A Cooperative Bayesian Nonparametric Framework for Primary User Activity Monitoring in Cognitive Radio Networks

Abstract

This paper introduces a novel approach that enables a number of cognitive radio devices that are observing the availability pattern of a number of primary users (PUs), to cooperate and use Bayesian nonparametric techniques to estimate the distributions of the PUs' activity pattern. To address this problem, a coalitional game is formulated between the cognitive devices and an algorithm for cooperative coalition formation is proposed. It is shown that the proposed coalition formation algorithm allows the cognitive nodes that are experiencing a similar behavior from some PUs to self-organize into disjoint, independent coalitions. Inside each coalition, the cooperative cognitive nodes use Bayesian nonparametric techniques so as to improve the accuracy of the estimated PUs' activity distributions. Simulation results show that the proposed algorithm significantly improves the estimates of the PUs' activity patterns.