Energy-Efficient Spectrum Sharing in Relay-Assisted Cognitive Radio Systems

TL;DR

This paper proposes a distributed spectrum sharing approach for relay-assisted cognitive radio systems that achieves energy efficiency and Pareto optimality through a game-theoretic framework and simple gradient algorithms.

Contribution

It introduces a novel game-theoretic model with a unique Nash bargaining solution for energy-efficient spectrum sharing in relay-assisted systems.

Findings

Spectral efficiency can be significantly improved.

The proposed distributed algorithm converges to the Pareto-efficient solution.

Energy-efficient spectrum sharing is feasible with simple gradient updates.

Abstract

This work characterizes an important solution concept of a relevant spectrum game. Two energy-efficient sources communicating with their respective destination compete for an extra channel brought by a relay charging the used bandwidth through a pricing mechanism. This game is shown to possess a unique Nash bargaining solution, exploiting a time-sharing argument. This Pareto-efficient solution can be implemented by using a distributed optimization algorithm for which each transmitter uses a simple gradient-type algorithm and alternately updates its spectrum sharing policy. Typical numerical results show to what extent spectral efficiency can be improved in a system involving selfish energy-efficient sources.