Gaussian Approximation-Based Belief Propagation Receiver for Uplink SCMA Systems With Imperfect CSIR
For uplink sparse code multiple access (SCMA) systems, a channel estimation is required to support a multi-user detection in practice. Motivated by the conventional detection, called a Gaussian approximation-based belief propagation (GA-BP) with matched filtering, we propose an efficient receiver su...
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Veröffentlicht in: | IEEE communications letters 2018-12, Vol.22 (12), p.2611-2614 |
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description | For uplink sparse code multiple access (SCMA) systems, a channel estimation is required to support a multi-user detection in practice. Motivated by the conventional detection, called a Gaussian approximation-based belief propagation (GA-BP) with matched filtering, we propose an efficient receiver suitable for the uplink SCMA systems when exact channel state information is not available. By estimating matched filtered channels (rather than explicitly estimating actual channels), the proposed methods efficiently support the second-stage GA-BP detector with negligible increment of complexity. The simulation results show that the proposed receiver achieves the similar estimation and detection performance to the state-of-the-art receiver while the required complexity can be drastically reduced. |
doi_str_mv | 10.1109/LCOMM.2018.2874441 |
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Motivated by the conventional detection, called a Gaussian approximation-based belief propagation (GA-BP) with matched filtering, we propose an efficient receiver suitable for the uplink SCMA systems when exact channel state information is not available. By estimating matched filtered channels (rather than explicitly estimating actual channels), the proposed methods efficiently support the second-stage GA-BP detector with negligible increment of complexity. The simulation results show that the proposed receiver achieves the similar estimation and detection performance to the state-of-the-art receiver while the required complexity can be drastically reduced.</description><identifier>ISSN: 1089-7798</identifier><identifier>EISSN: 1558-2558</identifier><identifier>DOI: 10.1109/LCOMM.2018.2874441</identifier><identifier>CODEN: ICLEF6</identifier><language>eng</language><publisher>New York: IEEE</publisher><subject>Approximation ; belief propagation ; Channel estimation ; Channels ; Complexity ; Complexity theory ; Detectors ; Estimation ; Filtration ; Gaussian approximation ; Guassian processes ; Mathematical analysis ; multi-user detection ; Propagation ; Receivers ; Sparse code multiple access ; Sparse matrices ; State of the art ; Uplink</subject><ispartof>IEEE communications letters, 2018-12, Vol.22 (12), p.2611-2614</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. 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The simulation results show that the proposed receiver achieves the similar estimation and detection performance to the state-of-the-art receiver while the required complexity can be drastically reduced.</description><subject>Approximation</subject><subject>belief propagation</subject><subject>Channel estimation</subject><subject>Channels</subject><subject>Complexity</subject><subject>Complexity theory</subject><subject>Detectors</subject><subject>Estimation</subject><subject>Filtration</subject><subject>Gaussian approximation</subject><subject>Guassian processes</subject><subject>Mathematical analysis</subject><subject>multi-user detection</subject><subject>Propagation</subject><subject>Receivers</subject><subject>Sparse code multiple access</subject><subject>Sparse matrices</subject><subject>State of the art</subject><subject>Uplink</subject><issn>1089-7798</issn><issn>1558-2558</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2018</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNo9kFtPAjEQhRujiYj-AX1p4vNir9A-wkaRBKIBiY9Nd3eqRdhd28XIv3e5xJeZSeacmZwPoVtKepQS_TBNX2azHiNU9ZgaCCHoGepQKVXC2nLezkTpZDDQ6hJdxbgihCgmaQcVY7uN0dsSD-s6VL9-YxtflcnIRijwCNYeHH4NVW0_Dgs8hxz8DwTsqoCX9dqXX3iRzoZ4sYsNbCJ-980nnmxqCA7yBqeLyfwaXTi7jnBz6l20fHp8S5-T6ct4kg6nSc60bJJCS2r7lEvHqXS5UxZcVlDRFyzXhWNyoHTOM6E1MJJxxwQtgEvJMyJoRhTvovvj3TbJ9xZiY1bVNpTtS8OoFES0p_YqdlTloYoxgDN1aGOHnaHE7GmaA02zp2lONFvT3dHkAeDfoISSXGn-B2QPcHw</recordid><startdate>20181201</startdate><enddate>20181201</enddate><creator>Lim, Seung-Chan</creator><creator>Park, Hyuncheol</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. 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Motivated by the conventional detection, called a Gaussian approximation-based belief propagation (GA-BP) with matched filtering, we propose an efficient receiver suitable for the uplink SCMA systems when exact channel state information is not available. By estimating matched filtered channels (rather than explicitly estimating actual channels), the proposed methods efficiently support the second-stage GA-BP detector with negligible increment of complexity. The simulation results show that the proposed receiver achieves the similar estimation and detection performance to the state-of-the-art receiver while the required complexity can be drastically reduced.</abstract><cop>New York</cop><pub>IEEE</pub><doi>10.1109/LCOMM.2018.2874441</doi><tpages>4</tpages><orcidid>https://orcid.org/0000-0002-7630-8533</orcidid></addata></record> |
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subjects | Approximation belief propagation Channel estimation Channels Complexity Complexity theory Detectors Estimation Filtration Gaussian approximation Guassian processes Mathematical analysis multi-user detection Propagation Receivers Sparse code multiple access Sparse matrices State of the art Uplink |
title | Gaussian Approximation-Based Belief Propagation Receiver for Uplink SCMA Systems With Imperfect CSIR |
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