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

Abstract

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 This may cause a serious problem in a high mobility environment; the shared MIMO CSI becomes outdated and consequently, the bit-error rate (BER) performance degrades.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
DOIs
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
Volume2018-August
ISSN (Print)1550-2252

Conference

Conference88th IEEE Vehicular Technology Conference, VTC-Fall 2018
CountryUnited States
CityChicago
Period18/8/2718/8/30

Keywords

  • 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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