Effect of spectrum sensing overhead on performance for cognitive radio networks with channel bonding

Abstract

In cognitive radio networks, secondary spectrum users detect available frequency channels by spectrum sensing. In general, the sensing time is communication overhead, and affects system's performance. In this paper, we theoretically consider the effect of sensing overhead on the system performance for cognitive radio networks with channel bonding. Specifically, we model the system with a multidimensional continuous-time Markov chain whose state is defined by the numbers of primary users, secondary users, and sensing users. The blocking probability, the forced termination probability and the throughput are derived. The analysis is validated by Monte Carlo simulation. Numerical examples show that the forced termination probability is not affected by sensing overhead, while the blocking probability and the throughput degrade with the increase in the sensing time. It is also shown that the optimal number of bonded sub-channels for the throughput performance significantly depends on the offered load from primary users.