Low complexity metric for joint MLD in overloaded MIMO system

Takayoshi Aoki, Yukitoshi Sanada

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

    1 Citation (Scopus)


    This paper presents a low complexity metric for joint maximum-likelihood detection (MLD) in overloaded multiple-input multiple-output (MIMO)-orthogonal frequency division multiplexing (OFDM) systems. In overloaded MIMO systems, a nonlinear detection scheme such as MLD combined with error correction coding achieves superior performance than that of a single signal stream with higher order modulation. However, MLD demands large computational complexity because of multiplications in the selection of candidate signal points. Thus, a Manhattan metric has been used to reduce the complexity. Nevertheless, it is not accurate and causes performance degradation in overloaded MIMO systems. Thus, this paper proposes a new metric that is calculated with summations and bit shifts. New numerical results obtained through computer simulation show that the proposed metric improves bit error rate (BER) performance more than 0.2dB at the BER of 10-4 in comparison with a Manhattan metric.

    Original languageEnglish
    Title of host publication2015 IEEE 82nd Vehicular Technology Conference, VTC Fall 2015 - Proceedings
    PublisherInstitute of Electrical and Electronics Engineers Inc.
    ISBN (Print)9781479980918
    Publication statusPublished - 2016 Jan 25
    Event82nd IEEE Vehicular Technology Conference, VTC Fall 2015 - Boston, United States
    Duration: 2015 Sep 62015 Sep 9


    Other82nd IEEE Vehicular Technology Conference, VTC Fall 2015
    Country/TerritoryUnited States

    ASJC Scopus subject areas

    • Computer Networks and Communications
    • Automotive Engineering
    • Hardware and Architecture


    Dive into the research topics of 'Low complexity metric for joint MLD in overloaded MIMO system'. Together they form a unique fingerprint.

    Cite this