{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T04:13:51Z","timestamp":1760242431902,"version":"build-2065373602"},"reference-count":20,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2017,8,18]],"date-time":"2017-08-18T00:00:00Z","timestamp":1503014400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"the National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["U1533125"],"award-info":[{"award-number":["U1533125"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100018537","name":"National Science and Technology Major Project","doi-asserted-by":"publisher","award":["2016ZX03001022"],"award-info":[{"award-number":["2016ZX03001022"]}],"id":[{"id":"10.13039\/501100018537","id-type":"DOI","asserted-by":"publisher"}]},{"name":"the Fundamental Research Funds for the Central Universities","award":["ZYGX2015Z011"],"award-info":[{"award-number":["ZYGX2015Z011"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Algorithms"],"abstract":"<jats:p>Higher-order cyclic cumulants (CCs) have been widely adopted for automatic modulation recognition (AMR) in cognitive radio. However, the CC-based AMR suffers greatly from the requirement of high-rate sampling. To overcome this limit, we resort to the theory of compressive sensing (CS). By exploiting the sparsity of CCs, recognition features can be extracted from a small amount of compressive measurements via a rough CS reconstruction algorithm. Accordingly, a CS-based AMR scheme is formulated. Simulation results demonstrate the availability and robustness of the proposed approach.<\/jats:p>","DOI":"10.3390\/a10030092","type":"journal-article","created":{"date-parts":[[2017,8,21]],"date-time":"2017-08-21T04:12:17Z","timestamp":1503288737000},"page":"92","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Automatic Modulation Recognition Using Compressive Cyclic Features"],"prefix":"10.3390","volume":"10","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0493-6159","authenticated-orcid":false,"given":"Lijin","family":"Xie","sequence":"first","affiliation":[{"name":"Department of Electronic Engineering, University of Electronic Science and Technology of China, Qingshuihe Campus, No. 2006, Xiyuan Ave, West Hi-Tech Zone, Chengdu 611731, Sichuan, China"}]},{"given":"Qun","family":"Wan","sequence":"additional","affiliation":[{"name":"Department of Electronic Engineering, University of Electronic Science and Technology of China, Qingshuihe Campus, No. 2006, Xiyuan Ave, West Hi-Tech Zone, Chengdu 611731, Sichuan, China"}]}],"member":"1968","published-online":{"date-parts":[[2017,8,18]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1688","DOI":"10.1109\/LCOMM.2013.080613.130070","article-title":"Feature space analysis of modulation classification using very high-order statistics","volume":"17","author":"Su","year":"2013","journal-title":"Commun. 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