Cooperative Routing for Underlay Cognitive Radio Networks Using Mutual-Information Accumulation

Abstract

In underlay cognitive radio networks (CRNs), secondary users (SUs) have to dynamically control their transmit powers so that the interference to primary users (PUs) is tolerable. Under this constraint, SUs' data link usually suffers from either high error rate with limited transmission range or long end-to-end delay caused by multi-hop transmissions. To improve the performance of SUs, cooperative routing using mutual-information accumulation is introduced in CRNs for the first time in this paper. To be specific, the routing and resource allocation problem in underlay CRNs is investigated and is factored into two sub-problems, each of which can be solved efficiently. Furthermore, a distributed algorithm is introduced and simulation results show that both the centralized and distributed algorithms can reduce upto 77% of the end-to-end delay compared to the traditional multi-hop delay-optimal routing in CRNs. Finally, theoretical analysis on the end-to-end delay for a one-dimensional (1-D) network in the low signal-to-interference ratio (SIR) region is conducted. Both the analytical and simulation results show that mutual-information accumulation can significantly decrease the delay of underlay CRNs, especially in the scenario where PUs have a tight interference power constraint.