{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,10]],"date-time":"2026-03-10T15:27:22Z","timestamp":1773156442452,"version":"3.50.1"},"reference-count":42,"publisher":"Institution of Engineering and Technology (IET)","issue":"6","license":[{"start":{"date-parts":[[2023,6,28]],"date-time":"2023-06-28T00:00:00Z","timestamp":1687910400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["ietresearch.onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["IET Networks"],"published-print":{"date-parts":[[2023,11]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>\n                    Cognitive radio (CR) systems are configured to dynamically assess the spectrum utilisation and contribute towards an improved spectrum efficiency. Hence, accurate detection of the incumbent signal in a given channel, popularly known as spectrum sensing (SS), is essential for CR. Here, in the domain of SS, the authors introduce a new goodness\u2010of\u2010fit test (GoFT) founded on\n                    <jats:italic>p<\/jats:italic>\n                    \u2010norm of the observations at the receiver node. To capture the heavy\u2010tailed nature of noise distribution in practical communication channels, the authors utilise generalised Gaussian distribution (GGD) as a noise model. A novel p\u2010norm detector (PND) and a geometric power detector (GPD) is proposed and corresponding probability density function (PDF) under GGD is derived. Via Monte Carlo simulations, the authors show a match of the derived PDFs with the simulation results. Using Neyman\u2010Pearson framework the performances of PND and GPD are compared with an existing differential entropy detector (DED), the well\u2010known energy detector (ED) and joint correlation and energy detector (CED) under GGD noise model. Evaluation of proposed PND and GPD utilising Monte Carlo simulations indicate a superior performance. Further, the experiments employing real\u2010world data establish superiority of the proposed detectors as compared to existing techniques. The authors derive and implement an optimised threshold for PND, providing further improvement in performance.\n                  <\/jats:p>","DOI":"10.1049\/ntw2.12092","type":"journal-article","created":{"date-parts":[[2023,6,29]],"date-time":"2023-06-29T00:02:12Z","timestamp":1687996932000},"page":"282-294","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Norm\u2010based spectrum sensing for cognitive radios under generalised Gaussian noise"],"prefix":"10.1049","volume":"12","author":[{"given":"Arati","family":"Halaki","sequence":"first","affiliation":[{"name":"Department of Electronics and Communication Engineering PES University  Bengaluru India"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9736-5011","authenticated-orcid":false,"given":"Sutapa","family":"Sarkar","sequence":"additional","affiliation":[{"name":"Department of Electronics and Communication Engineering CMR Institute of Technology  Bengaluru India"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0401-6651","authenticated-orcid":false,"given":"Sanjeev","family":"Gurugopinath","sequence":"additional","affiliation":[{"name":"Department of Electronics and Communication Engineering PES University  Bengaluru India"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5737-7974","authenticated-orcid":false,"given":"Muralishankar","family":"R","sequence":"additional","affiliation":[{"name":"Department of ECE, School of Engineering and Technology CMR University  Bengaluru India"}]}],"member":"265","published-online":{"date-parts":[[2023,6,28]]},"reference":[{"key":"e_1_2_12_2_1","doi-asserted-by":"publisher","DOI":"10.1109\/mcom.2014.6852078"},{"key":"e_1_2_12_3_1","doi-asserted-by":"publisher","DOI":"10.1049\/iet-com.2018.6067"},{"key":"e_1_2_12_4_1","doi-asserted-by":"publisher","DOI":"10.1109\/msp.2012.2183771"},{"key":"e_1_2_12_5_1","doi-asserted-by":"publisher","DOI":"10.1109\/twc.2009.081586"},{"key":"e_1_2_12_6_1","doi-asserted-by":"publisher","DOI":"10.23919\/jcc.2020.12.012"},{"key":"e_1_2_12_7_1","doi-asserted-by":"publisher","DOI":"10.1109\/jsyst.2018.2890333"},{"key":"e_1_2_12_8_1","doi-asserted-by":"publisher","DOI":"10.1049\/iet-com.2011.0452"},{"key":"e_1_2_12_9_1","doi-asserted-by":"publisher","DOI":"10.1109\/twc.2010.5403535"},{"key":"e_1_2_12_10_1","doi-asserted-by":"publisher","DOI":"10.1049\/iet-com.2010.0536"},{"key":"e_1_2_12_11_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-24540-9_18"},{"key":"e_1_2_12_12_1","first-page":"1","volume-title":"Proc. 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