A Survey on Soft Computing Techniques for Spectrum Sensing in a Cognitive Radio Network
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SURVEY ARTICLE
A Survey on Soft Computing Techniques for Spectrum Sensing in a Cognitive Radio Network Geoffrey Eappen1 · T Shankar1 Received: 11 June 2020 / Accepted: 7 October 2020 © Springer Nature Singapore Pte Ltd 2020
Abstract The need for faster wireless connectivity is increasing rapidly in all the sectors of the technologies. Whether it is a patient monitoring system, military application, entertainment services, streaming services, or global stock markets, there is a tremendous increase in the need for enhanced wireless telecommunication services. The wireless telecommunication consumers rely on bulk data, and massive growth in the number of users has resulted in the spectrum congestion. To avoid such spectrum congestion and to satisfy the data hunger of the wireless telecommunication users, the possible solution is Cognitive Radio Network (CRN). A CRN, therefore, plays a significant role in the field of wireless communication, and an efficient spectrum sensing enhances the effectiveness of the CRN. In this paper, complete research carried out so far in the field of spectrum sensing for CRN is discussed. Different soft computing techniques (GA, PSO, ABC, ACO, FFA, FSS, Cuckoo Search, ANN, FIS, GFIS) are surveyed in this paper, along with a detailed comparative analysis between conventional and soft computing techniques for spectrum sensing. In addition to that, the challenges faced in the implementation of CRN and its requirements is also addressed. Different spectrum sensing elements and requirements are presented and road map of spectrum sensing with soft computing techniques towards 5G is discussed. Furthermore, the paper also suggests the future prospects, research challenges and open issues associated with soft computing techniques for spectrum sensing in CRN. Keywords Cognitive radio network · Spectrum sensing · Soft computing techniques · Metaheuristic techniques
Motivational Background The tremendous demand for wireless applications has lead to the enormous growth of wireless communication. The existing radio spectrum is a finite natural resource, and it is getting jampacked continuously. And with the advancement towards 5G, there is a 1000 times increase in the demand of the radio spectrum because of the rise in demand of higher capacity, higher spectral efficiency and higher connectivity [142]. Therefore, the requirement for a robust and flexible wireless communication has become more evident. The conventional approach via electromagnetic spectrum licensing and re-utilizing it was not manageable. It was rather static * T Shankar [email protected] Geoffrey Eappen [email protected] 1
Department of Communication Engineering, School of Electronics Engineering(SENSE), Vellore Institute of Technology (VIT), Vellore, India
and caused inefficient use of the available spectrum. This raised the need for efficient spectrum utilization, which creates possibilities for spectrum access dynamically, called dynamic spectrum access (DSA). Federal Communication Commission (FCC) published a repor
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