FEAT: Fair Coordinated Iterative Water-Filling Algorithm

TL;DR

FEAT is a novel algorithm for fair and near-optimal channel allocation in interference-limited systems, balancing efficiency and fairness with low complexity, and showing robustness in multi-user scenarios.

Contribution

The paper introduces FEAT, a new water-filling algorithm that enhances fairness and efficiency in user channel assignment with low computational complexity.

Findings

FEAT outperforms related algorithms in interference-limited systems.

It achieves near-optimal, fair, and energy-efficient solutions.

Global optimality is less affected by the number of users than individual fairness.

Abstract

In this paper, we consider a perfect coordinated water-filling game, where each user transmits solely on a given carrier. The main goal of the proposed algorithm (which we call FEAT) is to get close to the optimal, while keeping a decent level of fairness. The key idea within FEAT is to minimize the ratio between the best and the worst utilities of the users. This is done by ensuring that, at each iteration (channel assignment), a user is satisfied with this assignment as long as he does not loose much more than other users in the system. It has been shown that FEAT outperforms most related algorithms in many aspects, especially in interference-limited systems. Indeed, with FEAT we can ensure a near-optimal, fair and energy efficient solution with low computational complexity. In terms of robustness, it turns out that the balance between being nearly globally optimal and good from individual point of view seems hard to sustain with a significant number of users. Also notice that, in this regard, global optimality gets less affected than the individual one, which offers hope that such an accurate water-filling algorithm can be designed around competition in interference-limited systems.