Open Access

ARTICLE

Power Optimized Multiple-UAV Error-Free Network in Cognitive Environment

Shakti Raj Chopra¹, Parulpreet Singh¹, Ahmed Alhussen^2,*, Nitin Mittal³, MohdAnul Haq⁴

1 School of Electronics and Electrical Engineering, Lovely Professional University, Phagwara, Punjab, 144411, India
2 Department of Computer Engineering, College of Computer and Information Sciences, Majmaah University, Al-Majmaah, 11952, Saudi Arabia
3 University Centre for Research and Development, Chandigarh University, Mohali, Punjab, 140413, India
4 Department of Computer Science, College of Computer and Information Sciences, Majmaah University, Al-Majmaah, 11952, Saudi Arabia

* Corresponding Author: Ahmed Alhussen. Email:

Computers, Materials & Continua 2023, 75(2), 3189-3201. https://doi.org/10.32604/cmc.2023.030061

Received 17 March 2022; Accepted 31 May 2022; Issue published 31 March 2023

Abstract

Many extensive UAV communication networks have used UAV cooperative control. Wireless networking services can be offered using unmanned aerial vehicles (UAVs) as aerial base stations. Not only is coverage maximization, but also better connectivity, a fundamental design challenge that must be solved. The number of applications for unmanned aerial vehicles (UAVs) operating in unlicensed bands is fast expanding as the Internet of Things (IoT) develops. Those bands, however, have become overcrowded as the number of systems that use them grows. Cognitive Radio (CR) and spectrum allocation approaches have emerged as a potential approach for resolving spectrum scarcity in wireless networks, and hence as technological solutions for future generations, from this perspective. As a result, combining CR with UAVs has the potential to give significant benefits for large-scale UAV deployment. The paper examines existing research on the subject of UAV covering and proposes a multi-UAV cognitive-based error-free model for energy-efficient communication. Coverage maximization, power control, and enhanced connection quality are the three steps of the proposed model. To satisfy the desired signal-to-noise ratio, the covering zone efficacy is investigated as a function of the distance among UAVs stationed in a specific geographic region depending on multiple deployment configurations like as rural, suburban, and urban macro deployment scenarios of the ITU-R M.2135 standard (SNR).

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Keywords

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