Sequential Channel Sensing in Cognitive Small Cell Based on User Traffic

In this letter, we study the problem of sequential channel sensing in cognitive small cell (CSC), taking into account the effect of data traffics of offload users (OUs). To capture the characteristics of practical network traffic, we propose a general OU traffic model, which includes non-bursty Poisson process and bursty ON/OFF Pareto process. We do not assume that the OUs always have packets to transmit; instead, we use the actual data transmitted per second as the achievable traffic throughput. Furthermore, we formulate a sensing order optimization problem based on the traffic model. We jointly consider channel capacity, idle probability, heterogeneous sensing time and OU traffic in getting the optimal channel sensing order. Simulation results show that the proposed approach outperforms existing methods.