Machine Learning and Cognitive Computing for Mobile Communications and Wireless Networks

5Spectrum Sensing and Allocation Schemes for Cognitive Radio

Amrita Rai¹*, Amit Sehgal¹, T.L. Singal² and Rajeev Agrawal¹

¹ ECE Dept., G. L. Bajaj Institute of Technology and Management, Greater Noida, India

² Chitkara University, Rajpura, India

Abstract

In wireless communication system, the radio spectrum is one of the biggest resource constraints with limited availability in nature. To regulate the use of this limited resource, Fixed Spectrum Access policy (FSA) was adopted by spectrum regulators. To overcome the limitation due to scarcity of spectrum and optimize spectrum utilization, Dynamic Spectrum Access (DSA) was proposed. In DSA, users are categorized as Primary Users (PUs) and Secondary Users (SUs). Incorporation of cognizance about the available spectrum into radio communication devices lead to the evolution of Cognitive Radio Networks (CRN) and radio devices with this capability are called Cognitive Radios (CR). To access radio spectrum using cognitive intelligence, several access models have been proposed for the CRs such as Concurrent Spectrum Access (CSA), Opportunistic Spectrum Access (OSA) and Hybrid Spectrum Access (HAS). In most cases, the CR user needs to frequently observe the spectrum to identify the spectrum holes. Such mechanism is known as Spectrum Sensing. Several techniques of spectrum sensing have been developed, broadly categorized into Direct Sensing and Indirect Sensing. The implementation of these techniques along with challenges faced in their ...