{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2022,12,22]],"date-time":"2022-12-22T06:03:54Z","timestamp":1671689034054},"reference-count":0,"publisher":"IOS Press","isbn-type":[{"value":"9781643683683","type":"print"},{"value":"9781643683690","type":"electronic"}],"license":[{"start":{"date-parts":[[2022,12,13]],"date-time":"2022-12-13T00:00:00Z","timestamp":1670889600000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022,12,13]]},"abstract":"<jats:p>Recently, alternating minimization has been widely employed for hybrid fully-connected precoding schemes, whereas the complexity is too high. In order to further reduce the complexity while maintaining the performance of single user point-to-point millimeter wave multiple-input multiple-output (MIMO) systems, we propose an alternating minimization algorithm of inverse matrix\u2019s phase extraction based on orthogonal matching pursuit (AIPO). Firstly, both the analog and digital precoding matrices are obtained by orthogonal matching pursuit algorithm. Then, the analog precoding matrix is updated using the phase information extracted from the digital precoding matrix and the optimal digital precoding matrix. Finally, the local optimal solution can be iteratively obtained under the least squares criterion and the modulus constraint. Simulation results verify that the proposed algorithm is capable of dramatically decreasing the complexity by more than sixty percent without compromising spectrum and energy efficiencies.<\/jats:p>","DOI":"10.3233\/faia220551","type":"book-chapter","created":{"date-parts":[[2022,12,21]],"date-time":"2022-12-21T08:01:11Z","timestamp":1671609671000},"source":"Crossref","is-referenced-by-count":0,"title":["Low Complexity and High Spectrum Efficiency Hybrid Precoding for Massive MIMO Systems"],"prefix":"10.3233","author":[{"given":"Gang","family":"Xie","sequence":"first","affiliation":[{"name":"School of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, China"}]},{"given":"Zhixiang","family":"Pei","sequence":"additional","affiliation":[{"name":"School of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, China"}]}],"member":"7437","container-title":["Frontiers in Artificial Intelligence and Applications","Proceedings of CECNet 2022"],"original-title":[],"link":[{"URL":"https:\/\/ebooks.iospress.nl\/pdf\/doi\/10.3233\/FAIA220551","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,12,21]],"date-time":"2022-12-21T08:01:12Z","timestamp":1671609672000},"score":1,"resource":{"primary":{"URL":"https:\/\/ebooks.iospress.nl\/doi\/10.3233\/FAIA220551"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,12,13]]},"ISBN":["9781643683683","9781643683690"],"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/faia220551","relation":{},"ISSN":["0922-6389","1879-8314"],"issn-type":[{"value":"0922-6389","type":"print"},{"value":"1879-8314","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,12,13]]}}}