Information rates of precoding for massive MIMO and base station cooperation in an indoor scenario
The performance of centralized and distributed massive MIMO deployments are studied for simulated indoor office scenarios. The distributed deployments use one of the following precoding methods: (1) local precoding with local channel state information (CSI) to the user equipments (UEs) that it serve...
Gespeichert in:
Veröffentlicht in: | EURASIP journal on wireless communications and networking 2020-01, Vol.2020 (1), p.1-12, Article 22 |
---|---|
Hauptverfasser: | , , , |
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
container_end_page | 12 |
---|---|
container_issue | 1 |
container_start_page | 1 |
container_title | EURASIP journal on wireless communications and networking |
container_volume | 2020 |
creator | Dierks, Stefan Kramer, Gerhard Panzner, Berthold Zirwas, Wolfgang |
description | The performance of centralized and distributed massive MIMO deployments are studied for simulated indoor office scenarios. The distributed deployments use one of the following precoding methods: (1) local precoding with local channel state information (CSI) to the user equipments (UEs) that it serves, (2) large-scale MIMO with local CSI to all UEs in the network, (3) network MIMO with global CSI. For the distributed deployment (3), it is found that using twice as many base station antennas as data streams provides many of the massive MIMO benefits in terms of spectral efficiency and fairness. This is in contrast to the centralized and distributed deployments using (1) or (2) where more antennas are needed. Two main conclusions are that distributing base stations helps to overcome wall penetration loss; however, a backhaul is required to mitigate inter-cell interference. The effect of estimation errors on the performance is also quantified. |
doi_str_mv | 10.1186/s13638-019-1636-5 |
format | Article |
fullrecord | <record><control><sourceid>proquest_webof</sourceid><recordid>TN_cdi_proquest_journals_2343522359</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><doaj_id>oai_doaj_org_article_359cd934879541f38b0dbfff15be098c</doaj_id><sourcerecordid>2343522359</sourcerecordid><originalsourceid>FETCH-LOGICAL-c377t-646032bc200dcee79eb604c8c373e208b2531ff3a701322cdb1d452128ba74713</originalsourceid><addsrcrecordid>eNqNkcGOFCEQhonRxHX0Abx14tG0SwENzdFMdJ1kN3vRMwG6mDDZgRF6NL69rJjxtIkXqFT9X1XBT8hboB8AZnldgUs-jxT0CJLLcXpGrkDOagSh9fNLrNhL8qrWA6WcC82uiNulkMvRrjGnodgV65DDcCro8xLTfmjF4WhrjT9wuNvd3Q82LYOzFYe6dsjnfMLS45havZ1Lblj1mGyJ-TV5EexDxTd_7w359vnT1-2X8fb-Zrf9eDt6rtQ6SiEpZ84zShePqDQ6SYWfW5Ujo7NjE4cQuFUUOGN-cbCIiQGbnVVCAd-QXe-7ZHswpxKPtvwy2UbzJ5HL3tiyRv-Ahk_aL5qLWelJQOCzo4sLIcDkkOo2ckPe9V6nkr-fsa7mkM8ltfUN44JPjLUWTQVd5UuutWC4TAVqHm0x3RbTbDGPtpipMXNnfqLLofqIyeOFo5ROjIKQqkUUtrF_8jaf09rQ9_-PNjXr6toUaY_l3xOe3u43GIqvrA</addsrcrecordid><sourcetype>Open Website</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2343522359</pqid></control><display><type>article</type><title>Information rates of precoding for massive MIMO and base station cooperation in an indoor scenario</title><source>Springer Online Journals Complete</source><source>DOAJ Directory of Open Access Journals</source><source>Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals</source><source>Web of Science - Science Citation Index Expanded - 2020<img src="https://exlibris-pub.s3.amazonaws.com/fromwos-v2.jpg" /></source><source>Springer Nature OA/Free Journals</source><creator>Dierks, Stefan ; Kramer, Gerhard ; Panzner, Berthold ; Zirwas, Wolfgang</creator><creatorcontrib>Dierks, Stefan ; Kramer, Gerhard ; Panzner, Berthold ; Zirwas, Wolfgang</creatorcontrib><description>The performance of centralized and distributed massive MIMO deployments are studied for simulated indoor office scenarios. The distributed deployments use one of the following precoding methods: (1) local precoding with local channel state information (CSI) to the user equipments (UEs) that it serves, (2) large-scale MIMO with local CSI to all UEs in the network, (3) network MIMO with global CSI. For the distributed deployment (3), it is found that using twice as many base station antennas as data streams provides many of the massive MIMO benefits in terms of spectral efficiency and fairness. This is in contrast to the centralized and distributed deployments using (1) or (2) where more antennas are needed. Two main conclusions are that distributing base stations helps to overcome wall penetration loss; however, a backhaul is required to mitigate inter-cell interference. The effect of estimation errors on the performance is also quantified.</description><identifier>ISSN: 1687-1472</identifier><identifier>ISSN: 1687-1499</identifier><identifier>EISSN: 1687-1499</identifier><identifier>DOI: 10.1186/s13638-019-1636-5</identifier><language>eng</language><publisher>Cham: Springer International Publishing</publisher><subject>Antennas ; Base station cooperation ; Communications Engineering ; Data transmission ; Engineering ; Engineering, Electrical & Electronic ; Indoor communication ; Information Systems Applications (incl.Internet) ; Massive MIMO ; Mobile radio communication ; Network MIMO ; Networks ; Science & Technology ; Signal,Image and Speech Processing ; Technology ; Telecommunications</subject><ispartof>EURASIP journal on wireless communications and networking, 2020-01, Vol.2020 (1), p.1-12, Article 22</ispartof><rights>Dierks et al. 2020</rights><rights>EURASIP Journal on Wireless Communications and Networking is a copyright of Springer, (2020). All Rights Reserved. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>true</woscitedreferencessubscribed><woscitedreferencescount>0</woscitedreferencescount><woscitedreferencesoriginalsourcerecordid>wos000520146700001</woscitedreferencesoriginalsourcerecordid><cites>FETCH-LOGICAL-c377t-646032bc200dcee79eb604c8c373e208b2531ff3a701322cdb1d452128ba74713</cites><orcidid>0000-0003-3142-0967 ; 0000-0002-3904-9181</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1186/s13638-019-1636-5$$EPDF$$P50$$Gspringer$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1186/s13638-019-1636-5$$EHTML$$P50$$Gspringer$$Hfree_for_read</linktohtml><link.rule.ids>315,781,785,865,2103,2115,27929,27930,28253,41125,41493,42194,42562,51324,51581</link.rule.ids></links><search><creatorcontrib>Dierks, Stefan</creatorcontrib><creatorcontrib>Kramer, Gerhard</creatorcontrib><creatorcontrib>Panzner, Berthold</creatorcontrib><creatorcontrib>Zirwas, Wolfgang</creatorcontrib><title>Information rates of precoding for massive MIMO and base station cooperation in an indoor scenario</title><title>EURASIP journal on wireless communications and networking</title><addtitle>J Wireless Com Network</addtitle><addtitle>EURASIP J WIREL COMM</addtitle><description>The performance of centralized and distributed massive MIMO deployments are studied for simulated indoor office scenarios. The distributed deployments use one of the following precoding methods: (1) local precoding with local channel state information (CSI) to the user equipments (UEs) that it serves, (2) large-scale MIMO with local CSI to all UEs in the network, (3) network MIMO with global CSI. For the distributed deployment (3), it is found that using twice as many base station antennas as data streams provides many of the massive MIMO benefits in terms of spectral efficiency and fairness. This is in contrast to the centralized and distributed deployments using (1) or (2) where more antennas are needed. Two main conclusions are that distributing base stations helps to overcome wall penetration loss; however, a backhaul is required to mitigate inter-cell interference. The effect of estimation errors on the performance is also quantified.</description><subject>Antennas</subject><subject>Base station cooperation</subject><subject>Communications Engineering</subject><subject>Data transmission</subject><subject>Engineering</subject><subject>Engineering, Electrical & Electronic</subject><subject>Indoor communication</subject><subject>Information Systems Applications (incl.Internet)</subject><subject>Massive MIMO</subject><subject>Mobile radio communication</subject><subject>Network MIMO</subject><subject>Networks</subject><subject>Science & Technology</subject><subject>Signal,Image and Speech Processing</subject><subject>Technology</subject><subject>Telecommunications</subject><issn>1687-1472</issn><issn>1687-1499</issn><issn>1687-1499</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><sourceid>C6C</sourceid><sourceid>AOWDO</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><sourceid>DOA</sourceid><recordid>eNqNkcGOFCEQhonRxHX0Abx14tG0SwENzdFMdJ1kN3vRMwG6mDDZgRF6NL69rJjxtIkXqFT9X1XBT8hboB8AZnldgUs-jxT0CJLLcXpGrkDOagSh9fNLrNhL8qrWA6WcC82uiNulkMvRrjGnodgV65DDcCro8xLTfmjF4WhrjT9wuNvd3Q82LYOzFYe6dsjnfMLS45havZ1Lblj1mGyJ-TV5EexDxTd_7w359vnT1-2X8fb-Zrf9eDt6rtQ6SiEpZ84zShePqDQ6SYWfW5Ujo7NjE4cQuFUUOGN-cbCIiQGbnVVCAd-QXe-7ZHswpxKPtvwy2UbzJ5HL3tiyRv-Ahk_aL5qLWelJQOCzo4sLIcDkkOo2ckPe9V6nkr-fsa7mkM8ltfUN44JPjLUWTQVd5UuutWC4TAVqHm0x3RbTbDGPtpipMXNnfqLLofqIyeOFo5ROjIKQqkUUtrF_8jaf09rQ9_-PNjXr6toUaY_l3xOe3u43GIqvrA</recordid><startdate>20200121</startdate><enddate>20200121</enddate><creator>Dierks, Stefan</creator><creator>Kramer, Gerhard</creator><creator>Panzner, Berthold</creator><creator>Zirwas, Wolfgang</creator><general>Springer International Publishing</general><general>Springer Nature</general><general>Springer Nature B.V</general><general>SpringerOpen</general><scope>C6C</scope><scope>AOWDO</scope><scope>BLEPL</scope><scope>DTL</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7SC</scope><scope>7SP</scope><scope>7XB</scope><scope>8AL</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>JQ2</scope><scope>K7-</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><scope>M0N</scope><scope>P5Z</scope><scope>P62</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>Q9U</scope><scope>DOA</scope><orcidid>https://orcid.org/0000-0003-3142-0967</orcidid><orcidid>https://orcid.org/0000-0002-3904-9181</orcidid></search><sort><creationdate>20200121</creationdate><title>Information rates of precoding for massive MIMO and base station cooperation in an indoor scenario</title><author>Dierks, Stefan ; Kramer, Gerhard ; Panzner, Berthold ; Zirwas, Wolfgang</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c377t-646032bc200dcee79eb604c8c373e208b2531ff3a701322cdb1d452128ba74713</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>Antennas</topic><topic>Base station cooperation</topic><topic>Communications Engineering</topic><topic>Data transmission</topic><topic>Engineering</topic><topic>Engineering, Electrical & Electronic</topic><topic>Indoor communication</topic><topic>Information Systems Applications (incl.Internet)</topic><topic>Massive MIMO</topic><topic>Mobile radio communication</topic><topic>Network MIMO</topic><topic>Networks</topic><topic>Science & Technology</topic><topic>Signal,Image and Speech Processing</topic><topic>Technology</topic><topic>Telecommunications</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Dierks, Stefan</creatorcontrib><creatorcontrib>Kramer, Gerhard</creatorcontrib><creatorcontrib>Panzner, Berthold</creatorcontrib><creatorcontrib>Zirwas, Wolfgang</creatorcontrib><collection>Springer Nature OA/Free Journals</collection><collection>Web of Science - Science Citation Index Expanded - 2020</collection><collection>Web of Science Core Collection</collection><collection>Science Citation Index Expanded</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Computer and Information Systems Abstracts</collection><collection>Electronics & Communications Abstracts</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Computing Database (Alumni Edition)</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>Advanced Technologies & Aerospace Collection</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>ProQuest Central Student</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Computer Science Collection</collection><collection>Computer Science Database</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><collection>Computing Database</collection><collection>Advanced Technologies & Aerospace Database</collection><collection>ProQuest Advanced Technologies & Aerospace Collection</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>ProQuest Central Basic</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>EURASIP journal on wireless communications and networking</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Dierks, Stefan</au><au>Kramer, Gerhard</au><au>Panzner, Berthold</au><au>Zirwas, Wolfgang</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Information rates of precoding for massive MIMO and base station cooperation in an indoor scenario</atitle><jtitle>EURASIP journal on wireless communications and networking</jtitle><stitle>J Wireless Com Network</stitle><stitle>EURASIP J WIREL COMM</stitle><date>2020-01-21</date><risdate>2020</risdate><volume>2020</volume><issue>1</issue><spage>1</spage><epage>12</epage><pages>1-12</pages><artnum>22</artnum><issn>1687-1472</issn><issn>1687-1499</issn><eissn>1687-1499</eissn><abstract>The performance of centralized and distributed massive MIMO deployments are studied for simulated indoor office scenarios. The distributed deployments use one of the following precoding methods: (1) local precoding with local channel state information (CSI) to the user equipments (UEs) that it serves, (2) large-scale MIMO with local CSI to all UEs in the network, (3) network MIMO with global CSI. For the distributed deployment (3), it is found that using twice as many base station antennas as data streams provides many of the massive MIMO benefits in terms of spectral efficiency and fairness. This is in contrast to the centralized and distributed deployments using (1) or (2) where more antennas are needed. Two main conclusions are that distributing base stations helps to overcome wall penetration loss; however, a backhaul is required to mitigate inter-cell interference. The effect of estimation errors on the performance is also quantified.</abstract><cop>Cham</cop><pub>Springer International Publishing</pub><doi>10.1186/s13638-019-1636-5</doi><tpages>12</tpages><orcidid>https://orcid.org/0000-0003-3142-0967</orcidid><orcidid>https://orcid.org/0000-0002-3904-9181</orcidid><oa>free_for_read</oa></addata></record> |
fulltext | fulltext |
identifier | ISSN: 1687-1472 |
ispartof | EURASIP journal on wireless communications and networking, 2020-01, Vol.2020 (1), p.1-12, Article 22 |
issn | 1687-1472 1687-1499 1687-1499 |
language | eng |
recordid | cdi_proquest_journals_2343522359 |
source | Springer Online Journals Complete; DOAJ Directory of Open Access Journals; Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals; Web of Science - Science Citation Index Expanded - 2020<img src="https://exlibris-pub.s3.amazonaws.com/fromwos-v2.jpg" />; Springer Nature OA/Free Journals |
subjects | Antennas Base station cooperation Communications Engineering Data transmission Engineering Engineering, Electrical & Electronic Indoor communication Information Systems Applications (incl.Internet) Massive MIMO Mobile radio communication Network MIMO Networks Science & Technology Signal,Image and Speech Processing Technology Telecommunications |
title | Information rates of precoding for massive MIMO and base station cooperation in an indoor scenario |
url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-15T17%3A28%3A05IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_webof&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Information%20rates%20of%20precoding%20for%20massive%20MIMO%20and%20base%20station%20cooperation%20in%20an%20indoor%20scenario&rft.jtitle=EURASIP%20journal%20on%20wireless%20communications%20and%20networking&rft.au=Dierks,%20Stefan&rft.date=2020-01-21&rft.volume=2020&rft.issue=1&rft.spage=1&rft.epage=12&rft.pages=1-12&rft.artnum=22&rft.issn=1687-1472&rft.eissn=1687-1499&rft_id=info:doi/10.1186/s13638-019-1636-5&rft_dat=%3Cproquest_webof%3E2343522359%3C/proquest_webof%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2343522359&rft_id=info:pmid/&rft_doaj_id=oai_doaj_org_article_359cd934879541f38b0dbfff15be098c&rfr_iscdi=true |