Distributed user matching and power allocation in cooperative cognitive networks

Cooperative transmission between Primary licensed Users (PUs) and Secondary unlicensed Users (SUs) in cognitive radio networks aims to improve the probability of transmission opportunities. This paper investigates the problem of finding the best match for each PU among a set of available SUs and allocating optimum power to them. The proposed method in this paper works only with local information, due to the unavailability of global Channel State Information (CSI). Using a graph theoretical approach and applying principle of contract theory lead us to a distributed solution that works under asymmetry of information. Simulation results are carried out to evaluate the network throughput versus different number of PUs and SUs. We finally compare the performance results with a benchmark scenario.