Evaluation of the Effects of Compressive Spectrum Sensing Parameters on Primary User Behavior Estimation
As the Internet of Things (IoT) technology is being deployed, the demand for radio spectrum is increasing. Cognitive radio (CR) is one of the most promising solutions to allow opportunistic spectrum access for IoT secondary users through utilizing spectrum holes resulting from the underutilization o...
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| Format: | Article |
| Language: | English |
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Port Said University
2021-09-01
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| Series: | Port Said Engineering Research Journal |
| Subjects: | |
| Online Access: | https://pserj.journals.ekb.eg/article_185492_6176504776a54398add4c9b6a9ae78b4.pdf |
| _version_ | 1797653393603297280 |
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| author | Ahmed Tawfik Mohamed Abdelkader Sherif Abuelenin |
| author_facet | Ahmed Tawfik Mohamed Abdelkader Sherif Abuelenin |
| author_sort | Ahmed Tawfik |
| collection | DOAJ |
| description | As the Internet of Things (IoT) technology is being deployed, the demand for radio spectrum is increasing. Cognitive radio (CR) is one of the most promising solutions to allow opportunistic spectrum access for IoT secondary users through utilizing spectrum holes resulting from the underutilization of frequency spectrum. A CR needs to frequently sense the spectrum to avoid interference with primary users (PUs). Compressive spectrum sensing techniques have been gaining increasing interest in wideband spectrum sensing, as they reduce the need for high-rate analog-to-digital converters, reducing the complexity and energy requirements of the CR. In order to enhance spectrum sensing performance, researchers proposed to incorporate PU spectrum usage information into the process of spectrum sensing. Spectrum usage information can be obtained through pilot signals, geo-locational databases or through evaluation of previous spectrum sensing results. In this paper, we are studying the effects of compressive sensing parameters namely compression ratio, sensing period, and sensing duration on the estimation of primary user behavior statistics. We achieved an accurate estimation of the primary user's behavior while saving 40% of the sampling rate by using compressive spectrum sensing compared to traditional spectrum sensing with Nyquist rate sampling. |
| first_indexed | 2024-03-11T16:44:00Z |
| format | Article |
| id | doaj.art-178ed06c6c8d48bbba097da3a63f2712 |
| institution | Directory Open Access Journal |
| issn | 1110-6603 2536-9377 |
| language | English |
| last_indexed | 2024-03-11T16:44:00Z |
| publishDate | 2021-09-01 |
| publisher | Port Said University |
| record_format | Article |
| series | Port Said Engineering Research Journal |
| spelling | doaj.art-178ed06c6c8d48bbba097da3a63f27122023-10-23T05:57:50ZengPort Said UniversityPort Said Engineering Research Journal1110-66032536-93772021-09-0125211211910.21608/pserj.2021.64521.1094185492Evaluation of the Effects of Compressive Spectrum Sensing Parameters on Primary User Behavior EstimationAhmed Tawfik0Mohamed Abdelkader1Sherif Abuelenin2Electrical Engineering Department, Faculty of Engineering, Port Said University, Port Said, EgyptElectrical Engineering Department, Faculty of Engineering, Port Said University, Port Said, Egypt.Dept. of Electrical Engineering, Port Said University, Port Fouad, Port Said 42526, EgyptAs the Internet of Things (IoT) technology is being deployed, the demand for radio spectrum is increasing. Cognitive radio (CR) is one of the most promising solutions to allow opportunistic spectrum access for IoT secondary users through utilizing spectrum holes resulting from the underutilization of frequency spectrum. A CR needs to frequently sense the spectrum to avoid interference with primary users (PUs). Compressive spectrum sensing techniques have been gaining increasing interest in wideband spectrum sensing, as they reduce the need for high-rate analog-to-digital converters, reducing the complexity and energy requirements of the CR. In order to enhance spectrum sensing performance, researchers proposed to incorporate PU spectrum usage information into the process of spectrum sensing. Spectrum usage information can be obtained through pilot signals, geo-locational databases or through evaluation of previous spectrum sensing results. In this paper, we are studying the effects of compressive sensing parameters namely compression ratio, sensing period, and sensing duration on the estimation of primary user behavior statistics. We achieved an accurate estimation of the primary user's behavior while saving 40% of the sampling rate by using compressive spectrum sensing compared to traditional spectrum sensing with Nyquist rate sampling.https://pserj.journals.ekb.eg/article_185492_6176504776a54398add4c9b6a9ae78b4.pdfcognitive radiocompressive spectrum sensingprimary user activity statistics |
| spellingShingle | Ahmed Tawfik Mohamed Abdelkader Sherif Abuelenin Evaluation of the Effects of Compressive Spectrum Sensing Parameters on Primary User Behavior Estimation Port Said Engineering Research Journal cognitive radio compressive spectrum sensing primary user activity statistics |
| title | Evaluation of the Effects of Compressive Spectrum Sensing Parameters on Primary User Behavior Estimation |
| title_full | Evaluation of the Effects of Compressive Spectrum Sensing Parameters on Primary User Behavior Estimation |
| title_fullStr | Evaluation of the Effects of Compressive Spectrum Sensing Parameters on Primary User Behavior Estimation |
| title_full_unstemmed | Evaluation of the Effects of Compressive Spectrum Sensing Parameters on Primary User Behavior Estimation |
| title_short | Evaluation of the Effects of Compressive Spectrum Sensing Parameters on Primary User Behavior Estimation |
| title_sort | evaluation of the effects of compressive spectrum sensing parameters on primary user behavior estimation |
| topic | cognitive radio compressive spectrum sensing primary user activity statistics |
| url | https://pserj.journals.ekb.eg/article_185492_6176504776a54398add4c9b6a9ae78b4.pdf |
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