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

Hyukyeon Lee, Hyunsub Kim, Minjoon Kim, Jaeseok Kim

Research output: Chapter in Book/Report/Conference proceedingConference 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 languageEnglish
Title of host publication30th International Conference on Information Networking, ICOIN 2016
PublisherIEEE Computer Society
Pages439-441
Number of pages3
ISBN (Electronic)9781509017249
DOIs
Publication statusPublished - 2016 Mar 7
Event30th International Conference on Information Networking, ICOIN 2016 - Kota Kinabalu, Malaysia
Duration: 2016 Jan 132016 Jan 15

Publication series

NameInternational Conference on Information Networking
Volume2016-March
ISSN (Print)1976-7684

Other

Other30th International Conference on Information Networking, ICOIN 2016
CountryMalaysia
CityKota Kinabalu
Period16/1/1316/1/15

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Information Systems

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  • Cite this

    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 (pp. 439-441). [7427154] (International Conference on Information Networking; Vol. 2016-March). IEEE Computer Society. https://doi.org/10.1109/ICOIN.2016.7427154