Coordination and Bargaining over the Gaussian Interference Channel

TL;DR

This paper explores how two selfish users can negotiate and coordinate over a Gaussian interference channel using game theory, focusing on incentives, fair rate allocation, and comparing bargaining solutions with traditional time-division methods.

Contribution

It introduces a game-theoretic framework for incentive-compatible cooperation and fair rate allocation in Gaussian interference channels using Nash bargaining solutions.

Findings

Identifies conditions where users have incentives to cooperate.

Proposes a negotiation scheme based on Han-Kobayashi coding.

Shows the bargaining solution can outperform TDM in certain scenarios.

Abstract

This work considers coordination and bargaining between two selfish users over a Gaussian interference channel using game theory. The usual information theoretic approach assumes full cooperation among users for codebook and rate selection. In the scenario investigated here, each selfish user is willing to coordinate its actions only when an incentive exists and benefits of cooperation are fairly allocated. To improve communication rates, the two users are allowed to negotiate for the use of a simple Han-Kobayashi type scheme with fixed power split and conditions for which users have incentives to cooperate are identified. The Nash bargaining solution (NBS) is used as a tool to get fair information rates. The operating point is obtained as a result of an optimization problem and compared with a TDM-based one in the literature.