Distributed back-pressure scheduling with opportunistic routing in cognitive radio networks

Abstract

A challenging problem in cognitive radio networks (CRNs) is to design a throughput efficient routing and scheduling algorithm for end-to-end communications between secondary users (SUs) in a distributed manner. Due to the opportunistic nature of CRN routing, we consider a framework with randomized path selection in this paper. Motivated by the back-pressure scheduling policy, we adopt the differential queue backlog as the routing metric to achieve throughput efficiency. Moreover, we demonstrate the sufficient condition for our framework to achieve throughput optimality by analyzing the Lyapunov drift. We further propose a distributed medium access control algorithm that can approximately satisfy the required condition when the transmission attempt probability is low. The performance of our proposed scheme is evaluated in a simulation platform, and the evaluation results verify the effectiveness of our distributed scheme.