Utility driven cooperative spectrum sensing scheduling for heterogeneous multi-channel cognitive radio networks

Owing to the spectrum scarcity and energy constrained devices in wireless networks arises the demand for an efficient spectrum sensing technique which improves both sensing performance and energy efficiency for cognitive radio networks. This paper proposes a cooperative spectrum sensing scheduling (CSSS) scheme for heterogeneous multi-channel cognitive radio networks with the objective of finding an efficient sensing schedule to enhance network utility while keeping the energy depletion at a lower level. We start with formulating the CSSS problem as an optimization problem, which captures both the energy-performance and performance opportunity trade-offs. We prove that the formulated CSSS problem is non-deterministic polynomial hard (NP-hard). To tackle the higher computational complexity of the formulated problem, we propose a greedy-based heuristic solution, which produces a sub-optimal result in polynomial time. To reduce energy consumption during spectrum sensing, we make secondary users to adaptively decide on the sensing duration based on the received signal-to-noise ratio (SNR), where higher SNR leads to lower sensing duration and vice-versa. For enhancing network throughput, SUs sense multiple channels in the order of their suitability for data transmission to explore as many numbers of channels as possible within the permitted maximum sensing time. We consider erroneous nature of reporting channel to make the cooperative decision robust against errors during reporting. Simulation based results show the effectiveness of the proposed scheme in terms of utility, energy overhead, and the number of channels explored compared to similar schemes from literature.