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Silicon complexity for maximum likelihood MIMO detection using spherical decoding
Multiple-input multiple-output (MIMO) wireless systems increase spectral efficiency by transmitting independent signals on multiple transmit antennas in the same channel bandwidth. The key to using MIMO is in building a receiver that can decorrelate the spatial signatures on the receiver antenna arr...
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Published in: | IEEE journal of solid-state circuits 2004-09, Vol.39 (9), p.1544-1552 |
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container_end_page | 1552 |
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container_title | IEEE journal of solid-state circuits |
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creator | Garrett, D. Davis, L. ten Brink, S. Hochwald, B. Knagge, G. |
description | Multiple-input multiple-output (MIMO) wireless systems increase spectral efficiency by transmitting independent signals on multiple transmit antennas in the same channel bandwidth. The key to using MIMO is in building a receiver that can decorrelate the spatial signatures on the receiver antenna array. Original MIMO detection schemes such as the vertical Bell Labs layered space-time (VBLAST) detector use a nulling and cancellation process for detection that is sub-optimal as compared to constrained maximum likelihood (ML) techniques. This paper presents a silicon complexity analysis of ML search techniques for MIMO as applied to the HSDPA extension of UMTS. For MIMO constellations of 4/spl times/4 QPSK or lower, it is possible to perform an exhaustive ML search in today's silicon technologies. When the search complexity exceeds technology limits for high complexity MIMO constellations, it is possible to apply spherical decoding techniques to achieve near-ML performance. The paper presents an architecture for a 4/spl times/4 16QAM MIMO spherical decoder with soft outputs that achieves 38.8 Mb/s over a 5-MHz channel using only approximately 10 mm/sup 2/ in a 0.18-/spl mu/m CMOS process. |
doi_str_mv | 10.1109/JSSC.2004.831454 |
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The key to using MIMO is in building a receiver that can decorrelate the spatial signatures on the receiver antenna array. Original MIMO detection schemes such as the vertical Bell Labs layered space-time (VBLAST) detector use a nulling and cancellation process for detection that is sub-optimal as compared to constrained maximum likelihood (ML) techniques. This paper presents a silicon complexity analysis of ML search techniques for MIMO as applied to the HSDPA extension of UMTS. For MIMO constellations of 4/spl times/4 QPSK or lower, it is possible to perform an exhaustive ML search in today's silicon technologies. When the search complexity exceeds technology limits for high complexity MIMO constellations, it is possible to apply spherical decoding techniques to achieve near-ML performance. The paper presents an architecture for a 4/spl times/4 16QAM MIMO spherical decoder with soft outputs that achieves 38.8 Mb/s over a 5-MHz channel using only approximately 10 mm/sup 2/ in a 0.18-/spl mu/m CMOS process.</description><identifier>ISSN: 0018-9200</identifier><identifier>EISSN: 1558-173X</identifier><identifier>DOI: 10.1109/JSSC.2004.831454</identifier><identifier>CODEN: IJSCBC</identifier><language>eng</language><publisher>New York, NY: IEEE</publisher><subject>Antenna arrays ; Applied sciences ; Bandwidth ; Channels ; Complexity ; Constellations ; Decoding ; Decorrelation ; Design. Technologies. Operation analysis. Testing ; Detectors ; Electronics ; Exact sciences and technology ; Integrated circuits ; Maximum likelihood decoding ; Maximum likelihood detection ; MIMO ; Receivers ; Receiving antennas ; Searching ; Semiconductor electronics. Microelectronics. Optoelectronics. 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(IEEE) 2004</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c447t-71a8764b4da152d47767e672bd2e6f355ecf0537f38bb8c562f59318b8f84dab3</citedby><cites>FETCH-LOGICAL-c447t-71a8764b4da152d47767e672bd2e6f355ecf0537f38bb8c562f59318b8f84dab3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/1327753$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>314,780,784,27924,27925,54796</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=16171103$$DView record in Pascal Francis$$Hfree_for_read</backlink></links><search><creatorcontrib>Garrett, D.</creatorcontrib><creatorcontrib>Davis, L.</creatorcontrib><creatorcontrib>ten Brink, S.</creatorcontrib><creatorcontrib>Hochwald, B.</creatorcontrib><creatorcontrib>Knagge, G.</creatorcontrib><title>Silicon complexity for maximum likelihood MIMO detection using spherical decoding</title><title>IEEE journal of solid-state circuits</title><addtitle>JSSC</addtitle><description>Multiple-input multiple-output (MIMO) wireless systems increase spectral efficiency by transmitting independent signals on multiple transmit antennas in the same channel bandwidth. The key to using MIMO is in building a receiver that can decorrelate the spatial signatures on the receiver antenna array. Original MIMO detection schemes such as the vertical Bell Labs layered space-time (VBLAST) detector use a nulling and cancellation process for detection that is sub-optimal as compared to constrained maximum likelihood (ML) techniques. This paper presents a silicon complexity analysis of ML search techniques for MIMO as applied to the HSDPA extension of UMTS. For MIMO constellations of 4/spl times/4 QPSK or lower, it is possible to perform an exhaustive ML search in today's silicon technologies. When the search complexity exceeds technology limits for high complexity MIMO constellations, it is possible to apply spherical decoding techniques to achieve near-ML performance. The paper presents an architecture for a 4/spl times/4 16QAM MIMO spherical decoder with soft outputs that achieves 38.8 Mb/s over a 5-MHz channel using only approximately 10 mm/sup 2/ in a 0.18-/spl mu/m CMOS process.</description><subject>Antenna arrays</subject><subject>Applied sciences</subject><subject>Bandwidth</subject><subject>Channels</subject><subject>Complexity</subject><subject>Constellations</subject><subject>Decoding</subject><subject>Decorrelation</subject><subject>Design. Technologies. Operation analysis. Testing</subject><subject>Detectors</subject><subject>Electronics</subject><subject>Exact sciences and technology</subject><subject>Integrated circuits</subject><subject>Maximum likelihood decoding</subject><subject>Maximum likelihood detection</subject><subject>MIMO</subject><subject>Receivers</subject><subject>Receiving antennas</subject><subject>Searching</subject><subject>Semiconductor electronics. Microelectronics. Optoelectronics. Solid state devices</subject><subject>Silicon</subject><subject>Studies</subject><subject>Transmitting antennas</subject><issn>0018-9200</issn><issn>1558-173X</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2004</creationdate><recordtype>article</recordtype><recordid>eNp9kUtLAzEUhYMoWB97wc0gqKupeU4ySyk-KopIFdyFTCax0ZlJTWag_femtCC4cHXJPd-53NwDwAmCY4RgefUwm03GGEI6FgRRRnfACDEmcsTJ-y4YQYhEXiZ9HxzE-JmelAo0Ai8z1zjtu0z7dtGYpetXmfUha9XStUObNe7LNG7ufZ09TZ-es9r0RvcuGYbouo8sLuYmOK2apGhfp9YR2LOqieZ4Ww_B2-3N6-Q-f3y-m06uH3NNKe9zjpTgBa1orRDDNeW84KbguKqxKSxhzGgLGeGWiKoSmhXYspIgUQkrkqcih-ByM3cR_PdgYi9bF7VpGtUZP0QpygJDhjhM5MW_JBasSKfiCTz7A376IXTpF7LEKO0kqEgQ3EA6-BiDsXIRXKvCSiIo11HIdRRyHYXcRJEs59u5KqZT2aA67eKvr0A8GUniTjecM8b8ygRzzgj5AZTAkT4</recordid><startdate>20040901</startdate><enddate>20040901</enddate><creator>Garrett, D.</creator><creator>Davis, L.</creator><creator>ten Brink, S.</creator><creator>Hochwald, B.</creator><creator>Knagge, G.</creator><general>IEEE</general><general>Institute of Electrical and Electronics Engineers</general><general>The Institute of Electrical and Electronics Engineers, Inc. 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Testing</topic><topic>Detectors</topic><topic>Electronics</topic><topic>Exact sciences and technology</topic><topic>Integrated circuits</topic><topic>Maximum likelihood decoding</topic><topic>Maximum likelihood detection</topic><topic>MIMO</topic><topic>Receivers</topic><topic>Receiving antennas</topic><topic>Searching</topic><topic>Semiconductor electronics. Microelectronics. Optoelectronics. Solid state devices</topic><topic>Silicon</topic><topic>Studies</topic><topic>Transmitting antennas</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Garrett, D.</creatorcontrib><creatorcontrib>Davis, L.</creatorcontrib><creatorcontrib>ten Brink, S.</creatorcontrib><creatorcontrib>Hochwald, B.</creatorcontrib><creatorcontrib>Knagge, G.</creatorcontrib><collection>IEEE All-Society Periodicals Package (ASPP) 1998-Present</collection><collection>IEEE Electronic Library Online</collection><collection>Pascal-Francis</collection><collection>CrossRef</collection><collection>Electronics & Communications Abstracts</collection><collection>Technology Research Database</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>ANTE: Abstracts in New Technology & Engineering</collection><collection>Engineering Research Database</collection><jtitle>IEEE journal of solid-state circuits</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Garrett, D.</au><au>Davis, L.</au><au>ten Brink, S.</au><au>Hochwald, B.</au><au>Knagge, G.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Silicon complexity for maximum likelihood MIMO detection using spherical decoding</atitle><jtitle>IEEE journal of solid-state circuits</jtitle><stitle>JSSC</stitle><date>2004-09-01</date><risdate>2004</risdate><volume>39</volume><issue>9</issue><spage>1544</spage><epage>1552</epage><pages>1544-1552</pages><issn>0018-9200</issn><eissn>1558-173X</eissn><coden>IJSCBC</coden><abstract>Multiple-input multiple-output (MIMO) wireless systems increase spectral efficiency by transmitting independent signals on multiple transmit antennas in the same channel bandwidth. The key to using MIMO is in building a receiver that can decorrelate the spatial signatures on the receiver antenna array. Original MIMO detection schemes such as the vertical Bell Labs layered space-time (VBLAST) detector use a nulling and cancellation process for detection that is sub-optimal as compared to constrained maximum likelihood (ML) techniques. This paper presents a silicon complexity analysis of ML search techniques for MIMO as applied to the HSDPA extension of UMTS. For MIMO constellations of 4/spl times/4 QPSK or lower, it is possible to perform an exhaustive ML search in today's silicon technologies. When the search complexity exceeds technology limits for high complexity MIMO constellations, it is possible to apply spherical decoding techniques to achieve near-ML performance. The paper presents an architecture for a 4/spl times/4 16QAM MIMO spherical decoder with soft outputs that achieves 38.8 Mb/s over a 5-MHz channel using only approximately 10 mm/sup 2/ in a 0.18-/spl mu/m CMOS process.</abstract><cop>New York, NY</cop><pub>IEEE</pub><doi>10.1109/JSSC.2004.831454</doi><tpages>9</tpages></addata></record> |
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subjects | Antenna arrays Applied sciences Bandwidth Channels Complexity Constellations Decoding Decorrelation Design. Technologies. Operation analysis. Testing Detectors Electronics Exact sciences and technology Integrated circuits Maximum likelihood decoding Maximum likelihood detection MIMO Receivers Receiving antennas Searching Semiconductor electronics. Microelectronics. Optoelectronics. Solid state devices Silicon Studies Transmitting antennas |
title | Silicon complexity for maximum likelihood MIMO detection using spherical decoding |
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