Low-Complexity Distributed Beamforming for Relay Networks With Real-Valued Implementation
The distributed beamforming problem for amplify-and-forward relay networks is studied. Maximizing output SNR (signal-to-noise ratio) for distributed beamforming can be considered as a generalized eigenvector problem (GEP) and the principal eigenvector and its eigenvalue can be derived with a standar...
Saved in:
| Published in | IEEE transactions on signal processing Vol. 61; no. 20; pp. 5039 - 5048 |
|---|---|
| Main Authors | , , |
| Format | Journal Article |
| Language | English |
| Published |
New York, NY
IEEE
01.10.2013
Institute of Electrical and Electronics Engineers |
| Subjects | |
| Online Access | Get full text |
| ISSN | 1053-587X 1941-0476 |
| DOI | 10.1109/TSP.2013.2274957 |
Cover
Loading…
| Abstract | The distributed beamforming problem for amplify-and-forward relay networks is studied. Maximizing output SNR (signal-to-noise ratio) for distributed beamforming can be considered as a generalized eigenvector problem (GEP) and the principal eigenvector and its eigenvalue can be derived with a standard closed-form solution. In this paper, four classes of beamforming algorithms are derived based on different design criteria and constraints, including maximizing output SNR subject to a constraint on the total transmitted signal power, minimizing the total transmitted signal power subject to certain level of output SNR, minimizing the relay node number subject to constraints on the total signal power and output SNR, and a robust algorithm to deal with channel estimation errors. All of the algorithms have a low computational complexity due to the proposed real-valued implementation. |
|---|---|
| AbstractList | The distributed beamforming problem for amplify-and-forward relay networks is studied. Maximizing output SNR (signal-to-noise ratio) for distributed beamforming can be considered as a generalized eigenvector problem (GEP) and the principal eigenvector and its eigenvalue can be derived with a standard closed-form solution. In this paper, four classes of beamforming algorithms are derived based on different design criteria and constraints, including maximizing output SNR subject to a constraint on the total transmitted signal power, minimizing the total transmitted signal power subject to certain level of output SNR, minimizing the relay node number subject to constraints on the total signal power and output SNR, and a robust algorithm to deal with channel estimation errors. All of the algorithms have a low computational complexity due to the proposed real-valued implementation. |
| Author | Wei Liu Jian Li Lei Zhang |
| Author_xml | – sequence: 1 givenname: Lei surname: Zhang fullname: Zhang, Lei – sequence: 2 givenname: Wei surname: Liu fullname: Liu, Wei – sequence: 3 givenname: Jian surname: Li fullname: Li, Jian |
| BackLink | http://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=27783929$$DView record in Pascal Francis |
| BookMark | eNp9kDlPAzEQhS0UJJJAj0SzDeUGX7telxCuSBEgCFdl2Y4Nhj0i21HIv2ejDRQUVDMavfdm5huAXt3UBoBDBEcIQX4ye7gbYYjICGNGecZ2QB9xilJIWd5re5iRNCvYyx4YhPABIaKU533wOm1W6bipFqX5cnGdnLsQvVPLaObJmZGVbXzl6rekrcm9KeU6uTFx1fjPkDy7-N7OZJk-yXLZ6ieblMrUUUbX1Ptg18oymINtHYLHy4vZ-Dqd3l5NxqfTVGNOYqpzqyG2VFJFcUbJXOYYFlQaCimfE8mZsYxCixSkWV4opbXMFTJYZQpbjckQHHe5Cxm0LK2XtXZBLLyrpF8LzFhBeLtqCPJOp30TgjdWaNddGr10pUBQbECKFqTYgBRbkK0R_jH-ZP9jOeoszhjzK88z1v7EyDelgYGr |
| CODEN | ITPRED |
| CitedBy_id | crossref_primary_10_1109_ACCESS_2016_2604341 crossref_primary_10_1109_TSIPN_2015_2463076 crossref_primary_10_1109_TCOMM_2021_3109271 crossref_primary_10_1109_TSP_2019_2954519 crossref_primary_10_1109_TVT_2014_2311472 crossref_primary_10_1109_TWC_2016_2517629 crossref_primary_10_1109_ACCESS_2017_2768436 crossref_primary_10_1109_ACCESS_2017_2774143 crossref_primary_10_1109_JSYST_2018_2869853 |
| Cites_doi | 10.1109/TIT.2009.2034786 10.1109/LCOMM.2011.011811.101720 10.1109/LSP.2010.2096466 10.1109/JSAC.2007.070219 10.1109/TSP.2009.2020002 10.1109/TWC.2007.05227 10.1109/TSP.2009.2026067 10.1109/MCOM.2009.4785387 10.1109/TIT.2009.2018175 10.1109/TSP.2011.2109957 10.1109/TCOMM.2003.818096 10.1109/TSP.2007.894410 10.1109/LCOMM.2011.012511.102156 10.1109/TSP.2008.925945 10.1109/TSP.2003.821100 10.1109/TSP.2008.923806 10.1109/TWC.2007.360377 10.1109/TVT.2008.923668 10.1109/TIT.2003.817829 10.1002/9780470661178 10.1109/TCOMM.2011.030411.100158 |
| ContentType | Journal Article |
| Copyright | 2014 INIST-CNRS |
| Copyright_xml | – notice: 2014 INIST-CNRS |
| DBID | 97E RIA RIE AAYXX CITATION IQODW |
| DOI | 10.1109/TSP.2013.2274957 |
| DatabaseName | IEEE Xplore (IEEE) IEEE All-Society Periodicals Package (ASPP) 1998–Present IEEE Electronic Library (IEL) CrossRef Pascal-Francis |
| DatabaseTitle | CrossRef |
| DatabaseTitleList | |
| Database_xml | – sequence: 1 dbid: RIE name: IEEE Electronic Library (IEL) url: https://proxy.k.utb.cz/login?url=https://ieeexplore.ieee.org/ sourceTypes: Publisher |
| DeliveryMethod | fulltext_linktorsrc |
| Discipline | Engineering Applied Sciences |
| EISSN | 1941-0476 |
| EndPage | 5048 |
| ExternalDocumentID | 27783929 10_1109_TSP_2013_2274957 6570497 |
| Genre | orig-research |
| GroupedDBID | -~X .DC 0R~ 29I 4.4 5GY 6IK 85S 97E AAJGR AARMG AASAJ AAWTH ABAZT ABQJQ ABVLG ACGFO ACIWK ACNCT AENEX AGQYO AGSQL AHBIQ AJQPL AKQYR ALMA_UNASSIGNED_HOLDINGS ASUFR ATWAV BEFXN BFFAM BGNUA BKEBE BPEOZ CS3 E.L EBS EJD F5P HZ~ IFIPE IPLJI JAVBF LAI MS~ O9- OCL P2P RIA RIE RNS TAE TN5 3EH 53G 5VS AAYOK AAYXX ABFSI ACKIV AETIX AI. AIBXA AKJIK ALLEH CITATION H~9 ICLAB IFJZH RIG VH1 IQODW |
| ID | FETCH-LOGICAL-c293t-c6fc02f4a4b42543da62084ae4049d3a97ef740f1b04568bbcca6b1e2b5b2fc23 |
| IEDL.DBID | RIE |
| ISSN | 1053-587X |
| IngestDate | Mon Jul 21 09:10:51 EDT 2025 Tue Jul 01 02:53:01 EDT 2025 Thu Apr 24 22:51:28 EDT 2025 Tue Aug 26 16:46:28 EDT 2025 |
| IsPeerReviewed | true |
| IsScholarly | true |
| Issue | 20 |
| Keywords | Estimation error Parameter estimation Relay Relay network Eigenvector Transmission protocol Eigenvalue Distributed beamforming relay networks Output signal Closed form equation Algorithm Computational complexity Beam forming Implementation robust algorithm generalized eigenvector problem Channel estimation Signal processing Routing protocols Signal to noise ratio |
| Language | English |
| License | https://ieeexplore.ieee.org/Xplorehelp/downloads/license-information/IEEE.html CC BY 4.0 |
| LinkModel | DirectLink |
| MergedId | FETCHMERGED-LOGICAL-c293t-c6fc02f4a4b42543da62084ae4049d3a97ef740f1b04568bbcca6b1e2b5b2fc23 |
| PageCount | 10 |
| ParticipantIDs | crossref_primary_10_1109_TSP_2013_2274957 pascalfrancis_primary_27783929 crossref_citationtrail_10_1109_TSP_2013_2274957 ieee_primary_6570497 |
| ProviderPackageCode | CITATION AAYXX |
| PublicationCentury | 2000 |
| PublicationDate | 2013-10-01 |
| PublicationDateYYYYMMDD | 2013-10-01 |
| PublicationDate_xml | – month: 10 year: 2013 text: 2013-10-01 day: 01 |
| PublicationDecade | 2010 |
| PublicationPlace | New York, NY |
| PublicationPlace_xml | – name: New York, NY |
| PublicationTitle | IEEE transactions on signal processing |
| PublicationTitleAbbrev | TSP |
| PublicationYear | 2013 |
| Publisher | IEEE Institute of Electrical and Electronics Engineers |
| Publisher_xml | – name: IEEE – name: Institute of Electrical and Electronics Engineers |
| References | ref13 ref24 ref12 ref23 ref15 ref14 ref20 ref11 ref10 ref21 ref2 ref1 ref17 ref16 ref19 ref18 ref8 ref7 ref9 ref4 ref3 ref6 zhang (ref5) 2012 golub (ref22) 1996 |
| References_xml | – ident: ref4 doi: 10.1109/TIT.2009.2034786 – ident: ref14 doi: 10.1109/LCOMM.2011.011811.101720 – ident: ref8 doi: 10.1109/LSP.2010.2096466 – ident: ref2 doi: 10.1109/JSAC.2007.070219 – ident: ref20 doi: 10.1109/TSP.2009.2020002 – ident: ref10 doi: 10.1109/TWC.2007.05227 – ident: ref19 doi: 10.1109/TSP.2009.2026067 – ident: ref1 doi: 10.1109/MCOM.2009.4785387 – ident: ref13 doi: 10.1109/TIT.2009.2018175 – ident: ref24 doi: 10.1109/TSP.2011.2109957 – start-page: 338 year: 2012 ident: ref5 article-title: A reference signal based beamforming scheme for relay networks with local channel state information publication-title: Proc Int ICST Conf Commun Netw China – ident: ref7 doi: 10.1109/TCOMM.2003.818096 – ident: ref15 doi: 10.1109/TSP.2007.894410 – ident: ref17 doi: 10.1109/LCOMM.2011.012511.102156 – ident: ref6 doi: 10.1109/TCOMM.2003.818096 – ident: ref18 doi: 10.1109/TSP.2008.925945 – ident: ref12 doi: 10.1109/TSP.2003.821100 – ident: ref9 doi: 10.1109/TSP.2008.923806 – ident: ref3 doi: 10.1109/TWC.2007.360377 – ident: ref21 doi: 10.1109/TVT.2008.923668 – ident: ref11 doi: 10.1109/TIT.2003.817829 – ident: ref23 doi: 10.1002/9780470661178 – ident: ref16 doi: 10.1109/TCOMM.2011.030411.100158 – year: 1996 ident: ref22 publication-title: Matrix Computations |
| SSID | ssj0014496 |
| Score | 2.1960042 |
| Snippet | The distributed beamforming problem for amplify-and-forward relay networks is studied. Maximizing output SNR (signal-to-noise ratio) for distributed... |
| SourceID | pascalfrancis crossref ieee |
| SourceType | Index Database Enrichment Source Publisher |
| StartPage | 5039 |
| SubjectTerms | Algorithm design and analysis Applied sciences Array signal processing Detection, estimation, filtering, equalization, prediction Distributed beamforming Exact sciences and technology generalized eigenvector problem Information, signal and communications theory Peer-to-peer computing relay networks Relays robust algorithm Robustness Signal and communications theory Signal to noise ratio Signal, noise Telecommunications and information theory |
| Title | Low-Complexity Distributed Beamforming for Relay Networks With Real-Valued Implementation |
| URI | https://ieeexplore.ieee.org/document/6570497 |
| Volume | 61 |
| hasFullText | 1 |
| inHoldings | 1 |
| isFullTextHit | |
| isPrint | |
| link | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwjV1LS8QwEB7Ukx58i-uLHrwIZjdN06Y9-mQRFcFdXU8lSRMU9yHaRfTXm2m7ZRURTy3tpA0zQ2fSfPMNwH7MuPUlpURTFRKumE9k6GuipOaZZC5gBljgfHUdtbv8ohf2ZuCwroUxxhTgM9PE02IvPxvpMf4qayFMgydiFmbdwq2s1ap3DDgvenG5dCEgYSx6ky1JmrQ6tzeI4Qqa7tVuPSC-haCipwoiIuWbU4otu1lMhZjzJbiaTK5Eljw3x7lq6s8fvI3_nf0yLFa5pndUOscKzJjhKixMMRCuwcPl6J3gNwF5MfMP7xR5dLEFlsm8YyMHmNI6Qc8dPcTNfXjXJW78zbt_yh_dNdknd7I_dvIF0fCgqmUarkP3_Kxz0iZVtwWiXcjPiY6spsxyyRXHCvlMRozGXBruZp0FMhHGCk6trzALjJVyto-Ub5gKFbOaBRswNxwNzSZ4NuA0Y4wKnSRcxEomOnJuEMWRZYFJRANaEwOkuqIix44Y_bRYktAkdSZL0WRpZbIGHNQjXkoajj9k11D5tVyl9wbsfbNxfZ8JUWSJW7-P24Z5fHoJ4NuBufx1bHZdIpKrvcIDvwCKc9ru |
| linkProvider | IEEE |
| linkToHtml | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwjV1LT-MwEB6xcIA98EaU5ZEDF6R16zhOnBx5quy2FdIWKKfIdmyBtrQIUq3g1-NJ0ggQQntKlIzlkWeUGcfffAOwHzNufUkp0VSFhCvmExn6miipeSaZC5gBFjh3e1H7kv8ahIMZ-FnXwhhjCvCZaeJtcZafjfUEf5W1EKbBE_EN5lzcD_2yWqs-M-C86MblEoaAhLEYTA8ladLq_7lAFFfQdJO7HYF4F4SKriqIiZRPblls2c_iTZA5W4LuVL0SW_K3OclVU798YG78X_2XYbHKNr3D0j1WYMaMVuH7Gw7CNbjpjP8R_CogM2b-7J0gky42wTKZd2TkPSa1TtBzVw-Rc89er0SOP3nXd_mteyaH5EoOJ06-oBq-r6qZRutweXbaP26Tqt8C0S7o50RHVlNmueSKY418JiNGYy4Nd1pngUyEsYJT6yvMA2OlnPUj5RumQsWsZsEGzI7GI7MJng04zRijQicJF7GSiY6cI0RxZFlgEtGA1tQAqa7IyLEnxjAtNiU0SZ3JUjRZWpmsAQf1iIeSiOML2TVc_FquWvcG7L6zcf2eCVHkiVufj9uD-Xa_20k7573fP2ABZyrhfNswmz9OzI5LS3K1W3jjKx5L3jc |
| openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Low-Complexity+Distributed+Beamforming+for+Relay+Networks+With+Real-Valued+Implementation&rft.jtitle=IEEE+transactions+on+signal+processing&rft.au=Lei+Zhang&rft.au=Wei+Liu&rft.au=Jian+Li&rft.date=2013-10-01&rft.pub=IEEE&rft.issn=1053-587X&rft.volume=61&rft.issue=20&rft.spage=5039&rft.epage=5048&rft_id=info:doi/10.1109%2FTSP.2013.2274957&rft.externalDocID=6570497 |
| thumbnail_l | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=1053-587X&client=summon |
| thumbnail_m | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=1053-587X&client=summon |
| thumbnail_s | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=1053-587X&client=summon |