{"id":8792,"date":"2013-01-16T00:35:06","date_gmt":"2013-01-15T22:35:06","guid":{"rendered":"http:\/\/hgpu.org\/?p=8792"},"modified":"2013-01-16T00:35:06","modified_gmt":"2013-01-15T22:35:06","slug":"efficient-implementation-of-multiuser-precoding-algorithms-on-gpu-for-mimo-ofdm-systems","status":"publish","type":"post","link":"https:\/\/hgpu.org\/?p=8792","title":{"rendered":"Efficient implementation of multiuser precoding algorithms on GPU for MIMO-OFDM systems"},"content":{"rendered":"<p>In this paper, we focus on the signal precoding stage in multiuser multicarrier systems, which can be often a computationally expensive task. In order to reduce their computational time, the implementation of some of the most employed multiuser precoding algorithms on a general purpose Graphic Processing Unit (GPU) is presented. These devices allow for a high level of parallel processing that can accelerate the time required for the signal precoding calculation. Results show that a speed-up of up to 4 is achieved when comparing the implementation on GPU with the conventional execution on a high performance CPU.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>In this paper, we focus on the signal precoding stage in multiuser multicarrier systems, which can be often a computationally expensive task. In order to reduce their computational time, the implementation of some of the most employed multiuser precoding algorithms on a general purpose Graphic Processing Unit (GPU) is presented. These devices allow for a [&hellip;]<\/p>\n","protected":false},"author":351,"featured_media":0,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_jetpack_memberships_contains_paid_content":false,"footnotes":"","jetpack_publicize_message":"","jetpack_publicize_feature_enabled":true,"jetpack_social_post_already_shared":false,"jetpack_social_options":{"image_generator_settings":{"template":"highway","default_image_id":0,"font":"","enabled":false},"version":2}},"categories":[36,89,3,41],"tags":[1787,14,521,20,710,1789],"class_list":["post-8792","post","type-post","status-publish","format-standard","hentry","category-algorithms","category-nvidia-cuda","category-paper","category-signal-processing","tag-algorithms","tag-cuda","tag-mimo","tag-nvidia","tag-nvidia-quadro-fx-5800","tag-signal-processing"],"views":2553,"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/8792","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/users\/351"}],"replies":[{"embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=8792"}],"version-history":[{"count":0,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/8792\/revisions"}],"wp:attachment":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=8792"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=8792"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=8792"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}