Energy-Efficient Power Control: A Look at 5G Wireless Technologies

TL;DR

This paper introduces energy-efficient power control algorithms for 5G wireless networks, considering minimum-rate constraints and general SINR expressions, with centralized and decentralized solutions validated through numerical analysis.

Contribution

It develops guaranteed-convergence centralized algorithms and game-theoretic decentralized methods for energy efficiency maximization in 5G networks with practical constraints.

Findings

Algorithms converge to KKT points with low complexity

Feasibility conditions for power control are derived

Numerical results compare network-centric and user-centric approaches

Abstract

This work develops power control algorithms for energy efficiency (EE) maximization (measured in bit/Joule) in wireless networks. Unlike previous related works, minimum-rate constraints are imposed and the signal-to-interference-plus-noise ratio takes a more general expression, which allows one to encompass some of the most promising 5G candidate technologies. Both network-centric and user-centric EE maximizations are considered. In the network-centric scenario, the maximization of the global EE and the minimum EE of the network are performed. Unlike previous contributions, we develop centralized algorithms that are guaranteed to converge, with affordable computational complexity, to a Karush-Kuhn-Tucker point of the considered non-convex optimization problems. Moreover, closed-form feasibility conditions are derived. In the user-centric scenario, game theory is used to study the equilibria of the network and to derive convergent power control algorithms, which can be implemented in a fully decentralized fashion. Both scenarios above are studied under the assumption that single or multiple resource blocks are employed for data transmission. Numerical results assess the performance of the proposed solutions, analyzing the impact of minimum-rate constraints, and comparing the network-centric and user-centric approaches.