Cooperative spectrum sensing for cognitive radio networks under limited time constraints

User cooperation for spectrum sensing in cognitive radios has been proposed in order to improve the overall performance by mitigating multi-path fading and shadowing experienced by the users. However, user cooperation results in high energy consumption, extra time for results exchange, as well as delay and security risks. In this paper, we investigate the effects of cooperative spectrum sensing (CSS) on energy consumption and achievable performance. Our analysis is based on a limited time resources assumption. This implies that the time resources dedicated for CSS process are limited and shared between spectrum sensing and results reporting, which depend on the number of sensing users. Our results show that cooperation among large number of users not only causes high energy consumption, but it also degrades the performance. Motivated by these considerations, the number of sensing users is optimized for different setups: throughput maximization, energy consumption minimization, and energy efficiency maximization. The optimal number of the sensing users is computed in a closed-form for both throughput maximization and energy minimization setups, while a simple iterative algorithm is proposed for obtaining the optimal number of sensing users for maximizing energy efficiency. Moreover, a novel energy efficient approach is presented that is able to significantly improve energy efficiency without degrading achievable throughput.