Joint Cell Selection and Resource Allocation Games with Backhaul Constraints

TL;DR

This paper introduces a game-theoretic approach to optimize user association and resource allocation in wireless networks with backhaul constraints, achieving near-optimal fairness with reduced computational complexity.

Contribution

It models the complex resource allocation problem as a potential game, enabling efficient, real-time solutions close to optimal while distributing computational load.

Findings

Game-theoretic model achieves near-optimal fairness.

Reduces computational complexity compared to traditional methods.

Enables real-time resource allocation in constrained networks.

Abstract

In this work we study the problem of user association and resource allocation to maximize the proportional fairness of a wireless network with limited backhaul capacity. The optimal solution of this problem requires solving a mixed integer non-linear programming problem which generally cannot be solved in real time. We propose instead to model the problem as a potential game, which decreases dramatically the computational complexity and obtains a user association and resource allocation close to the optimal solution. Additionally, the use of a game-theoretic approach allows an efficient distribution of the computational burden among the computational resources of the network.