Improving Spectrum Sensing for Cognitive Radio Network Using the Energy Detection with Entropy Method
Spectrum is one of the world’s most highly regulated and limited natural resources. Cognitive Radio (CR) is a cutting-edge technology that aims to solve the future spectrum shortage issue in wireless communication systems. CR is one of the most widely used methods for maximizing the use of the wirel...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Hindawi Limited
2022-01-01
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| Series: | Journal of Electrical and Computer Engineering |
| Online Access: | http://dx.doi.org/10.1155/2022/2656797 |
| _version_ | 1798001761216102400 |
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| author | Mustefa Badri Usman Ram Sewak Singh Satyasis Mishra Davinder Singh Rathee |
| author_facet | Mustefa Badri Usman Ram Sewak Singh Satyasis Mishra Davinder Singh Rathee |
| author_sort | Mustefa Badri Usman |
| collection | DOAJ |
| description | Spectrum is one of the world’s most highly regulated and limited natural resources. Cognitive Radio (CR) is a cutting-edge technology that aims to solve the future spectrum shortage issue in wireless communication systems. CR is one of the most widely used methods for maximizing the use of the wireless spectrum. Spectrum sensing is a critical step in discovering spectrum gaps in CR. Matching filter detection, energy detection (ED), cyclostationary detection, correlation coefficient detection, and wavelet detection are some of the frequency band sensing techniques. ED has received the most attention from many researchers because of its convenience and low computation complexity. However, noise instability, or the random and unavoidable variation of noise that exists in any communication link, greatly decreases the output of ED, especially whenever the signal-to-noise ratio (SNR) is poor. As a result, this research provides an exciting spectrum sensing option known as the energy detection with entropy method technique. In contrast to conventional ED, the proposed energy detection with entropy method offers better sensing performance in low SNR circumstances. According to simulation results, the proposed method has a significant performance improvement of about 18.58% when compared to CED at a given SNR of −18 dB. |
| first_indexed | 2024-04-11T11:41:18Z |
| format | Article |
| id | doaj.art-83a617de30df46ec84a301d4fa492717 |
| institution | Directory Open Access Journal |
| issn | 2090-0155 |
| language | English |
| last_indexed | 2024-04-11T11:41:18Z |
| publishDate | 2022-01-01 |
| publisher | Hindawi Limited |
| record_format | Article |
| series | Journal of Electrical and Computer Engineering |
| spelling | doaj.art-83a617de30df46ec84a301d4fa4927172022-12-22T04:25:48ZengHindawi LimitedJournal of Electrical and Computer Engineering2090-01552022-01-01202210.1155/2022/2656797Improving Spectrum Sensing for Cognitive Radio Network Using the Energy Detection with Entropy MethodMustefa Badri Usman0Ram Sewak Singh1Satyasis Mishra2Davinder Singh Rathee3Department of Electronics and Communication EngineeringDepartment of Electronics and Communication EngineeringDepartment of Electronics and Communication EngineeringDepartment of Electronics and Communication EngineeringSpectrum is one of the world’s most highly regulated and limited natural resources. Cognitive Radio (CR) is a cutting-edge technology that aims to solve the future spectrum shortage issue in wireless communication systems. CR is one of the most widely used methods for maximizing the use of the wireless spectrum. Spectrum sensing is a critical step in discovering spectrum gaps in CR. Matching filter detection, energy detection (ED), cyclostationary detection, correlation coefficient detection, and wavelet detection are some of the frequency band sensing techniques. ED has received the most attention from many researchers because of its convenience and low computation complexity. However, noise instability, or the random and unavoidable variation of noise that exists in any communication link, greatly decreases the output of ED, especially whenever the signal-to-noise ratio (SNR) is poor. As a result, this research provides an exciting spectrum sensing option known as the energy detection with entropy method technique. In contrast to conventional ED, the proposed energy detection with entropy method offers better sensing performance in low SNR circumstances. According to simulation results, the proposed method has a significant performance improvement of about 18.58% when compared to CED at a given SNR of −18 dB.http://dx.doi.org/10.1155/2022/2656797 |
| spellingShingle | Mustefa Badri Usman Ram Sewak Singh Satyasis Mishra Davinder Singh Rathee Improving Spectrum Sensing for Cognitive Radio Network Using the Energy Detection with Entropy Method Journal of Electrical and Computer Engineering |
| title | Improving Spectrum Sensing for Cognitive Radio Network Using the Energy Detection with Entropy Method |
| title_full | Improving Spectrum Sensing for Cognitive Radio Network Using the Energy Detection with Entropy Method |
| title_fullStr | Improving Spectrum Sensing for Cognitive Radio Network Using the Energy Detection with Entropy Method |
| title_full_unstemmed | Improving Spectrum Sensing for Cognitive Radio Network Using the Energy Detection with Entropy Method |
| title_short | Improving Spectrum Sensing for Cognitive Radio Network Using the Energy Detection with Entropy Method |
| title_sort | improving spectrum sensing for cognitive radio network using the energy detection with entropy method |
| url | http://dx.doi.org/10.1155/2022/2656797 |
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