On the feasibility of synchronous, retransmission-based cognitive networks

This paper presents a new, joint Markov chain model for the primary and secondary traffic in a cognitive radio network to assess the feasibility of opportunistic spectrum access for different operational scenarios, validated by extensive realistic Monte-Carlo simulations. Enhancing on the current literature, the generalized model allows for the consideration of a retransmission-based traffic as well as the presence of transmission queues for the primary user. The generalized model also allows for the investigation of the system behavior in the presence of imperfect sensing at the secondary users. The presented model is applicable for all primary user traffic models that use discrete-time Markov chains. An infinitely backlogged secondary user network is considered to investigate the maximum possible network utilization. The paper concludes that a percentile channel occupation of the primary user on its own is not always a sufficient metric to assess whether secondary transmission is feasible. It is shown that the interplay between primary network traffic characteristics, as well as the sensing frequency and probabilities of missed detection and false alarm for the secondary network detector are of primal importance for such feasibility claims. The results reveal that the preferred sensing frequency for the secondary users is a function of the primary user traffic pattern and that the commonly used frequency of sensing every transmission slot is not always optimal. The results also show that when sensing frequency is low, secondary utilization decreases with more bursty primary traffic, whereas the impact on primary utilization becomes less.