New Viewpoint and Algorithms for Water-Filling Solutions in Wireless Communications

Water-filling solutions play an important role in the designs for wireless communications, e.g., transmit covariance matrix design. A traditional physical understanding is to use the analogy of pouring water over a pool with fluctuating bottom. Numerous variants of water-filling solutions have been...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:IEEE transactions on signal processing 2020, Vol.68, p.1618-1634
Hauptverfasser: Xing, Chengwen, Jing, Yindi, Wang, Shuai, Ma, Shaodan, Poor, H. Vincent
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext bestellen
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page 1634
container_issue
container_start_page 1618
container_title IEEE transactions on signal processing
container_volume 68
creator Xing, Chengwen
Jing, Yindi
Wang, Shuai
Ma, Shaodan
Poor, H. Vincent
description Water-filling solutions play an important role in the designs for wireless communications, e.g., transmit covariance matrix design. A traditional physical understanding is to use the analogy of pouring water over a pool with fluctuating bottom. Numerous variants of water-filling solutions have been discovered during the evolution of wireless networks. To obtain the solution values, iterative computations are required, even for simple cases with compact mathematical formulations. Thus, algorithm design is a key issue for the practical use of water-filling solutions, which however has been given marginal attention in the literature. Many existing algorithms are designed on a case-by-case basis for the variations of water-filling solutions and/or with complex logics. In this paper, a new viewpoint for water-filling solutions is proposed to understand the problem dynamically by considering changes in the increasing rates on different subchannels. This fresh viewpoint provides a useful mechanism and fundamental information for finding the optimization solution values. Based on this new understanding, a novel and comprehensive method for practical water-filling algorithm design is proposed, which can be used for systems with various performance metrics and power constraints, even for systems with imperfect channel state information (CSI).
doi_str_mv 10.1109/TSP.2020.2973488
format Article
fullrecord <record><control><sourceid>proquest_RIE</sourceid><recordid>TN_cdi_crossref_primary_10_1109_TSP_2020_2973488</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><ieee_id>8995606</ieee_id><sourcerecordid>2379352087</sourcerecordid><originalsourceid>FETCH-LOGICAL-c399t-b0a9f28e8e54e443db1c7820ebff2a08816aa337a91cf4b8af15488711e38b9b3</originalsourceid><addsrcrecordid>eNo9kE1LAzEQhoMoWKt3wUvA89Z87SY5lmJVKCq0Wm8hu53UlO2mJrsU_71bK55mYJ53hnkQuqZkRCnRd4v564gRRkZMSy6UOkEDqgXNiJDFad-TnGe5kh_n6CKlDSFUCF0M0PwZ9vjdw34XfNNi26zwuF6H6NvPbcIuRLy0LcRs6uvaN2s8D3XX-tAk7Bu89BFqSAlPwnbbNb6yv6NLdOZsneDqrw7R2_R-MXnMZi8PT5PxLKu41m1WEqsdU6AgFyAEX5W0kooRKJ1jlihFC2s5l1bTyolSWUfz_jFJKXBV6pIP0e1x7y6Grw5Sazahi01_0jAuNc8ZUbKnyJGqYkgpgjO76Lc2fhtKzEGd6dWZgzrzp66P3BwjHgD-caV1XpCC_wCZz2r0</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2379352087</pqid></control><display><type>article</type><title>New Viewpoint and Algorithms for Water-Filling Solutions in Wireless Communications</title><source>IEEE Electronic Library (IEL)</source><creator>Xing, Chengwen ; Jing, Yindi ; Wang, Shuai ; Ma, Shaodan ; Poor, H. Vincent</creator><creatorcontrib>Xing, Chengwen ; Jing, Yindi ; Wang, Shuai ; Ma, Shaodan ; Poor, H. Vincent</creatorcontrib><description>Water-filling solutions play an important role in the designs for wireless communications, e.g., transmit covariance matrix design. A traditional physical understanding is to use the analogy of pouring water over a pool with fluctuating bottom. Numerous variants of water-filling solutions have been discovered during the evolution of wireless networks. To obtain the solution values, iterative computations are required, even for simple cases with compact mathematical formulations. Thus, algorithm design is a key issue for the practical use of water-filling solutions, which however has been given marginal attention in the literature. Many existing algorithms are designed on a case-by-case basis for the variations of water-filling solutions and/or with complex logics. In this paper, a new viewpoint for water-filling solutions is proposed to understand the problem dynamically by considering changes in the increasing rates on different subchannels. This fresh viewpoint provides a useful mechanism and fundamental information for finding the optimization solution values. Based on this new understanding, a novel and comprehensive method for practical water-filling algorithm design is proposed, which can be used for systems with various performance metrics and power constraints, even for systems with imperfect channel state information (CSI).</description><identifier>ISSN: 1053-587X</identifier><identifier>EISSN: 1941-0476</identifier><identifier>DOI: 10.1109/TSP.2020.2973488</identifier><identifier>CODEN: ITPRED</identifier><language>eng</language><publisher>New York: IEEE</publisher><subject>Algorithms ; Bottom pouring ; Cases (containers) ; Covariance matrix ; Design ; Heuristic algorithms ; index based algorithm ; Indexes ; Iterative methods ; Matrix methods ; Optimization ; Performance measurement ; Resource management ; Signal processing algorithms ; Water-filling solutions ; Wireless communication ; Wireless communications ; Wireless networks</subject><ispartof>IEEE transactions on signal processing, 2020, Vol.68, p.1618-1634</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2020</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c399t-b0a9f28e8e54e443db1c7820ebff2a08816aa337a91cf4b8af15488711e38b9b3</citedby><cites>FETCH-LOGICAL-c399t-b0a9f28e8e54e443db1c7820ebff2a08816aa337a91cf4b8af15488711e38b9b3</cites><orcidid>0000-0003-0412-6658 ; 0000-0002-2062-131X ; 0000-0002-1381-9678 ; 0000-0001-5521-3650 ; 0000-0002-4081-1954</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/8995606$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>314,780,784,796,4023,27922,27923,27924,54757</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/8995606$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Xing, Chengwen</creatorcontrib><creatorcontrib>Jing, Yindi</creatorcontrib><creatorcontrib>Wang, Shuai</creatorcontrib><creatorcontrib>Ma, Shaodan</creatorcontrib><creatorcontrib>Poor, H. Vincent</creatorcontrib><title>New Viewpoint and Algorithms for Water-Filling Solutions in Wireless Communications</title><title>IEEE transactions on signal processing</title><addtitle>TSP</addtitle><description>Water-filling solutions play an important role in the designs for wireless communications, e.g., transmit covariance matrix design. A traditional physical understanding is to use the analogy of pouring water over a pool with fluctuating bottom. Numerous variants of water-filling solutions have been discovered during the evolution of wireless networks. To obtain the solution values, iterative computations are required, even for simple cases with compact mathematical formulations. Thus, algorithm design is a key issue for the practical use of water-filling solutions, which however has been given marginal attention in the literature. Many existing algorithms are designed on a case-by-case basis for the variations of water-filling solutions and/or with complex logics. In this paper, a new viewpoint for water-filling solutions is proposed to understand the problem dynamically by considering changes in the increasing rates on different subchannels. This fresh viewpoint provides a useful mechanism and fundamental information for finding the optimization solution values. Based on this new understanding, a novel and comprehensive method for practical water-filling algorithm design is proposed, which can be used for systems with various performance metrics and power constraints, even for systems with imperfect channel state information (CSI).</description><subject>Algorithms</subject><subject>Bottom pouring</subject><subject>Cases (containers)</subject><subject>Covariance matrix</subject><subject>Design</subject><subject>Heuristic algorithms</subject><subject>index based algorithm</subject><subject>Indexes</subject><subject>Iterative methods</subject><subject>Matrix methods</subject><subject>Optimization</subject><subject>Performance measurement</subject><subject>Resource management</subject><subject>Signal processing algorithms</subject><subject>Water-filling solutions</subject><subject>Wireless communication</subject><subject>Wireless communications</subject><subject>Wireless networks</subject><issn>1053-587X</issn><issn>1941-0476</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNo9kE1LAzEQhoMoWKt3wUvA89Z87SY5lmJVKCq0Wm8hu53UlO2mJrsU_71bK55mYJ53hnkQuqZkRCnRd4v564gRRkZMSy6UOkEDqgXNiJDFad-TnGe5kh_n6CKlDSFUCF0M0PwZ9vjdw34XfNNi26zwuF6H6NvPbcIuRLy0LcRs6uvaN2s8D3XX-tAk7Bu89BFqSAlPwnbbNb6yv6NLdOZsneDqrw7R2_R-MXnMZi8PT5PxLKu41m1WEqsdU6AgFyAEX5W0kooRKJ1jlihFC2s5l1bTyolSWUfz_jFJKXBV6pIP0e1x7y6Grw5Sazahi01_0jAuNc8ZUbKnyJGqYkgpgjO76Lc2fhtKzEGd6dWZgzrzp66P3BwjHgD-caV1XpCC_wCZz2r0</recordid><startdate>2020</startdate><enddate>2020</enddate><creator>Xing, Chengwen</creator><creator>Jing, Yindi</creator><creator>Wang, Shuai</creator><creator>Ma, Shaodan</creator><creator>Poor, H. Vincent</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. (IEEE)</general><scope>97E</scope><scope>RIA</scope><scope>RIE</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>7SP</scope><scope>8FD</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><orcidid>https://orcid.org/0000-0003-0412-6658</orcidid><orcidid>https://orcid.org/0000-0002-2062-131X</orcidid><orcidid>https://orcid.org/0000-0002-1381-9678</orcidid><orcidid>https://orcid.org/0000-0001-5521-3650</orcidid><orcidid>https://orcid.org/0000-0002-4081-1954</orcidid></search><sort><creationdate>2020</creationdate><title>New Viewpoint and Algorithms for Water-Filling Solutions in Wireless Communications</title><author>Xing, Chengwen ; Jing, Yindi ; Wang, Shuai ; Ma, Shaodan ; Poor, H. Vincent</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c399t-b0a9f28e8e54e443db1c7820ebff2a08816aa337a91cf4b8af15488711e38b9b3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>Algorithms</topic><topic>Bottom pouring</topic><topic>Cases (containers)</topic><topic>Covariance matrix</topic><topic>Design</topic><topic>Heuristic algorithms</topic><topic>index based algorithm</topic><topic>Indexes</topic><topic>Iterative methods</topic><topic>Matrix methods</topic><topic>Optimization</topic><topic>Performance measurement</topic><topic>Resource management</topic><topic>Signal processing algorithms</topic><topic>Water-filling solutions</topic><topic>Wireless communication</topic><topic>Wireless communications</topic><topic>Wireless networks</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Xing, Chengwen</creatorcontrib><creatorcontrib>Jing, Yindi</creatorcontrib><creatorcontrib>Wang, Shuai</creatorcontrib><creatorcontrib>Ma, Shaodan</creatorcontrib><creatorcontrib>Poor, H. Vincent</creatorcontrib><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><collection>Computer and Information Systems Abstracts</collection><collection>Electronics &amp; Communications Abstracts</collection><collection>Technology Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts – Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><jtitle>IEEE transactions on signal processing</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Xing, Chengwen</au><au>Jing, Yindi</au><au>Wang, Shuai</au><au>Ma, Shaodan</au><au>Poor, H. Vincent</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>New Viewpoint and Algorithms for Water-Filling Solutions in Wireless Communications</atitle><jtitle>IEEE transactions on signal processing</jtitle><stitle>TSP</stitle><date>2020</date><risdate>2020</risdate><volume>68</volume><spage>1618</spage><epage>1634</epage><pages>1618-1634</pages><issn>1053-587X</issn><eissn>1941-0476</eissn><coden>ITPRED</coden><abstract>Water-filling solutions play an important role in the designs for wireless communications, e.g., transmit covariance matrix design. A traditional physical understanding is to use the analogy of pouring water over a pool with fluctuating bottom. Numerous variants of water-filling solutions have been discovered during the evolution of wireless networks. To obtain the solution values, iterative computations are required, even for simple cases with compact mathematical formulations. Thus, algorithm design is a key issue for the practical use of water-filling solutions, which however has been given marginal attention in the literature. Many existing algorithms are designed on a case-by-case basis for the variations of water-filling solutions and/or with complex logics. In this paper, a new viewpoint for water-filling solutions is proposed to understand the problem dynamically by considering changes in the increasing rates on different subchannels. This fresh viewpoint provides a useful mechanism and fundamental information for finding the optimization solution values. Based on this new understanding, a novel and comprehensive method for practical water-filling algorithm design is proposed, which can be used for systems with various performance metrics and power constraints, even for systems with imperfect channel state information (CSI).</abstract><cop>New York</cop><pub>IEEE</pub><doi>10.1109/TSP.2020.2973488</doi><tpages>17</tpages><orcidid>https://orcid.org/0000-0003-0412-6658</orcidid><orcidid>https://orcid.org/0000-0002-2062-131X</orcidid><orcidid>https://orcid.org/0000-0002-1381-9678</orcidid><orcidid>https://orcid.org/0000-0001-5521-3650</orcidid><orcidid>https://orcid.org/0000-0002-4081-1954</orcidid><oa>free_for_read</oa></addata></record>
fulltext fulltext_linktorsrc
identifier ISSN: 1053-587X
ispartof IEEE transactions on signal processing, 2020, Vol.68, p.1618-1634
issn 1053-587X
1941-0476
language eng
recordid cdi_crossref_primary_10_1109_TSP_2020_2973488
source IEEE Electronic Library (IEL)
subjects Algorithms
Bottom pouring
Cases (containers)
Covariance matrix
Design
Heuristic algorithms
index based algorithm
Indexes
Iterative methods
Matrix methods
Optimization
Performance measurement
Resource management
Signal processing algorithms
Water-filling solutions
Wireless communication
Wireless communications
Wireless networks
title New Viewpoint and Algorithms for Water-Filling Solutions in Wireless Communications
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-08T17%3A25%3A14IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_RIE&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=New%20Viewpoint%20and%20Algorithms%20for%20Water-Filling%20Solutions%20in%20Wireless%20Communications&rft.jtitle=IEEE%20transactions%20on%20signal%20processing&rft.au=Xing,%20Chengwen&rft.date=2020&rft.volume=68&rft.spage=1618&rft.epage=1634&rft.pages=1618-1634&rft.issn=1053-587X&rft.eissn=1941-0476&rft.coden=ITPRED&rft_id=info:doi/10.1109/TSP.2020.2973488&rft_dat=%3Cproquest_RIE%3E2379352087%3C/proquest_RIE%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2379352087&rft_id=info:pmid/&rft_ieee_id=8995606&rfr_iscdi=true