Open Access

ARTICLE

Analysis of Cognitive Radio for LTE and 5G Waveforms

Ramesh Ramamoorthy¹, Himanshu Sharma², A. Akilandeswari³, Nidhi Gour², Arun Kumar^4,*, Mehedi Masud⁵

1 Centre for Artificial Intelligence, Chennai Institute of Technology, Chennai, India
2 Department of Computer Science and Engineering, JECRC University, Jaipur, 303905, India
3 Institute of ECE, Saveetha School of Engineering, Chennai, India
4 Department of Electronics and Communication Engineering, JECRC University, Jaipur, 303905, India
5 Department of Computer Science, College of Computers and Information Technology, Taif University, 11099, Saudi Arabia

* Corresponding Author: Arun Kumar. Email:

Computer Systems Science and Engineering 2022, 43(3), 1207-1217. https://doi.org/10.32604/csse.2022.024749

Received 29 October 2021; Accepted 13 December 2021; Issue published 09 May 2022

Abstract

Spectrum sensing is one of the major concerns in reaching an efficient Quality of service (QOS) in the advanced mobile communication system. The advanced engineering sciences such as 5G, device 2 device communications (D2D), Internet of things (IoT), MIMO require a large spectrum for better service. Orthogonal frequency division multiplexing (OFDM) is not a choice in advanced radio due to the Cyclic Prefix (CP), wastage of the spectrum, and so on. Hence, it is important to explore the spectral efficient advanced waveform techniques and combine a cognitive radio (CR) with the 5G waveform to sense the idle spectrum, which overcomes the spectrum issue. The demand for spectrum is ever increasing; however, spectrum is limited and is an acutely scarce resource. To alleviate the issue, techniques like Cognitive Radios (CR) have been devised. However, such techniques are non-standardized, and many variations of CR algorithms have been tried and tested. This paper details the several spectrum sensing methods tailored for CR. We explain the benefits, uniqueness, and drawbacks of the various techniques to provide a comprehensive review of the scene, including all recent and novel techniques of CR. Finally, we provided experimental results for the performance of the CR for key 5G and beyond modulation techniques to elaborate the dependency of the CR techniques for CR applications and provide a competitive review of their performance. Experiments show that the CR integrated with NOMA shows better performance as compared with existing techniques.

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Keywords

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