed-Integer solver and a low-complexity, Evolutionary Game Theory-based algorithm to achieve this. Lastly, we introduce a novel approach to simulate errors in predictive user position modeling to assess the robustness of our proactive allocation strategy against real-world uncertainties. The contributions of MobiFi advance the field of resource management in mobile LiFi-WiFi networks, enabling efficiency and reliability.