A best-first tree-searching approach for ML decoding in MIMO system

Handle URI:
http://hdl.handle.net/10754/236095
Title:
A best-first tree-searching approach for ML decoding in MIMO system
Authors:
Shen, Chung-An; Eltawil, Ahmed M.; Mondal, Sudip; Salama, Khaled N. ( 0000-0001-7742-1282 )
Abstract:
In MIMO communication systems maximum-likelihood (ML) decoding can be formulated as a tree-searching problem. This paper presents a tree-searching approach that combines the features of classical depth-first and breadth-first approaches to achieve close to ML performance while minimizing the number of visited nodes. A detailed outline of the algorithm is given, including the required storage. The effects of storage size on BER performance and complexity in terms of search space are also studied. Our result demonstrates that with a proper choice of storage size the proposed method visits 40% fewer nodes than a sphere decoding algorithm at signal to noise ratio (SNR) = 20dB and by an order of magnitude at 0 dB SNR.
KAUST Department:
Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division; Sensors Lab
Citation:
Shen C-A, Eltawil AM, Mondal S, Salama KN (2010) A best-first tree-searching approach for ML decoding in MIMO system. Proceedings of 2010 IEEE International Symposium on Circuits and Systems. doi:10.1109/ISCAS.2010.5537825.
Conference/Event name:
2010 IEEE International Symposium on Circuits and Systems: Nano-Bio Circuit Fabrics and Systems, ISCAS 2010
Issue Date:
28-Jul-2012
DOI:
10.1109/ISCAS.2010.5537825
Type:
Conference Paper
Additional Links:
http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=5537825
Appears in Collections:
Conference Papers; Sensors Lab; Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division

Full metadata record

DC FieldValue Language
dc.contributor.authorShen, Chung-Anen
dc.contributor.authorEltawil, Ahmed M.en
dc.contributor.authorMondal, Sudipen
dc.contributor.authorSalama, Khaled N.en
dc.date.accessioned2012-07-28T10:26:10Z-
dc.date.available2012-07-28T10:26:10Z-
dc.date.issued2012-07-28en
dc.identifier.citationShen C-A, Eltawil AM, Mondal S, Salama KN (2010) A best-first tree-searching approach for ML decoding in MIMO system. Proceedings of 2010 IEEE International Symposium on Circuits and Systems. doi:10.1109/ISCAS.2010.5537825.en
dc.identifier.doi10.1109/ISCAS.2010.5537825en
dc.identifier.urihttp://hdl.handle.net/10754/236095en
dc.description.abstractIn MIMO communication systems maximum-likelihood (ML) decoding can be formulated as a tree-searching problem. This paper presents a tree-searching approach that combines the features of classical depth-first and breadth-first approaches to achieve close to ML performance while minimizing the number of visited nodes. A detailed outline of the algorithm is given, including the required storage. The effects of storage size on BER performance and complexity in terms of search space are also studied. Our result demonstrates that with a proper choice of storage size the proposed method visits 40% fewer nodes than a sphere decoding algorithm at signal to noise ratio (SNR) = 20dB and by an order of magnitude at 0 dB SNR.en
dc.language.isoenen
dc.relation.urlhttp://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=5537825en
dc.titleA best-first tree-searching approach for ML decoding in MIMO systemen
dc.typeConference Paperen
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Divisionen
dc.contributor.departmentSensors Laben
dc.conference.date30 May 2010 through 2 June 2010en
dc.conference.name2010 IEEE International Symposium on Circuits and Systems: Nano-Bio Circuit Fabrics and Systems, ISCAS 2010en
dc.conference.locationParisen
kaust.authorSalama, Khaled N.en
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