{"id":3616,"date":"2018-04-02T11:24:41","date_gmt":"2018-04-02T11:24:41","guid":{"rendered":"http:\/\/network.ee.tsinghua.edu.cn\/niulab\/?p=3616"},"modified":"2020-09-04T07:35:57","modified_gmt":"2020-09-04T07:35:57","slug":"algorithm-and-architecture-of-a-low-complexity-and-high-parallelism-preprocessing-based-k-best-detector-for-large-scale-mimo-systems","status":"publish","type":"post","link":"https:\/\/network.ee.tsinghua.edu.cn\/niulab\/?p=3616","title":{"rendered":"Algorithm and Architecture of a Low-Complexity and High-Parallelism Preprocessing-Based K-Best Detector for Large-Scale MIMO Systems"},"content":{"rendered":"<p><span class=\"paper_subtitle\"><a href=\"https:\/\/network.ee.tsinghua.edu.cn\/niulab\/wp-content\/uploads\/2018\/10\/PengTSP18.pdf\" rel=\"https:\/\/network.ee.tsinghua.edu.cn\/niulab\/wp-content\/uploads\/2018\/10\/PengTSP18.pdf\">TSP18<\/a><\/span><\/p>\n<p><span class=\"paper_subtitle\">LANGUAGE<\/span> English<\/p>\n<p><span class=\"paper_subtitle\">SOURCE<\/span> <strong><em> IEEE TRANSACTIONS ON SIGNAL PROCESSING<\/em><\/strong><\/p>\n<p><span class=\"paper_subtitle\">Published Date<\/span>:2018-04<\/p>\n<p><span class=\"paper_subtitle\">ABSTRACT<\/span><\/p>\n<p>Abstract\u2014As a branch of sphere decoding, the K-best method has played an important role in detection in large-scale multipleinput- multiple-output (MIMO) systems. However, as the numbers of users and antennas grow, the preprocessing complexity increases significantly, which is one of the major issues with the K-best<br \/>\nmethod. To address this problem, this paper proposes a preprocessing algorithm combining Cholesky sorted QR decomposition and partial iterative lattice reduction (CHOSLAR) for K-best detection in a 64-quadrature amplitude modulation (QAM) 16 \u00d7 16 MIMO system. First, Cholesky decomposition is conducted to perform sorted QR decomposition. Compared with conventional sorted QR decomposition, this method reduces the number of multiplications by 25.1% and increases parallelism. Then, a constant-throughput partial iterative lattice reduction method is adopted to achieve near-optimal detection accuracy. This method further increases parallelism, reduces the number of matrix swaps by 45.5%, and reduces the number of multiplications by 67.3%. Finally, a sortingreduced K-best strategy is used for vector estimation, thereby, reducing the number of comparators by 84.7%. This method suffers an accuracy loss of only approximately 1.44 dB compared with maximum likelihood detection. Based on CHOSLAR, this paper proposes a fully pipelined very-large-scale-integration architecture. A series of different systolic arrays and parallel processing units achieves an optimal tradeoff among throughput, area consumption, and power consumption. This architectural layout is obtained via TSMC 65-nm 1P9M CMOS technology, and throughput metrics of 1.40 Gbps\/W (throughput\/power) and 0.62 Mbps\/kG (throughput\/area) are achieved, demonstrating that the proposed system is much more efficient than state-of-the-art designs.<\/p>\n","protected":false},"excerpt":{"rendered":"<p><a href=\"https:\/\/network.ee.tsinghua.edu.cn\/niulab\/wp-content\/uploads\/2018\/10\/PengTSP18.pdf\" target=\"_blank\"><img loading=\"lazy\" decoding=\"async\" class=\"alignleft size-full wp-image-117\" title=\"pdf\" src=\"https:\/\/network.ee.tsinghua.edu.cn\/niulab\/wp-content\/uploads\/2010\/08\/pdf.gif\"alt=\"\" width=\"95\" height=\"50\" \/><\/a>Guiqiang Peng, Leibo Liu, Sheng Zhou, Yang Xue, Shouyi Yin, and Shaojun Wei, Algorithm and Architecture of a Low-Complexity and High-Parallelism Preprocessing-Based K-Best Detector for Large-Scale MIMO Systems, <span class=\"papersource\">IEEE TRANSACTIONS ON SIGNAL PROCESSING, Apr. 2018, 66(7):1860-1875<\/span><\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_jetpack_memberships_contains_paid_content":false,"footnotes":""},"categories":[7],"tags":[100],"jetpack_sharing_enabled":true,"jetpack_featured_media_url":"","_links":{"self":[{"href":"https:\/\/network.ee.tsinghua.edu.cn\/niulab\/index.php?rest_route=\/wp\/v2\/posts\/3616"}],"collection":[{"href":"https:\/\/network.ee.tsinghua.edu.cn\/niulab\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/network.ee.tsinghua.edu.cn\/niulab\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/network.ee.tsinghua.edu.cn\/niulab\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/network.ee.tsinghua.edu.cn\/niulab\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=3616"}],"version-history":[{"count":3,"href":"https:\/\/network.ee.tsinghua.edu.cn\/niulab\/index.php?rest_route=\/wp\/v2\/posts\/3616\/revisions"}],"predecessor-version":[{"id":3619,"href":"https:\/\/network.ee.tsinghua.edu.cn\/niulab\/index.php?rest_route=\/wp\/v2\/posts\/3616\/revisions\/3619"}],"wp:attachment":[{"href":"https:\/\/network.ee.tsinghua.edu.cn\/niulab\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=3616"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/network.ee.tsinghua.edu.cn\/niulab\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=3616"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/network.ee.tsinghua.edu.cn\/niulab\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=3616"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}