Applications of SDR exact-ML criterion to tree-searching detection for MIMO systems

Minjoon Kim, Jaeseok Kim

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

In previous work, we proposed the positive diagonal values (PDV) criterion, which is an exact-ML criterion of semidefinite relaxation (SDR) optimality condition. In this paper, we apply the PDV criterion to the tree-searching based MIMO detection by two ways. The first application is node-pruning algorithm for depth first search such as sphere decoding (SD). The proposed node-pruning algorithm using PDV criterion is not based on the Euclidean distance mostly used for node-pruning algorithm, instead, it uses an absolute test in each node so that it can be worked independently with many existing node-pruning algorithms. Furthermore, the proposed node-pruning algorithm can guarantee the exact-ML performance and reduce the number of nodes visited significantly. The second application is K-best algorithm of breadth first search. The proposed K-best algorithm takes K candidates at each stage based on PDV criterion. As a result, the proposed K-best algorithm can achieve near-ML performance.

Original languageEnglish
Title of host publication2014, 8th International Conference on Signal Processing and Communication Systems, ICSPCS 2014 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781479952557
DOIs
Publication statusPublished - 2014 Jan 23
Event8th International Conference on Signal Processing and Communication Systems, ICSPCS 2014 - Gold Coast, Australia
Duration: 2014 Dec 152014 Dec 17

Other

Other8th International Conference on Signal Processing and Communication Systems, ICSPCS 2014
CountryAustralia
CityGold Coast
Period14/12/1514/12/17

Fingerprint

MIMO systems
Decoding

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Signal Processing
  • Electrical and Electronic Engineering

Cite this

Kim, M., & Kim, J. (2014). Applications of SDR exact-ML criterion to tree-searching detection for MIMO systems. In 2014, 8th International Conference on Signal Processing and Communication Systems, ICSPCS 2014 - Proceedings [7021135] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICSPCS.2014.7021135
Kim, Minjoon ; Kim, Jaeseok. / Applications of SDR exact-ML criterion to tree-searching detection for MIMO systems. 2014, 8th International Conference on Signal Processing and Communication Systems, ICSPCS 2014 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2014.
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Kim, M & Kim, J 2014, Applications of SDR exact-ML criterion to tree-searching detection for MIMO systems. in 2014, 8th International Conference on Signal Processing and Communication Systems, ICSPCS 2014 - Proceedings., 7021135, Institute of Electrical and Electronics Engineers Inc., 8th International Conference on Signal Processing and Communication Systems, ICSPCS 2014, Gold Coast, Australia, 14/12/15. https://doi.org/10.1109/ICSPCS.2014.7021135

Applications of SDR exact-ML criterion to tree-searching detection for MIMO systems. / Kim, Minjoon; Kim, Jaeseok.

2014, 8th International Conference on Signal Processing and Communication Systems, ICSPCS 2014 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2014. 7021135.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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AB - In previous work, we proposed the positive diagonal values (PDV) criterion, which is an exact-ML criterion of semidefinite relaxation (SDR) optimality condition. In this paper, we apply the PDV criterion to the tree-searching based MIMO detection by two ways. The first application is node-pruning algorithm for depth first search such as sphere decoding (SD). The proposed node-pruning algorithm using PDV criterion is not based on the Euclidean distance mostly used for node-pruning algorithm, instead, it uses an absolute test in each node so that it can be worked independently with many existing node-pruning algorithms. Furthermore, the proposed node-pruning algorithm can guarantee the exact-ML performance and reduce the number of nodes visited significantly. The second application is K-best algorithm of breadth first search. The proposed K-best algorithm takes K candidates at each stage based on PDV criterion. As a result, the proposed K-best algorithm can achieve near-ML performance.

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Kim M, Kim J. Applications of SDR exact-ML criterion to tree-searching detection for MIMO systems. In 2014, 8th International Conference on Signal Processing and Communication Systems, ICSPCS 2014 - Proceedings. Institute of Electrical and Electronics Engineers Inc. 2014. 7021135 https://doi.org/10.1109/ICSPCS.2014.7021135