# Energy Efficient Joint Resource Allocation and Power Control for D2D Communications

## TL;DR

This paper presents a novel iterative scheme for joint resource allocation and power control in D2D communications, significantly improving energy efficiency by transforming a complex fractional optimization problem into a manageable two-layer approach.

## Contribution

It introduces a new two-layer optimization method that decouples resource allocation and power control for energy-efficient D2D communications, utilizing fractional programming and network flow techniques.

## Key findings

- Achieves notable energy efficiency improvements in simulations.
- Effectively decouples resource allocation and power control tasks.
- Demonstrates convergence and optimality of the proposed scheme.

## Abstract

In this paper, joint resource allocation and power control for energy efficient device-to-device (D2D) communications underlaying cellular networks are investigated. The resource and power are optimized for maximization of the energy efficiency (EE) of D2D communications. Exploiting the properties of fractional programming, we transform the original nonconvex optimization problem in fractional form into an equivalent optimization problem in subtractive form. Then, an efficient iterative resource allocation and power control scheme is proposed. In each iteration, part of the constraints of the EE optimization problem is removed by exploiting the penalty function approach. We further propose a novel two-layer approach which allows to find the optimum at each iteration by decoupling the EE optimization problem of joint resource allocation and power control into two separate steps. In the first layer, the optimal power values are obtained by solving a series of maximization problems through root-finding with or without considering the loss of cellular users' rates. In the second layer, the formulated optimization problem belongs to a classical resource allocation problem with single allocation format which admits a network flow formulation so that it can be solved to optimality. Simulation results demonstrate the remarkable improvements in terms of EE by using the proposed iterative resource allocation and power control scheme.