Wireless Optimisation via Convex Bandits: Unlicensed LTE/WiFi Coexistence

TL;DR

This paper introduces the application of Bandit Convex Optimization to wireless network coexistence, demonstrating its potential through a new algorithm and experimental results in LTE/WiFi scenarios.

Contribution

It formulates a novel BCO approach for unlicensed LTE/WiFi coexistence, proposing a simple algorithm with theoretical analysis and experimental validation.

Findings

Successful formulation of LTE/WiFi coexistence as a BCO problem

Development of a sequential multi-point BCO algorithm for wireless optimization

Experimental validation showing promising results in simulated environments

Abstract

Bandit Convex Optimisation (BCO) is a powerful framework for sequential decision-making in non-stationary and partially observable environments. In a BCO problem, a decision-maker sequentially picks actions to minimize the cumulative cost associated with these decisions, all while receiving partial feedback about the state of the environment. This formulation is a very natural fit for wireless-network optimisation problems and has great application potential since: i) instead of assuming full observability of the network state, it only requires the metric to optimise as input, and ii) it provides strong performance guarantees while making only minimal assumptions about the network dynamics. Despite these advantages, BCO has not yet been explored in the context of wireless-network optimisation. In this paper, we make the first steps to demonstrate the potential of BCO techniques by formulating an unlicensed LTE/WiFi fair coexistence use case in the framework, and providing experimental results in a simulated environment. On the algorithmic front, we propose a simple and natural sequential multi-point BCO algorithm amenable to wireless networking optimisation, and provide its theoretical analysis. We expect the contributions of this paper to pave the way to further research on the application of online convex methods in the bandit setting.