Efficient Spectrum Sensing Pattern Using Intelligent Matrix in Cognitive Radio Network
I K. Leelarani, Divya Kumari · 2014
Cognitive radio (CR) can successfully deal with the growing demand and scarcity of the wireless spectrum. To exploit limited spectrum efficiently, CR technology allows unlicensed users to access licensed spectrum bands. Since licensed users have priorities to use the bands, the unlicensed users need to continuously monitor the licensed users’ activities to avoid interference and collisions. How to obtain reliable results of the licensed users’ activities is the main task for spectrum sensing. Based on the sensing results, the unlicensed users should adapt their transmit powers and access strategies to protect the licensed communications. One of the key effecting factors on the CR network throughput is the spectrum sensing sequence used by each secondary user. In this paper, secondary users’ throughput maximization through finding an appropriate sensing matrix (SM) is investigated. The proposed intelligent learning and optimization cycle, based on neural networks, finds the optimal sensing sequence for each secondary user without any prior knowledge about the wireless environment. The structure of the proposed scheme is discussed in detail, and its efficiencies are verified through numerical results.