Low Complexity Energy Optimization Algorithm for Massive MIMO systems
We consider the problem of nearly optimal energy efficiency in massive(Multiinput Multi-output) MIMO systems. Considering the correlated channel in practice, we derive the ergodic expression with zero-forcing precoding and analyze the simplified antennas selection method. Aiming at optimizing the en...
Gespeichert in:
| Veröffentlicht in: | China communications 2015-12, Vol.12 (S1), p.74-82 |
|---|---|
| Hauptverfasser: | , , , |
| Format: | Artikel |
| Sprache: | eng |
| Schlagworte: | |
| Online-Zugang: | Volltext bestellen |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | 82 |
|---|---|
| container_issue | S1 |
| container_start_page | 74 |
| container_title | China communications |
| container_volume | 12 |
| creator | Yuan, Jingya Li, Xiaohui Hei, Yongqiang Fu, Weihong |
| description | We consider the problem of nearly optimal energy efficiency in massive(Multiinput Multi-output) MIMO systems. Considering the correlated channel in practice, we derive the ergodic expression with zero-forcing precoding and analyze the simplified antennas selection method. Aiming at optimizing the energy efficiency, the closed form expressions of the nearly optimal number of transmit antennas and transmit power are given under the circuit consumption model. The joint solution of the number of transmit antennas and transmit power was replaced to only solve transmit power. Based on the expression only related with transmit power, we give an energy efficiency optimization algorithm. The simulation results show that the proposed algorithm can achieve nearly optimal energy efficiency with fast convergence speed. |
| doi_str_mv | 10.1109/CC.2015.7386173 |
| format | Article |
| fullrecord | <record><control><sourceid>crossref_RIE</sourceid><recordid>TN_cdi_chongqing_primary_90718479504849538349484948</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><cqvip_id>90718479504849538349484948</cqvip_id><ieee_id>7386173</ieee_id><sourcerecordid>10_1109_CC_2015_7386173</sourcerecordid><originalsourceid>FETCH-LOGICAL-c259t-ffa70fa47eef5ee26cbe790661610f7e3fd85996cbe153ed4723b3b3a29060c53</originalsourceid><addsrcrecordid>eNpFj8tuwjAQRb1opSLKuotu_AMBO34vkUUfEohNu45MGAdXJKZx1Db9-iYC0ZnFjGbOvdJF6IGSOaXELKyd54SKuWJaUsVu0IRKxTLBubpDs5Q-yFBaSibzCVqt4ze2sT4d4Sd0PV410FY93p66UIdf14XY4OWxim3oDjX2scUbl1L4Arx53Wxx6lMHdbpHt94dE8wuc4ren1Zv9iVbb59f7XKdlbkwXea9U8Q7rgC8AMhluQNliJRUUuIVML_XwpjxTAWDPVc52w3t8gEipWBTtDj7lm1MqQVfnNpQu7YvKCnG8IW1xRi-uIQfFI9nRQCAK_3_ZRe_Q2yqz9BUV8QQRTVXRhCuuRFMM27GjWv2B_YVZpk</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype></control><display><type>article</type><title>Low Complexity Energy Optimization Algorithm for Massive MIMO systems</title><source>IEEE Electronic Library (IEL)</source><creator>Yuan, Jingya ; Li, Xiaohui ; Hei, Yongqiang ; Fu, Weihong</creator><creatorcontrib>Yuan, Jingya ; Li, Xiaohui ; Hei, Yongqiang ; Fu, Weihong</creatorcontrib><description>We consider the problem of nearly optimal energy efficiency in massive(Multiinput Multi-output) MIMO systems. Considering the correlated channel in practice, we derive the ergodic expression with zero-forcing precoding and analyze the simplified antennas selection method. Aiming at optimizing the energy efficiency, the closed form expressions of the nearly optimal number of transmit antennas and transmit power are given under the circuit consumption model. The joint solution of the number of transmit antennas and transmit power was replaced to only solve transmit power. Based on the expression only related with transmit power, we give an energy efficiency optimization algorithm. The simulation results show that the proposed algorithm can achieve nearly optimal energy efficiency with fast convergence speed.</description><identifier>ISSN: 1673-5447</identifier><identifier>DOI: 10.1109/CC.2015.7386173</identifier><identifier>CODEN: CCHOBE</identifier><language>eng</language><publisher>China Institute of Communications</publisher><subject>Algorithm design and analysis ; antenna number optimization ; Complexity theory ; efficiency;ergodic ; energy ; Energy efficiency ; ergodic expression ; expression;fraction ; fraction program ; MIMO ; number ; Optimization ; optimization;antenna ; power optimization ; program;power ; Transmitting antennas</subject><ispartof>China communications, 2015-12, Vol.12 (S1), p.74-82</ispartof><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Uhttp://image.cqvip.com/vip1000/qk/89450X/89450X.jpg</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/7386173$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>314,780,784,796,27924,27925,54758</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/7386173$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Yuan, Jingya</creatorcontrib><creatorcontrib>Li, Xiaohui</creatorcontrib><creatorcontrib>Hei, Yongqiang</creatorcontrib><creatorcontrib>Fu, Weihong</creatorcontrib><title>Low Complexity Energy Optimization Algorithm for Massive MIMO systems</title><title>China communications</title><addtitle>ChinaComm</addtitle><addtitle>China Communications</addtitle><description>We consider the problem of nearly optimal energy efficiency in massive(Multiinput Multi-output) MIMO systems. Considering the correlated channel in practice, we derive the ergodic expression with zero-forcing precoding and analyze the simplified antennas selection method. Aiming at optimizing the energy efficiency, the closed form expressions of the nearly optimal number of transmit antennas and transmit power are given under the circuit consumption model. The joint solution of the number of transmit antennas and transmit power was replaced to only solve transmit power. Based on the expression only related with transmit power, we give an energy efficiency optimization algorithm. The simulation results show that the proposed algorithm can achieve nearly optimal energy efficiency with fast convergence speed.</description><subject>Algorithm design and analysis</subject><subject>antenna number optimization</subject><subject>Complexity theory</subject><subject>efficiency;ergodic</subject><subject>energy</subject><subject>Energy efficiency</subject><subject>ergodic expression</subject><subject>expression;fraction</subject><subject>fraction program</subject><subject>MIMO</subject><subject>number</subject><subject>Optimization</subject><subject>optimization;antenna</subject><subject>power optimization</subject><subject>program;power</subject><subject>Transmitting antennas</subject><issn>1673-5447</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2015</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNpFj8tuwjAQRb1opSLKuotu_AMBO34vkUUfEohNu45MGAdXJKZx1Db9-iYC0ZnFjGbOvdJF6IGSOaXELKyd54SKuWJaUsVu0IRKxTLBubpDs5Q-yFBaSibzCVqt4ze2sT4d4Sd0PV410FY93p66UIdf14XY4OWxim3oDjX2scUbl1L4Arx53Wxx6lMHdbpHt94dE8wuc4ren1Zv9iVbb59f7XKdlbkwXea9U8Q7rgC8AMhluQNliJRUUuIVML_XwpjxTAWDPVc52w3t8gEipWBTtDj7lm1MqQVfnNpQu7YvKCnG8IW1xRi-uIQfFI9nRQCAK_3_ZRe_Q2yqz9BUV8QQRTVXRhCuuRFMM27GjWv2B_YVZpk</recordid><startdate>20151201</startdate><enddate>20151201</enddate><creator>Yuan, Jingya</creator><creator>Li, Xiaohui</creator><creator>Hei, Yongqiang</creator><creator>Fu, Weihong</creator><general>China Institute of Communications</general><scope>2RA</scope><scope>92L</scope><scope>CQIGP</scope><scope>~WA</scope><scope>97E</scope><scope>RIA</scope><scope>RIE</scope><scope>AAYXX</scope><scope>CITATION</scope></search><sort><creationdate>20151201</creationdate><title>Low Complexity Energy Optimization Algorithm for Massive MIMO systems</title><author>Yuan, Jingya ; Li, Xiaohui ; Hei, Yongqiang ; Fu, Weihong</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c259t-ffa70fa47eef5ee26cbe790661610f7e3fd85996cbe153ed4723b3b3a29060c53</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2015</creationdate><topic>Algorithm design and analysis</topic><topic>antenna number optimization</topic><topic>Complexity theory</topic><topic>efficiency;ergodic</topic><topic>energy</topic><topic>Energy efficiency</topic><topic>ergodic expression</topic><topic>expression;fraction</topic><topic>fraction program</topic><topic>MIMO</topic><topic>number</topic><topic>Optimization</topic><topic>optimization;antenna</topic><topic>power optimization</topic><topic>program;power</topic><topic>Transmitting antennas</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Yuan, Jingya</creatorcontrib><creatorcontrib>Li, Xiaohui</creatorcontrib><creatorcontrib>Hei, Yongqiang</creatorcontrib><creatorcontrib>Fu, Weihong</creatorcontrib><collection>中文科技期刊数据库</collection><collection>中文科技期刊数据库-CALIS站点</collection><collection>中文科技期刊数据库-7.0平台</collection><collection>中文科技期刊数据库- 镜像站点</collection><collection>IEEE All-Society Periodicals Package (ASPP) 2005-present</collection><collection>IEEE All-Society Periodicals Package (ASPP) 1998-Present</collection><collection>IEEE Electronic Library (IEL)</collection><collection>CrossRef</collection><jtitle>China communications</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Yuan, Jingya</au><au>Li, Xiaohui</au><au>Hei, Yongqiang</au><au>Fu, Weihong</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Low Complexity Energy Optimization Algorithm for Massive MIMO systems</atitle><jtitle>China communications</jtitle><stitle>ChinaComm</stitle><addtitle>China Communications</addtitle><date>2015-12-01</date><risdate>2015</risdate><volume>12</volume><issue>S1</issue><spage>74</spage><epage>82</epage><pages>74-82</pages><issn>1673-5447</issn><coden>CCHOBE</coden><abstract>We consider the problem of nearly optimal energy efficiency in massive(Multiinput Multi-output) MIMO systems. Considering the correlated channel in practice, we derive the ergodic expression with zero-forcing precoding and analyze the simplified antennas selection method. Aiming at optimizing the energy efficiency, the closed form expressions of the nearly optimal number of transmit antennas and transmit power are given under the circuit consumption model. The joint solution of the number of transmit antennas and transmit power was replaced to only solve transmit power. Based on the expression only related with transmit power, we give an energy efficiency optimization algorithm. The simulation results show that the proposed algorithm can achieve nearly optimal energy efficiency with fast convergence speed.</abstract><pub>China Institute of Communications</pub><doi>10.1109/CC.2015.7386173</doi><tpages>9</tpages></addata></record> |
| fulltext | fulltext_linktorsrc |
| identifier | ISSN: 1673-5447 |
| ispartof | China communications, 2015-12, Vol.12 (S1), p.74-82 |
| issn | 1673-5447 |
| language | eng |
| recordid | cdi_chongqing_primary_90718479504849538349484948 |
| source | IEEE Electronic Library (IEL) |
| subjects | Algorithm design and analysis antenna number optimization Complexity theory efficiency ergodic energy Energy efficiency ergodic expression expression fraction fraction program MIMO number Optimization optimization antenna power optimization program power Transmitting antennas |
| title | Low Complexity Energy Optimization Algorithm for Massive MIMO systems |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-06T14%3A02%3A37IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-crossref_RIE&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Low%20Complexity%20Energy%20Optimization%20Algorithm%20for%20Massive%20MIMO%20systems&rft.jtitle=China%20communications&rft.au=Yuan,%20Jingya&rft.date=2015-12-01&rft.volume=12&rft.issue=S1&rft.spage=74&rft.epage=82&rft.pages=74-82&rft.issn=1673-5447&rft.coden=CCHOBE&rft_id=info:doi/10.1109/CC.2015.7386173&rft_dat=%3Ccrossref_RIE%3E10_1109_CC_2015_7386173%3C/crossref_RIE%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_id=info:pmid/&rft_cqvip_id=90718479504849538349484948&rft_ieee_id=7386173&rfr_iscdi=true |