Reduced-Complexity ML Detection and Capacity-Optimized Training for Spatial Modulation Systems

Spatial Modulation (SM) is a recently developed low-complexity Multiple-Input Multiple-Output scheme that jointly uses antenna indices and a conventional signal set to convey information. It has been shown that the Maximum-Likelihood (ML) detector of an SM system involves joint detection of the tran...

Ausführliche Beschreibung

Gespeichert in:

Bibliographische Detailangaben
Veröffentlicht in:	IEEE transactions on communications Jg. 62; H. 1; S. 112 - 125
Hauptverfasser:	Rajashekar, Rakshith, Hari, K. V. S., Hanzo, L.
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York, NY IEEE 01.01.2014 Institute of Electrical and Electronics Engineers The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Allocations and channel estimation Antennas Applied sciences Channel estimation Codes Communication channels Complexity Computational complexity Detection, estimation, filtering, equalization, prediction Detectors Exact sciences and technology Information, signal and communications theory ML decoding Modulation Modulation, demodulation Optimization Radiocommunications Receivers Searching Signal and communications theory Signal, noise Spatial modulation Systems, networks and services of telecommunications Telecommunications Telecommunications and information theory Training Transmission and modulation (techniques and equipments) Transmitting antennas Wideband communications Performance evaluation MIMO system Parameter estimation Quadrature amplitude modulation Worst case method Measurement sensor ML decoding training Power allocation Computational complexity Information transmission Optimization Maximum likelihood decoding Joint detection Learning Simulation Spatial modulation Optimal allocation Transmitting antenna Channel estimation Maximum likelihood Signal to noise ratio
ISSN:	0090-6778, 1558-0857
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Abstract	Spatial Modulation (SM) is a recently developed low-complexity Multiple-Input Multiple-Output scheme that jointly uses antenna indices and a conventional signal set to convey information. It has been shown that the Maximum-Likelihood (ML) detector of an SM system involves joint detection of the transmit antenna index and of the transmitted symbol, hence, the ML search complexity grows linearly with the number of transmit antennas and the size of the signal set. To circumvent the problem, we show that the ML search complexity of an SM system may be rendered independent of the constellation size, provided that the signal set employed is a square- or a rectangular-QAM. Furthermore, we derive bounds for the capacity of the SM system and derive the optimal power allocation between the data and the training sequences by maximizing the worst-case capacity bound of the SM system operating with imperfect channel state information. We show, with the aid of our simulation results, that the proposed detector is ML-optimal, despite its lowest complexity amongst the existing detectors. Furthermore, we show that employing the proposed optimal power allocation provides a substantial gain in terms of the SM system's capacity as well as signal-to-noise ratio compared to its equal-power-allocation counterpart. Finally, we compare the performance of the SM system to that of the conventional Multiple-Input Multiple-Output (MIMO) system and show that the SM system is capable of outperforming the conventional MIMO system by a significant margin, when both the systems are employing optimal power splitting.
AbstractList	Spatial Modulation (SM) is a recently developed low-complexity Multiple-Input Multiple-Output scheme that jointly uses antenna indices and a conventional signal set to convey information. It has been shown that the Maximum-Likelihood (ML) detector of an SM system involves joint detection of the transmit antenna index and of the transmitted symbol, hence, the ML search complexity grows linearly with the number of transmit antennas and the size of the signal set. To circumvent the problem, we show that the ML search complexity of an SM system may be rendered independent of the constellation size, provided that the signal set employed is a square- or a rectangular-QAM. Furthermore, we derive bounds for the capacity of the SM system and derive the optimal power allocation between the data and the training sequences by maximizing the worst-case capacity bound of the SM system operating with imperfect channel state information. We show, with the aid of our simulation results, that the proposed detector is ML-optimal, despite its lowest complexity amongst the existing detectors. Furthermore, we show that employing the proposed optimal power allocation provides a substantial gain in terms of the SM system's capacity as well as signal-to-noise ratio compared to its equal-power-allocation counterpart. Finally, we compare the performance of the SM system to that of the conventional Multiple-Input Multiple-Output (MIMO) system and show that the SM system is capable of outperforming the conventional MIMO system by a significant margin, when both the systems are employing optimal power splitting.
Author	Hari, K. V. S. Hanzo, L. Rajashekar, Rakshith
Author_xml	– sequence: 1 givenname: Rakshith surname: Rajashekar fullname: Rajashekar, Rakshith email: rakshithmr@ece.iisc.ernet.in organization: Dept. of Electr. Commun. Eng., Indian Inst. of Sci., Bangalore, India – sequence: 2 givenname: K. V. S. surname: Hari fullname: Hari, K. V. S. email: hari@ece.iisc.ernet.in organization: Dept. of Electr. Commun. Eng., Indian Inst. of Sci., Bangalore, India – sequence: 3 givenname: L. surname: Hanzo fullname: Hanzo, L. email: lh@ecs.soton.ac.uk organization: Sch. of ECS, Univ. of Southampton, Southampton, UK
BackLink	http://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=28203662$$DView record in Pascal Francis
BookMark	eNqNkUtr3DAUhUVJoJOkv6AbQyl04-mVZeuxKRSnL5hhIJluK-7I10XBr1oydPrr6xmnXWSV1RXc75wrzrliF13fEWMJhzXnYN7vy912u86AizXPIFuGLuAFW_Gi0On8VhdsBWAglUrpl-wqhAcAyEGIFftxR9XkqErLvh0a-u3jMdlukluK5KLvuwS7KilxQDdv0t0Qfev_UJXsR_Sd734mdT8m9wNGj02y7aupwbPs_hgiteGGXdbYBHr1OK_Z98-f9uXXdLP78q38uEmdUBDTA8esyjkWqKUxRhutCmfQCDgohEpzp3I4iFzmUgqJeU7S6FooJRUZeSBxzd4tvsPY_5ooRNv64KhpsKN-CpZLxSWA4mZG3zxBH_pp7ObfWV5APmdWiGym3j5SGBw29Yid88EOo29xPNpMZyCkPHEfFs6NfQgj1XYO6hxBnBNqLAd7qsmea7KnmuxSk11qmg30E4N_N54hfb1IPRH9l0mpjJBK_AWryqBP
CODEN	IECMBT
CitedBy_id	crossref_primary_10_1109_ACCESS_2019_2949217 crossref_primary_10_1109_JSTSP_2019_2922587 crossref_primary_10_1109_LCOMM_2015_2448616 crossref_primary_10_1109_TCOMM_2020_3021117 crossref_primary_10_1007_s11235_020_00745_y crossref_primary_10_1109_JPHOT_2019_2958272 crossref_primary_10_1109_LWC_2017_2742508 crossref_primary_10_1109_ACCESS_2019_2918710 crossref_primary_10_1109_TCOMM_2018_2851567 crossref_primary_10_1109_LCOMM_2015_2415808 crossref_primary_10_1109_COMST_2018_2815642 crossref_primary_10_1109_TSP_2017_2757907 crossref_primary_10_1016_j_jnca_2018_11_014 crossref_primary_10_1109_TCOMM_2018_2869812 crossref_primary_10_1109_TCOMM_2014_2387171 crossref_primary_10_1109_TWC_2023_3255406 crossref_primary_10_1109_TVT_2015_2477078 crossref_primary_10_1109_TSP_2021_3068848 crossref_primary_10_1109_LCOMM_2020_3033123 crossref_primary_10_1109_TGCN_2023_3262559 crossref_primary_10_1109_TVT_2016_2526628 crossref_primary_10_1109_JIOT_2024_3388321 crossref_primary_10_1109_TSP_2017_2768019 crossref_primary_10_1109_TCOMM_2018_2867528 crossref_primary_10_1109_JSAC_2019_2929380 crossref_primary_10_1109_JSAC_2019_2929381 crossref_primary_10_1109_ACCESS_2017_2694557 crossref_primary_10_1109_TCOMM_2018_2890245 crossref_primary_10_1109_LWC_2017_2753801 crossref_primary_10_1109_TVT_2018_2819025 crossref_primary_10_1007_s42979_025_03793_w crossref_primary_10_1109_ACCESS_2017_2707182 crossref_primary_10_1109_TVT_2015_2430855 crossref_primary_10_1109_TCOMM_2016_2515624 crossref_primary_10_1109_LCOMM_2018_2859938 crossref_primary_10_1109_TCOMM_2020_3013030 crossref_primary_10_1109_TVT_2019_2942634 crossref_primary_10_1109_TVT_2020_3012044 crossref_primary_10_1109_TVT_2022_3141520 crossref_primary_10_1109_LCOMM_2015_2453313 crossref_primary_10_1049_el_2018_1011 crossref_primary_10_1049_el_2015_0262 crossref_primary_10_1109_TVT_2016_2555378 crossref_primary_10_1109_JSAC_2017_2720238 crossref_primary_10_1109_TBC_2017_2731039 crossref_primary_10_1007_s11277_019_06927_5 crossref_primary_10_1109_ACCESS_2017_2762822 crossref_primary_10_1109_OJCOMS_2024_3510535 crossref_primary_10_1109_TCOMM_2017_2740935 crossref_primary_10_1109_LCOMM_2019_2915304 crossref_primary_10_1109_TCSII_2019_2896350 crossref_primary_10_1109_ACCESS_2019_2926063 crossref_primary_10_1007_s11432_021_3333_4 crossref_primary_10_1109_TVT_2016_2536802 crossref_primary_10_1109_ACCESS_2017_2737528 crossref_primary_10_1109_MCOM_023_2300120 crossref_primary_10_1002_dac_5931 crossref_primary_10_1109_TVT_2018_2819728 crossref_primary_10_1109_TVT_2021_3129843 crossref_primary_10_1109_ACCESS_2016_2568040 crossref_primary_10_1109_LWC_2016_2609417 crossref_primary_10_1007_s11276_020_02508_8 crossref_primary_10_1109_TCOMM_2020_2983368 crossref_primary_10_1109_ACCESS_2019_2928033 crossref_primary_10_1109_JSAC_2019_2929450 crossref_primary_10_1109_TCOMM_2019_2924213 crossref_primary_10_1109_TVT_2022_3155244 crossref_primary_10_1109_TWC_2017_2687929 crossref_primary_10_1109_TVT_2017_2774042 crossref_primary_10_1002_dac_3742 crossref_primary_10_3390_fi14050159 crossref_primary_10_1109_COMST_2016_2533580 crossref_primary_10_1109_TVT_2017_2755401 crossref_primary_10_1109_JSAC_2019_2929453 crossref_primary_10_1109_LCOMM_2021_3117844 crossref_primary_10_1109_LCOMM_2017_2734648 crossref_primary_10_1109_JSAC_2017_2698899 crossref_primary_10_1109_TCOMM_2018_2833548 crossref_primary_10_1007_s11277_017_4057_y crossref_primary_10_1109_TVT_2018_2869679 crossref_primary_10_1109_ACCESS_2017_2763978 crossref_primary_10_1109_TWC_2016_2514421 crossref_primary_10_1109_TWC_2016_2645201 crossref_primary_10_1109_ACCESS_2021_3128168 crossref_primary_10_1109_TITS_2023_3326779 crossref_primary_10_1016_j_dsp_2022_103824 crossref_primary_10_1016_j_dsp_2022_103825 crossref_primary_10_1109_ACCESS_2016_2582462 crossref_primary_10_1002_dac_4165 crossref_primary_10_1109_LWC_2019_2953270 crossref_primary_10_1109_LWC_2024_3506578 crossref_primary_10_1109_TCOMM_2018_2796605 crossref_primary_10_1049_cmu2_12572 crossref_primary_10_1109_TVT_2016_2614005 crossref_primary_10_1109_ACCESS_2020_2987055 crossref_primary_10_1109_TCOMM_2019_2918306 crossref_primary_10_1002_dac_3818 crossref_primary_10_1016_j_phycom_2023_102266 crossref_primary_10_1109_TCOMM_2016_2547900 crossref_primary_10_1186_s13638_015_0509_9 crossref_primary_10_1109_LCOMM_2014_2361859 crossref_primary_10_1109_TVT_2021_3063168 crossref_primary_10_1109_TVT_2018_2889024 crossref_primary_10_1109_ACCESS_2019_2959673 crossref_primary_10_1109_TCOMM_2017_2676818 crossref_primary_10_1109_TVT_2016_2558205 crossref_primary_10_1109_TCOMM_2017_2720170 crossref_primary_10_1109_TWC_2017_2752707 crossref_primary_10_1109_TVT_2019_2960591 crossref_primary_10_1109_TVT_2023_3277788 crossref_primary_10_1109_TWC_2017_2713777 crossref_primary_10_1109_ACCESS_2023_3343838 crossref_primary_10_1109_TCOMM_2017_2743166 crossref_primary_10_1109_TWC_2023_3296696 crossref_primary_10_1109_LCOMM_2015_2451615 crossref_primary_10_1109_TWC_2022_3173207 crossref_primary_10_1109_TVT_2018_2814348 crossref_primary_10_1049_cmu2_12564 crossref_primary_10_1109_LCOMM_2014_2331283 crossref_primary_10_1109_JSTSP_2019_2901131 crossref_primary_10_1109_TWC_2015_2497692 crossref_primary_10_1109_ACCESS_2019_2957706 crossref_primary_10_1186_s13638_017_1013_1 crossref_primary_10_1109_TVT_2018_2821684 crossref_primary_10_1109_ACCESS_2022_3217523 crossref_primary_10_1109_LCOMM_2018_2818706 crossref_primary_10_1049_iet_com_2018_6201 crossref_primary_10_1016_j_phycom_2019_04_010 crossref_primary_10_1109_TWC_2021_3054068 crossref_primary_10_1109_JSTSP_2019_2921527 crossref_primary_10_1109_TVT_2017_2757499 crossref_primary_10_1109_JSAC_2018_2872312
Cites_doi	10.1109/LCOMM.2011.111611.111960 10.1090/S0025-5718-1985-0777278-8 10.1109/TVT.2012.2186158 10.1109/TCOMM.2012.021712.100778 10.1109/TIT.2003.809594 10.1109/TCOMM.2013.061013.120547 10.1109/WCL.2012.120312.120601 10.1109/TVT.2007.912136 10.1109/TCOMM.2011.100411.110154 10.1109/CHINACOM.2006.344658 10.1109/TSP.2005.843746 10.1109/icc.2011.5963484 10.1109/LSP.2012.2190059 10.1109/LSP.2012.2221707 10.1109/TCOMM.2012.072412.110857 10.1109/18.771234 10.1109/GLOCOM.2010.5683993 10.1109/LCOMM.2008.080739 10.1109/LCOMM.2011.120211.112026 10.1109/LCOMM.2011.111611.112127 10.1109/LCOMM.2010.06.100163 10.1109/LCOMM.2008.071986 10.1109/TCOMM.2010.093010.090730 10.1109/ISIT.2008.4595475 10.1109/ICC.2004.1313013 10.1109/49.730453 10.1109/MCOM.2011.6094024 10.1109/TIT.2013.2242956 10.1017/CBO9780511807213 10.1109/26.764926 10.1109/ACSSC.2006.354768
ContentType	Journal Article
Copyright	2015 INIST-CNRS Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) Jan 2014
Copyright_xml	– notice: 2015 INIST-CNRS – notice: Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) Jan 2014
DBID	97E RIA RIE AAYXX CITATION IQODW 7SP 8FD L7M F28 FR3
DOI	10.1109/TCOMM.2013.120213.120850
DatabaseName	IEEE Xplore (IEEE) IEEE All-Society Periodicals Package (ASPP) 1998–Present IEEE Electronic Library (IEL) CrossRef Pascal-Francis Electronics & Communications Abstracts Technology Research Database Advanced Technologies Database with Aerospace ANTE: Abstracts in New Technology & Engineering Engineering Research Database
DatabaseTitle	CrossRef Technology Research Database Advanced Technologies Database with Aerospace Electronics & Communications Abstracts Engineering Research Database ANTE: Abstracts in New Technology & Engineering
DatabaseTitleList	Technology Research Database Engineering Research Database
Database_xml	– sequence: 1 dbid: RIE name: IEEE Electronic Library (IEL) url: https://ieeexplore.ieee.org/ sourceTypes: Publisher
DeliveryMethod	fulltext_linktorsrc
Discipline	Engineering Applied Sciences
EISSN	1558-0857
EndPage	125
ExternalDocumentID	3237916731 28203662 10_1109_TCOMM_2013_120213_120850 6679367
Genre	orig-research
GroupedDBID	-~X .DC 0R~ 29I 3EH 4.4 5GY 5VS 6IK 85S 97E AAJGR AARMG AASAJ AAWTH ABAZT ABFSI ABQJQ ABVLG ACGFO ACGFS ACIWK ACKIV ACNCT AENEX AETIX AGQYO AGSQL AHBIQ AI. AIBXA AKJIK AKQYR ALLEH ALMA_UNASSIGNED_HOLDINGS ASUFR ATWAV BEFXN BFFAM BGNUA BKEBE BPEOZ CS3 DU5 E.L EBS EJD HZ~ H~9 IAAWW IBMZZ ICLAB IES IFIPE IFJZH IPLJI JAVBF LAI M43 MS~ O9- OCL P2P RIA RIE RNS TAE TN5 VH1 ZCA ZCG AAYXX CITATION AAYOK IQODW RIG 7SP 8FD L7M F28 FR3
ID	FETCH-LOGICAL-c370t-b1a2d41a5a8699989875c9a930b7a0d81c740b34646636a44e698f37767e96be3
IEDL.DBID	RIE
ISICitedReferencesCount	163
ISICitedReferencesURI	http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=000330622000009&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
ISSN	0090-6778
IngestDate	Sat Sep 27 17:15:47 EDT 2025 Mon Jun 30 10:12:36 EDT 2025 Wed Apr 02 07:26:30 EDT 2025 Sat Nov 29 01:41:33 EST 2025 Tue Nov 18 21:07:04 EST 2025 Wed Aug 27 02:49:10 EDT 2025
IsPeerReviewed	true
IsScholarly	true
Issue	1
Keywords	Performance evaluation MIMO system Parameter estimation Quadrature amplitude modulation Worst case method Measurement sensor ML decoding training Power allocation Computational complexity Information transmission Optimization Maximum likelihood decoding Joint detection Learning Simulation Spatial modulation Optimal allocation Transmitting antenna Channel estimation Maximum likelihood 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-c370t-b1a2d41a5a8699989875c9a930b7a0d81c740b34646636a44e698f37767e96be3
Notes	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23
PQID	1504558532
PQPubID	85472
PageCount	14
ParticipantIDs	crossref_primary_10_1109_TCOMM_2013_120213_120850 proquest_miscellaneous_1671600719 pascalfrancis_primary_28203662 crossref_citationtrail_10_1109_TCOMM_2013_120213_120850 proquest_journals_1504558532 ieee_primary_6679367
PublicationCentury	2000
PublicationDate	2014-January 2014-01-00 2014 20140101
PublicationDateYYYYMMDD	2014-01-01
PublicationDate_xml	– month: 01 year: 2014 text: 2014-January
PublicationDecade	2010
PublicationPlace	New York, NY
PublicationPlace_xml	– name: New York, NY – name: New York
PublicationTitle	IEEE transactions on communications
PublicationTitleAbbrev	TCOMM
PublicationYear	2014
Publisher	IEEE Institute of Electrical and Electronics Engineers The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher_xml	– name: IEEE – name: Institute of Electrical and Electronics Engineers – name: The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
References	ref35 ref34 ref12 ref15 ref36 ref14 ref31 ref30 ref11 ref10 ref2 ref1 ref16 ref19 cover (ref32) 2006 marzetta (ref33) 0 ref24 rajashekar (ref17) 2012 ref23 ref26 ref25 ref20 hassibi (ref13) 0; 2 basar (ref18) 2012; 16 ref22 ref21 ref28 ref29 golub (ref27) 1996 ref8 ref7 ref9 ref4 ref3 ref6 ref5
References_xml	– ident: ref21 doi: 10.1109/LCOMM.2011.111611.111960 – year: 0 ident: ref33 article-title: BLAST training: estimating channel characteristics for high-capacity space-time wireless publication-title: Proc 1999 Allerton Conf Communications Control and Computing – ident: ref10 doi: 10.1090/S0025-5718-1985-0777278-8 – volume: 2 start-page: 1497 year: 0 ident: ref13 article-title: On the expected complexity of integer leastsquares problems publication-title: Proc 2002 IEEE ICASSP – ident: ref4 doi: 10.1109/TVT.2012.2186158 – ident: ref20 doi: 10.1109/TCOMM.2012.021712.100778 – ident: ref28 doi: 10.1109/TIT.2003.809594 – ident: ref16 doi: 10.1109/TCOMM.2013.061013.120547 – year: 1996 ident: ref27 publication-title: Matrix Computations – ident: ref9 doi: 10.1109/WCL.2012.120312.120601 – ident: ref2 doi: 10.1109/TVT.2007.912136 – year: 2006 ident: ref32 publication-title: Elements of Information Theory – ident: ref6 doi: 10.1109/TCOMM.2011.100411.110154 – ident: ref1 doi: 10.1109/CHINACOM.2006.344658 – ident: ref11 doi: 10.1109/TSP.2005.843746 – ident: ref15 doi: 10.1109/icc.2011.5963484 – ident: ref8 doi: 10.1109/LSP.2012.2190059 – ident: ref19 doi: 10.1109/LSP.2012.2221707 – ident: ref22 doi: 10.1109/TCOMM.2012.072412.110857 – ident: ref12 doi: 10.1109/18.771234 – ident: ref14 doi: 10.1109/GLOCOM.2010.5683993 – ident: ref5 doi: 10.1109/LCOMM.2008.080739 – volume: 16 start-page: 176 year: 2012 ident: ref18 article-title: Performance of spatial modulation in the presence of channel estimation errors publication-title: IEEE Commun Lett doi: 10.1109/LCOMM.2011.120211.112026 – ident: ref7 doi: 10.1109/LCOMM.2011.111611.112127 – ident: ref23 doi: 10.1109/LCOMM.2010.06.100163 – ident: ref31 doi: 10.1109/LCOMM.2008.071986 – ident: ref24 doi: 10.1109/TCOMM.2010.093010.090730 – year: 2012 ident: ref17 article-title: Low complexity maximum likelihood detection in spatial modulation systems. – ident: ref30 doi: 10.1109/ISIT.2008.4595475 – ident: ref35 doi: 10.1109/ICC.2004.1313013 – ident: ref36 doi: 10.1109/49.730453 – ident: ref3 doi: 10.1109/MCOM.2011.6094024 – ident: ref25 doi: 10.1109/TIT.2013.2242956 – ident: ref26 doi: 10.1017/CBO9780511807213 – ident: ref34 doi: 10.1109/26.764926 – ident: ref29 doi: 10.1109/ACSSC.2006.354768
SSID	ssj0004033
Score	2.5238178
Snippet	Spatial Modulation (SM) is a recently developed low-complexity Multiple-Input Multiple-Output scheme that jointly uses antenna indices and a conventional...
SourceID	proquest pascalfrancis crossref ieee
SourceType	Aggregation Database Index Database Enrichment Source Publisher
StartPage	112
SubjectTerms	Allocations and channel estimation Antennas Applied sciences Channel estimation Codes Communication channels Complexity Computational complexity Detection, estimation, filtering, equalization, prediction Detectors Exact sciences and technology Information, signal and communications theory ML decoding Modulation Modulation, demodulation Optimization Radiocommunications Receivers Searching Signal and communications theory Signal, noise Spatial modulation Systems, networks and services of telecommunications Telecommunications Telecommunications and information theory Training Transmission and modulation (techniques and equipments) Transmitting antennas Wideband communications
Title	Reduced-Complexity ML Detection and Capacity-Optimized Training for Spatial Modulation Systems
URI	https://ieeexplore.ieee.org/document/6679367 https://www.proquest.com/docview/1504558532 https://www.proquest.com/docview/1671600719
Volume	62
WOSCitedRecordID	wos000330622000009&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
hasFullText	1
inHoldings	1
isFullTextHit
isPrint
journalDatabaseRights	– providerCode: PRVIEE databaseName: IEEE Electronic Library (IEL) customDbUrl: eissn: 1558-0857 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0004033 issn: 0090-6778 databaseCode: RIE dateStart: 19720101 isFulltext: true titleUrlDefault: https://ieeexplore.ieee.org/ providerName: IEEE
link	http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV1Rb9QwDLa2iQf2AIMxcTCmIPFIRnNJk-YRHUx74LZpOqQ9UaWJK02CHtr1kODX46S5MgQP21OrOlGj2IntxPYH8CZgUam2aTkJ8JQrozVvlEVOn3UQDbai9AlswpydVVdX9mIL3o65MIiYgs_wOL6mu_yw9Ot4VBaR-6zUZhu2jdFDrtafHMhC5oqTMZzdVJuoncK-W8zO5_MYxSWPBfn6w6OKmfa3VFHCVomRkW5Fk9MOqBb_bNBJ65w8vt949-BRti7Z-0EcnsAWdk9h91bNwX34chmLtWLgcSeI1TD7n2z-iX3APgVldcx1gc1IhXqi8HPaUb5d_8LAFhlLgpGVyyKQMQkumy9Dhv9iufT5M_h88nExO-UZZIF7aYqeN8JNgxKudJUmY7Gy5MB466wsGuOKUAlvVNFIpRXZJtophdpWrYxFgNDqBuUB7HTLDp8DUw6dC05qTz5j6RVZPhq9KLF15AgbMQGzme_a5wrkEQjja508kcLWiVN15FQ9cKoeODUBMfb8PlThuEOf_ciRsX1mxgSO_mLxSCffk7S5nk7gcMPzOq_nVU1msyrJs5JEfj2SaSXG6xXX4XJNbTT5ntFksy_-_-uX8JCGqYYDnEPY6W_W-Aoe-B_99ermKInzb3YV75c
linkProvider	IEEE
linkToHtml	http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV3db9QwDLfGQGI88DUmDsYIEo9kpJc0aR7RwTTE9YbQIe2JKk1caRL00K6HBH89TpsrQ_AAT63qRI1iJ7YT2z-A5wFFoZq64STAU66M1rxWFjl91iGrscly34NNmMWiOD-373fgxZgLg4h98Bkex9f-Lj-s_CYelUXkPiu1uQbXc6WmYsjW-pUFKWSqORkD2k2xjdsR9uVydlaWMY5LHmfk7Q-PIubaX1FGPbpKjI10a5qeZsC1-GOL7vXOyZ3_G_FduJ3sS_ZqEIh7sIPtfbh1pergPnz6EMu1YuBxL4j1MLvvrJyz19j1YVktc21gM1Kinij8jPaULxc_MLBlQpNgZOeyCGVMosvKVUgAYCwVP38AH0_eLGenPMEscC-N6HiduWlQmctdoclcLCy5MN46K0VtnAhF5o0StVRakXWinVKobdHIWAYIra5RHsBuu2rxITDl0LngpPbkNeZeke2j0Wc5No5cYZNNwGznu_KpBnmEwvhc9b6IsFXPqSpyqho4VQ2cmkA29vw61OH4hz77kSNj-8SMCRz9xuKRTt4n6XM9ncDhludVWtHrigxnlZNvJYn8bCTTWowXLK7F1YbaaPI-o9FmH_3910_h5umynFfzt4t3j2GPhqyG45xD2O0uN_gEbvhv3cX68qgX7Z8SL_Le
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=Reduced-Complexity+ML+Detection+and+Capacity-Optimized+Training+for+Spatial+Modulation+Systems&rft.jtitle=IEEE+transactions+on+communications&rft.au=RAJASHEKAR%2C+Rakshith&rft.au=HARI%2C+K.+V.+S&rft.au=HANZO%2C+L&rft.date=2014&rft.pub=Institute+of+Electrical+and+Electronics+Engineers&rft.issn=0090-6778&rft.volume=62&rft.issue=1&rft.spage=112&rft.epage=125&rft_id=info:doi/10.1109%2FTCOMM.2013.120213.120850&rft.externalDBID=n%2Fa&rft.externalDocID=28203662
thumbnail_l	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=0090-6778&client=summon
thumbnail_m	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=0090-6778&client=summon
thumbnail_s	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=0090-6778&client=summon