Distributed Interference-Aware Energy-Efficient Resource Allocation for Device-to-Device Communications Underlaying Cellular Networks

TL;DR

This paper presents a distributed algorithm for energy-efficient resource allocation in D2D underlay cellular networks, addressing interference and power constraints to improve device energy efficiency.

Contribution

It introduces a novel game-theoretic, distributed approach for maximizing energy efficiency under interference and QoS constraints in D2D communications.

Findings

Algorithm effectively improves energy efficiency of UEs.

Simulation results confirm convergence and performance gains.

Approach handles non-convex optimization via fractional programming.

Abstract

The introduction of device-to-device (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). In this paper, we propose a distributed interference-aware energy-efficient resource allocation algorithm to maximize each UE's energy efficiency (EE) 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. The formulated EE maximization problem is a non-convex problem and is transformed into a convex optimization problem by exploiting the properties of the nonlinear fractional programming. An iterative optimization algorithm is proposed and verified through computer simulations.