Adaptive MMSE-SVD to Improve the Tracking Ability Against Fast Fading

Yuta Seki, Amnart Boonkajay, Fumiyuki Adachi

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

    1 Citation (Scopus)


    Multi-User Multiple Input Multiple Output (MU-MIMO) can significantly increase the link capacity without bandwidth expansion. One promising technique is MMSE-SVD, which is a combination of minimum mean square error (MMSE) filter at the base station (BS) side and eigenmode filter generated by singular value decomposition (SVD) at user equipment (UE) side. MMSE-SVD requires BS and UEs to share the MIMO channel state information (CSI) prior to data transmission. This may cause a serious problem in a high mobility environment; the shared MIMO CSI becomes outdated and consequently, the bit-error rate (BER) performance degrades. In this paper, we propose an adaptive MMSE-SVD, which updates the transmit filter using channel prediction and the receive filter using decision-feedback channel estimation. The uncoded BER performance of adaptive MMSE-SVD for orthogonal frequency division multiplexing (OFDM) downlink and single-carrier (SC) uplink is evaluated by computer simulation. Simulation results confirmed that adaptive MMSE-SVD increases the allowable maximum Doppler frequency (boldsymbol{f}-{mathbf{D}}boldsymbol{T}) for keeping mathbf{BER} < 10-{-2} by about 4 times for OFDM downlink while by about 1.6 times for SC uplink.

    Original languageEnglish
    Title of host publication2018 IEEE 88th Vehicular Technology Conference, VTC-Fall 2018 - Proceedings
    PublisherInstitute of Electrical and Electronics Engineers Inc.
    ISBN (Electronic)9781538663585
    Publication statusPublished - 2018 Jul 2
    Event88th IEEE Vehicular Technology Conference, VTC-Fall 2018 - Chicago, United States
    Duration: 2018 Aug 272018 Aug 30

    Publication series

    NameIEEE Vehicular Technology Conference
    ISSN (Print)1550-2252


    Conference88th IEEE Vehicular Technology Conference, VTC-Fall 2018
    Country/TerritoryUnited States


    • MU-MIMO
    • OFDM downlink
    • SC uplink
    • decision-feedback channel estimation
    • linear prediction

    ASJC Scopus subject areas

    • Computer Science Applications
    • Electrical and Electronic Engineering
    • Applied Mathematics


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