Globally Optimal Energy-Efficient Power Control and Receiver Design in Wireless Networks

TL;DR

This paper develops a framework for globally optimal energy-efficient power control and receiver design in wireless networks, addressing non-convex problems and proposing practical suboptimal solutions with lower complexity.

Contribution

It introduces a novel monotonic framework leveraging fractional programming for global optimality and a sequential optimization approach for computationally feasible suboptimal solutions.

Findings

The framework achieves global optimality in practical scenarios.

Sequential fractional programming provides near-optimal solutions with lower complexity.

Numerical results validate the effectiveness of the proposed methods.

Abstract

The characterization of the global maximum of energy efficiency (EE) problems in wireless networks is a challenging problem due to the non-convex nature of investigated problems in interference channels. The aim of this work is to develop a new and general framework to achieve globally optimal solutions. First, the hidden monotonic structure of the most common EE maximization problems is exploited jointly with fractional programming theory to obtain globally optimal solutions with exponential complexity in the number of network links. To overcome this issue, we also propose a framework to compute suboptimal power control strategies characterized by affordable complexity. This is achieved by merging fractional programming and sequential optimization. The proposed monotonic framework is used to shed light on the ultimate performance of wireless networks in terms of EE and also to benchmark the performance of the lower-complexity framework based on sequential programming. Numerical evidence is provided to show that the sequential fractional programming framework achieves global optimality in several practical communication scenarios.