A fast convergence LLL algorithm with fixed-complexity for SIC-based MIMO detection

Hyukyeon Lee; Hyunsub Kim; Minjoon Kim; Jaeseok Kim

doi:10.1109/ICOIN.2016.7427154

A fast convergence LLL algorithm with fixed-complexity for SIC-based MIMO detection

Hyukyeon Lee, Hyunsub Kim, Minjoon Kim, Jaeseok Kim

Department of Electrical and Electronic Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

1 Citation (Scopus)

Abstract

In this paper, we propose a fixed-complexity variant of LLL (Lenstra-Lenstra-Lovasz) algorithm. LLL algorithm is widely used in MIMO signal processing to obtain full diversity gain with low complexity increase. However, because of its non-deterministic nature with varying complexity and high worst-case costs, the real implementation of original LLL algorithm is difficult. Although some fixed-complexity variants of LLL algorithm has been proposed, but still their complexity in large MIMO system is high. The proposed algorithm uses column selection method based on threshold which leads to the fast convergence in fewer iterations. Simulation result shows that the proposed algorithm converges faster than other fixed-complexity variants of LLL algorithms while it saves about 30% complexity in 8 × 8 MIMO system compared to existing fixed-complexity LLL (fc-LLL) algorithm.

Original language	English
Title of host publication	30th International Conference on Information Networking, ICOIN 2016
Publisher	IEEE Computer Society
Pages	439-441
Number of pages	3
ISBN (Electronic)	9781509017249
DOIs	https://doi.org/10.1109/ICOIN.2016.7427154
Publication status	Published - 2016 Mar 7
Event	30th International Conference on Information Networking, ICOIN 2016 - Kota Kinabalu, Malaysia Duration: 2016 Jan 13 → 2016 Jan 15

Publication series

Name	International Conference on Information Networking
Volume	2016-March
ISSN (Print)	1976-7684

Other

Other	30th International Conference on Information Networking, ICOIN 2016
Country/Territory	Malaysia
City	Kota Kinabalu
Period	16/1/13 → 16/1/15

Bibliographical note

Funding Information:
This work was supported by the National Research Foundation of Korea(NRF) grant funded by the Korea government( MSIP) (No. NRF-2015R1A2A2A01004883)

Publisher Copyright:
© 2016 IEEE.

All Science Journal Classification (ASJC) codes

Computer Networks and Communications
Information Systems

Access to Document

10.1109/ICOIN.2016.7427154

Cite this

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title = "A fast convergence LLL algorithm with fixed-complexity for SIC-based MIMO detection",

abstract = "In this paper, we propose a fixed-complexity variant of LLL (Lenstra-Lenstra-Lovasz) algorithm. LLL algorithm is widely used in MIMO signal processing to obtain full diversity gain with low complexity increase. However, because of its non-deterministic nature with varying complexity and high worst-case costs, the real implementation of original LLL algorithm is difficult. Although some fixed-complexity variants of LLL algorithm has been proposed, but still their complexity in large MIMO system is high. The proposed algorithm uses column selection method based on threshold which leads to the fast convergence in fewer iterations. Simulation result shows that the proposed algorithm converges faster than other fixed-complexity variants of LLL algorithms while it saves about 30% complexity in 8 × 8 MIMO system compared to existing fixed-complexity LLL (fc-LLL) algorithm.",

author = "Hyukyeon Lee and Hyunsub Kim and Minjoon Kim and Jaeseok Kim",

note = "Funding Information: This work was supported by the National Research Foundation of Korea(NRF) grant funded by the Korea government( MSIP) (No. NRF-2015R1A2A2A01004883) Publisher Copyright: {\textcopyright} 2016 IEEE.; 30th International Conference on Information Networking, ICOIN 2016 ; Conference date: 13-01-2016 Through 15-01-2016",

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doi = "10.1109/ICOIN.2016.7427154",

language = "English",

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publisher = "IEEE Computer Society",

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Lee, H, Kim, H, Kim, M & Kim, J 2016, A fast convergence LLL algorithm with fixed-complexity for SIC-based MIMO detection. in 30th International Conference on Information Networking, ICOIN 2016., 7427154, International Conference on Information Networking, vol. 2016-March, IEEE Computer Society, pp. 439-441, 30th International Conference on Information Networking, ICOIN 2016, Kota Kinabalu, Malaysia, 16/1/13. https://doi.org/10.1109/ICOIN.2016.7427154

A fast convergence LLL algorithm with fixed-complexity for SIC-based MIMO detection. / Lee, Hyukyeon; Kim, Hyunsub; Kim, Minjoon et al.

30th International Conference on Information Networking, ICOIN 2016. IEEE Computer Society, 2016. p. 439-441 7427154 (International Conference on Information Networking; Vol. 2016-March).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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N1 - Funding Information: This work was supported by the National Research Foundation of Korea(NRF) grant funded by the Korea government( MSIP) (No. NRF-2015R1A2A2A01004883) Publisher Copyright: © 2016 IEEE.

PY - 2016/3/7

Y1 - 2016/3/7

N2 - In this paper, we propose a fixed-complexity variant of LLL (Lenstra-Lenstra-Lovasz) algorithm. LLL algorithm is widely used in MIMO signal processing to obtain full diversity gain with low complexity increase. However, because of its non-deterministic nature with varying complexity and high worst-case costs, the real implementation of original LLL algorithm is difficult. Although some fixed-complexity variants of LLL algorithm has been proposed, but still their complexity in large MIMO system is high. The proposed algorithm uses column selection method based on threshold which leads to the fast convergence in fewer iterations. Simulation result shows that the proposed algorithm converges faster than other fixed-complexity variants of LLL algorithms while it saves about 30% complexity in 8 × 8 MIMO system compared to existing fixed-complexity LLL (fc-LLL) algorithm.

AB - In this paper, we propose a fixed-complexity variant of LLL (Lenstra-Lenstra-Lovasz) algorithm. LLL algorithm is widely used in MIMO signal processing to obtain full diversity gain with low complexity increase. However, because of its non-deterministic nature with varying complexity and high worst-case costs, the real implementation of original LLL algorithm is difficult. Although some fixed-complexity variants of LLL algorithm has been proposed, but still their complexity in large MIMO system is high. The proposed algorithm uses column selection method based on threshold which leads to the fast convergence in fewer iterations. Simulation result shows that the proposed algorithm converges faster than other fixed-complexity variants of LLL algorithms while it saves about 30% complexity in 8 × 8 MIMO system compared to existing fixed-complexity LLL (fc-LLL) algorithm.

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A fast convergence LLL algorithm with fixed-complexity for SIC-based MIMO detection

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