Utility Constrained Energy Minimization In Aloha Networks

TL;DR

This paper introduces a convex optimization approach to optimize transmission probabilities in Aloha networks, improving energy efficiency, fairness, and network lifetime through a utility constrained energy minimization framework.

Contribution

It presents a novel convex optimization model for energy minimization with utility constraints and applies SQP to optimize transmission probabilities in Aloha networks.

Findings

Achieves improved fairness among nodes

Reduces overall energy consumption

Extends network lifetime

Abstract

In this paper we consider the issue of energy efficiency in random access networks and show that optimizing transmission probabilities of nodes can enhance network performance in terms of energy consumption and fairness. First, we propose a heuristic power control method that improves throughput, and then we model the Utility Constrained Energy Minimization (UCEM) problem in which the utility constraint takes into account single and multi node performance. UCEM is modeled as a convex optimization problem and Sequential Quadratic Programming (SQP) is used to find optimal transmission probabilities. Numerical results show that our method can achieve fairness, reduce energy consumption and enhance lifetime of such networks.