New Algorithms for Maximizing Cellular Wireless Network Energy Efficiency

TL;DR

This paper introduces novel algorithms for optimizing energy efficiency in cellular wireless networks by addressing power allocation, interference management, and QoS constraints, demonstrating significant performance improvements over benchmarks.

Contribution

The paper develops a comprehensive framework using fractional programming and dual decomposition for energy-efficient power allocation in multi-cell networks, including single-tier and two-tier systems.

Findings

Algorithms outperform benchmarks by 2.7 times in energy efficiency

Closed-form power update expressions derived from multi-level water-filling

Framework extends to two-tier networks with QoS constraints

Abstract

In this paper, we aim to maximize the energy efficiency of cellular wireless networks. Specifically, we address the power allocation problem in multi-cell multi-carrier systems. Considering realistic base station power consumption models, we formulate a network-wide energy efficiency maximization problem. Using tools from fractional programming, we cast this problem in the framework of bi-criterion optimization where rate maximization and power minimization are weighted accordingly. Interference pricing mechanism is applied to reduce the intercell interference and to achieve a higher network performance. We decompose the main problem into subproblems via dual decomposition. These subproblems are independently solved per sector using limited information exchange between base stations. We first derive our expressions and present algorithms for the single-tier networks. Then, we extend our analysis to two-tier networks where picocell base stations are deployed to improve the network performance and reduce the link distances. Lastly, we extend our framework and include the quality-of-service constraints.We obtain closed-form expressions for the power level updates which are determined by the multi-level water-filling algorithm, or, as it is sometimes called as, the modified waterfilling algorithm. Based on our simulation results, we demonstrate that the proposed algorithms can outperform the benchmark approaches in terms of energy efficiency by a factor of 2.7.