Hybrid Feedback-Based Access Scheme for Cognitive Radio Systems

In this paper, a cognitive radio system is studied in which the secondary user (SU) leverages the primary user (PU) channel quality indicator feedback (CQI) and the PU automatic repeat request (ARQ). The SU randomly accesses the PU channel with access probabilities based on its spectrum sensing outcome and the PU feedbacks. The SU's access probabilities are selected though an optimization problem with the objective to maximize the SU's throughput while ensuring the stability of the PU's packet queue. This system is modeled using a multi-dimensional Markov chain. This model enabled us to derive a closed-form expression for the SU's throughput, which is used in the throughput maximization problem. The proposed scheme is shown to improve the SU service rate compared to the system where no PU feedback is exploited by the SU, the system where the SU utilizes only the PU CQI feedback, and the system where the SU utilizes only the PU ARQ feedback.