Combination of spectrum sensing and allocation in cognitive radio networks based on compressive sampling

Spectrum sensing is an essential approach for the realization of cognitive radio. Cognitive users are expected to find available spectrum holes over a wide frequency range. However, sampling a wide bandwidth fast and accurately is a major technical challenge for the cognitive users due to their hardware limitations and limited power. Even though the spectrum holes have been detected successfully, it is still a challenge to allocate the spectrum holes over such a wide frequency range. Besides, the multi-user environment, as well as asynchronous sensing period of multiple cognitive users, makes it more difficult to detect and allocate the spectrum holes. Consequently, a combined mechanism of spectrum sensing and spectrum allocation based on compressive sampling is developed to overcome these challenges. Specifically, the spectrum sensing mechanism based on compressive sampling reduces the sampling rate effectively via exploring the sparseness of the received signal. Additionally, the spectrum allocation among the neighboring cognitive users is discussed as a constraint during the signal reconstruct process of the compressive spectrum sensing. Hence, both the spectrum sensing and the spectrum allocation are managed in this combined scheme, with the wide band detection and the multi-user problem both solved. A cooperative distributed algorithm is proposed for its implementation. The performance of the combined design is measured in the detect accuracy of the compressive spectrum sensing and the utilization efficiency of the spectrum allocation, which is demonstrated in the simulation.