Fairness-Oriented User Association in HetNets Using Bargaining Game Theory

TL;DR

This paper proposes a fairness-oriented user association method in HetNets using bargaining game theory, specifically Nash Bargaining Solution, to achieve fair load distribution and Pareto optimality, with a novel coalition generation algorithm.

Contribution

It introduces a bargaining game-based framework for fair user association in HetNets and proposes a SINR-based coalition generation algorithm for improved coalition formation.

Findings

The proposed scheme improves fairness and load balancing among BSs and users.

It achieves proportional fairness and Pareto optimality in user association.

Performance is comparable to throughput-oriented schemes in terms of data rates.

Abstract

In this paper, the user association and resource allocation problem is investigated for a two-tier HetNet consisting of one macro Base Station (BS) and a number of pico BSs. The effectiveness of user association to BSs is evaluated in terms of fairness and load distribution. In particular, the problem of determining a fair user association is formulated as a bargaining game so that for the Nash Bargaining Solution (NBS) abiding the fairness axioms provides an optimal and fair user association. The NBS also yields in a Pareto optimal solution and leads to a proportional fair solution in the proposed HetNet model. Additionally, we introduce a novel algorithmic solution in which a new Coalition Generation Algorithm (CGA), called SINR-based CGA, is considered in order to simplify the coalition generation phase. Our simulation results show the efficiency of the proposed user association scheme in terms of fairness and load distribution among BSs and users. In particular, we compare the performance of the proposed solution with that of the throughput-oriented scheme in terms of the max-sum-rate scheme and show that the proposed solution yields comparable average data rates and overall sum rate.