Research Article Stage Spectrum Sensing Technique for Cognitive Radio Network Using Energy and Entropy Detection Mustefa Badri Usman , Ram Sewak Singh, and S Rajkumar Department of Electronics and Communication Engineering, School of Electrical Engineering and Computing, Adama Science and Technology University, P.O.Box:1888, Adama, Ethiopia Correspondence should be addressed to Mustefa Badri Usman; mustefabedri123@gmail.com Received 6 April 2022; Accepted 27 July 2022; Published 24 August 2022 Academic Editor: Jiafeng Zhou Copyright©2022MustefaBadriUsmanetal.isisanopenaccessarticledistributedundertheCreativeCommonsAttribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. eradiospectrumisoneoftheworld’smosthighlyregulatedandlimitednaturalresources.enumberofwirelessdeviceshas increased dramatically in recent years, resulting in a scarcity of available radio spectrum due to static spectrum allocation. However, many studies on static allocation show that the licensed spectrum bands are underutilized. Cognitive radio has been considered as a viable solution to the issues of spectrum scarcity and underutilization. Spectrum sensing is an important part in cognitive radio for detecting spectrum holes. To detect the availability or unavailability of primary user signals, many spectrum sensingtechniquessuchasmatchedfilterdetection,cyclostationaryfeaturedetection,andenergydetectionhavebeendeveloped. Energy detection has gained significant attention from researchers because of its ease of implementation, fast sensing time, and low computational complexity. Conventional detectors’ performance degrades rapidly at low SNR due to their sensitivity to the uncertaintyofnoise.Tomitigatenoiseuncertainty,Shannon,Tsallis,Kapur,andRenyientropy-baseddetectionhasbeenusedin this study, and their performances are compared to choose the best performer. According to the comparison results, the Renyi entropyoutperformsotherentropymethods.Inthisstudy,two-stagespectrumsensingisproposedusingenergydetectionasthe coarsestageandRenyientropy-baseddetectionasthefinestagetoimprovetheperformanceofsingle-stagedetectiontechniques. Furthermore, the performance comparison among conventional energy detection, entropy-based detection, and the proposed two-stagetechniquesoverAWGNchannelareperformed.eparameterssuchasprobabilityofdetection,falsealarmprobability, miss-detectionprobability,andreceiveroperatingcharacteristicscurveareusedtoevaluatetheperformanceofspectrumsensing techniques.Ithasbeenshownthattheproposedtwo-stagesensingtechniqueoutperformssingle-stageenergydetectionandRenyi entropy-based detection by 11dB and 1dB, respectively. 1. Introduction Nowadays,wirelesscommunicationtechnologiesarerapidly evolving to accommodate people’s demands and require- ments, which are changing exponentially [1]. As wireless technology advances, the need for spectrum resources is increasing, which has resulted in a scarcity of spectrum due toastaticspectrumallocationpolicy.Onthecontrary,recent studies on current spectrum allocation show the underuti- lizationoftheallocatedspectrumtothelicenseduseratany specific location and time. Cognitive radio has been iden- tified as a possible technology for addressing the issues of spectral scarcity and underutilization [2]. Cognitiveradio(CR)isacriticaltechnologythatallowsfor more efficient use of restricted and inefficiently utilized fre- quency bands using an opportunistic manner [1]. CR has four main tasks/functions: spectrum sensing (SS), spectrum deci- sion/management, spectrum sharing/allocation, and spectrum mobility/handoff. SS is used to determine the portion of the spectrum that are vacant and senses the presence of licensed primary users (PUs). Spectrum management selects the most suitable vacant spectrum holes among the detected ones. e goal of spectrum sharing is to evenly or fairly distribute the spectrum holes among the secondary users (SUs). Spectrum mobility aims to maintain communication while transitioning to better spectrum holes [3, 4]. Hindawi Wireless Power Transfer Volume 2022, Article ID 7941978, 10 pages https://doi.org/10.1155/2022/7941978