Hybrid ARQ-CQI Feedback-Based Access Scheme in Cognitive Radio Networks

Abstract

In this paper, we consider a cognitive radio (CR) network where the primary network’s feedback information is utilized to develop an access scheme for the secondary network to exploit the underutilized primary spectrum resources. Secondary users (SUs) identify the spectrum opportunities by sensing the spectrum for primary users (PUs) activities and by listening to the PUs feedback. The feedback signals monitored in this research work are the channel quality indicator (CQI) and automatic repeat request (ARQ) available in the PUs network. For detecting the PUs activities, SUs employ soft energy sensing, where SUs access the PUs’ channel with access probabilities that are based on the sensed PUs’ energy level. The access probabilities are optimized to maximize the SUs service rate while maintaining the PUs queues’ stability. The system is modeled as a three-dimensional Markov chain (MC) that captures the number of packets in the PUs queues and the state of the two observed PUs’ feedback signals. The performance of the system is evaluated by deriving the SUs service rate and the average PUs packet delay. We compare the performance of the proposed system with other baseline systems utilizing different types of PUs’ feedback signals. Results reveal the improvement in the SUs service rate and the PUs’ delay of the proposed system compared to the baseline systems. This improvement is mainly due to the fact that in our proposed system SUs have access to extra information, in terms of PUs feedback, as compared to other systems. Therefore, SUs in our proposed system can have better inference on the PUs’ activities; thus more collisions between the PUs and the SUs can be avoided, resulting in significant performance gains in terms of SUs’ throughput and PUs’ average delay.Part of this work was published in [1] .