A Game-Theoretic Approach to Energy-Efficient Resource Allocation in Device-to-Device Underlay Communications

TL;DR

This paper introduces a game-theoretic framework for energy-efficient resource allocation in D2D underlay communications, addressing interference and battery constraints to optimize individual device energy efficiency.

Contribution

It proposes a distributed algorithm based on nonlinear fractional programming that finds the Nash equilibrium for energy-efficient resource allocation in D2D networks.

Findings

The algorithm converges to the Nash equilibrium.

It characterizes the tradeoff between energy efficiency and spectral efficiency.

Provides closed-form expressions for EE and SE gaps.

Abstract

Despite the numerous benefits brought by Device-to-Device (D2D) communications, the introduction of D2D into cellular networks poses many new challenges in the resource allocation design due to the co-channel interference caused by spectrum reuse and limited battery life of User Equipments (UEs). Most of the previous studies mainly focus on how to maximize the Spectral Efficiency (SE) and ignore the energy consumption of UEs. In this paper, we study how to maximize each UE's Energy Efficiency (EE) in an interference-limited environment subject to its specific Quality of Service (QoS) and maximum transmission power constraints. We model the resource allocation problem as a noncooperative game, in which each player is self-interested and wants to maximize its own EE. A distributed interference-aware energy-efficient resource allocation algorithm is proposed by exploiting the properties of the nonlinear fractional programming. We prove that the optimum solution obtained by the proposed algorithm is the Nash equilibrium of the noncooperative game. We also analyze the tradeoff between EE and SE and derive closed-form expressions for EE and SE gaps.