{"id":9526,"date":"2021-02-20T15:37:20","date_gmt":"2021-02-20T07:37:20","guid":{"rendered":"https:\/\/virtual.math.ntnu.edu.tw\/?p=9526"},"modified":"2021-02-20T15:46:14","modified_gmt":"2021-02-20T07:46:14","slug":"001-9","status":"publish","type":"post","link":"https:\/\/virtual.math.ntnu.edu.tw\/index.php\/2021\/02\/20\/001-9\/","title":{"rendered":"<span style=\"color:#3566BD\">[\u5c08\u984c\u6f14\u8b1b] <\/span>Secrecy Energy Efficiency in Cognitive Radio Networks with Untrusted Secondary Users"},"content":{"rendered":"<p>\u4e3b\u8b1b\u4eba\uff1a\u7941\u5fe0\u52c7\u6559\u6388<br \/>\n\u4e3b\u8b1b\u4eba\u4f86\u81ea\uff1a\u570b\u7acb\u6e05\u83ef\u5927\u5b78 Institute of Communications Engineering &amp; Department of Electrical Engineering<br \/>\n\u984c\u76ee\uff1aSecrecy Energy Efficiency in Cognitive Radio Networks with Untrusted Secondary Users<br \/>\n\u6458\u8981\uff1aThe information security and energy efficiency in cognitive radio (CR) networks have been<br \/>\nextensively studied. However, the practical scenario involving multiple untrusted secondary users (SUs)<br \/>\nin CR networks under the underlay spectrum sharing mechanism has not been studied so far. This talk<br \/>\nconsiders the downlink secrecy energy efficient coordinated beamforming design for multiple inputs<br \/>\nsingle output CR networks under this scenario. Our goal is to maximize the global secrecy energy<br \/>\nefficiency (GSEE), defined as the ratio of the sum of secrecy rates of all the primary users (PUs) to the<br \/>\ntotal power consumption, under requirements on quality of service of Pus and SUs as well as<br \/>\nconstraints on power budget at the primary transmitter (PTx) and the secondary transmitter (STx). To<br \/>\ntackle the non-convex GSEE maximization (GSEEM) problem, an algorithm is proposed based on<br \/>\nDinkelbach method and successive convex approximation to jointly optimize beamforming vectors of<br \/>\nthe PTx and the STx. The convergence behavior and the computational complexity of the proposed<br \/>\nGSEEM algorithm are analyzed, followed by the connection with the secrecy rate maximization design<br \/>\nand the power minimization (PM) design in terms of GSEE. In view of significantly higher<br \/>\ncomputational complexity of the proposed GSEEM algorithm than that of the PM design, a 2-step<br \/>\nsearching scheme is further designed to efficiently search for an approximate solution to the considered<br \/>\nGSEEM problem based on the PM design and the golden search method. Simulation results<br \/>\ndemonstrate the efficacy of the proposed GSEEM algorithm and the searching scheme, and show that<br \/>\nthe spatial degrees of freedom (primarily determined by the antenna numbers of PTx and STx) is the<br \/>\nkey factor to the performance of the proposed GSEEM algorithm.<\/p>\n<p>\u6642\u9593\uff1a2021-3-3 14:00 (\u661f\u671f\u4e09) \/\u00a0\u5730\u9ede\uff1aM212<br \/>\n\u8336\u6703\u6642\u9593\uff1a2021-3-3 13:30 (\u661f\u671f\u4e09) \/ \u8336\u6703\u5730\u9ede\uff1aM104<\/p>\n<p><a href=\"https:\/\/virtual.math.ntnu.edu.tw\/wp-content\/uploads\/2021\/02\/Invited-Talk-Chi-Abstract-and-Bio-NTNU-2021-3-3.pdf\">\u8b1b\u8005\u7c21\u4ecb\uff1aInvited Talk (Chi Abstract and Bio) (NTNU 2021-3-3)<\/a><\/p>\n<p class=\"wpf_wrapper\"><a class=\"print_link\" href=\"\" target=\"_blank\">\u53cb\u5584\u5217\u5370<\/a><\/p><!-- .wpf_wrapper -->","protected":false},"excerpt":{"rendered":"<p>\u4e3b\u8b1b\u4eba\uff1a\u7941\u5fe0\u52c7\u6559\u6388 \u4e3b\u8b1b\u4eba\u4f86\u81ea\uff1a\u570b\u7acb\u6e05\u83ef\u5927\u5b78 Institute of Communications Engi [&hellip;]<\/p>\n","protected":false},"author":18,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":[],"categories":[1,18,122,124],"tags":[],"_links":{"self":[{"href":"https:\/\/virtual.math.ntnu.edu.tw\/index.php\/wp-json\/wp\/v2\/posts\/9526"}],"collection":[{"href":"https:\/\/virtual.math.ntnu.edu.tw\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/virtual.math.ntnu.edu.tw\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/virtual.math.ntnu.edu.tw\/index.php\/wp-json\/wp\/v2\/users\/18"}],"replies":[{"embeddable":true,"href":"https:\/\/virtual.math.ntnu.edu.tw\/index.php\/wp-json\/wp\/v2\/comments?post=9526"}],"version-history":[{"count":3,"href":"https:\/\/virtual.math.ntnu.edu.tw\/index.php\/wp-json\/wp\/v2\/posts\/9526\/revisions"}],"predecessor-version":[{"id":9534,"href":"https:\/\/virtual.math.ntnu.edu.tw\/index.php\/wp-json\/wp\/v2\/posts\/9526\/revisions\/9534"}],"wp:attachment":[{"href":"https:\/\/virtual.math.ntnu.edu.tw\/index.php\/wp-json\/wp\/v2\/media?parent=9526"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/virtual.math.ntnu.edu.tw\/index.php\/wp-json\/wp\/v2\/categories?post=9526"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/virtual.math.ntnu.edu.tw\/index.php\/wp-json\/wp\/v2\/tags?post=9526"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}