Coalition Formation for Throughput Enhancement via One-Sided Matching Theory

Abstract

Recently there have been numerous studies exploring the benefits of the coalition formation in a cognitive radio network and it has been shown that coalition formation tends to improve the performance of cognitive radio networks. In this paper, we use the concepts from matching theory to form coalitions of varying size among cognitive radio users for cooperative spectrum sensing under target detection probability constraint. In the proposed model, we make use of one-sided matching theory to develop an algorithm for the cognitive radios to form coalitions of varying the size to improve their individual gains (.e.g. throughput and the probability of false alarm). We prove that the proposed algorithm leads to stable coalition formation in the cognitive radio network and show using simulations that the proposed matching algorithm for coalition formation yields significant gains in term of reduced false alarm probability and increased throughput per cognitive radio user as compared to the non-cooperative scenario.