A Sliding-Window LMMSE Turbo Equalization Scheme for OTFS

Franz Lampel; Alex Alvarado; Frans M.J. Willems

doi:10.1109/LCOMM.2023.3326168

A Sliding-Window LMMSE Turbo Equalization Scheme for OTFS

Franz Lampel (Corresponding author)
, Alex Alvarado
, Frans M.J. Willems

Research output: Contribution to journal › Article › Academic › peer-review

4 Citations (Scopus)

258 Downloads (Pure)

Abstract

This letter discusses a recently proposed linear minimum mean square error (LMMSE) turbo equalization scheme for OTFS. The complexity of the LMMSE-based equalizer, measured by the number of complex multiply-and-addition operations, scales with the cube of the number of transmitted symbols in an OTFS frame. To lower the complexity, we propose to limit the number of symbols in the equalization process by introducing a sliding window and exploiting the periodicity properties of the delay-Doppler domain. We demonstrate that for a practical channel model, which introduces fractional delay and Doppler shifts, even a narrow sliding window provides a bit error rate (BER) performance within 0.17 dB compared to the unconstrained LMMSE-based turbo equalizer. At the same time, the complexity of the sliding window LMMSE turbo equalizer is reduced by a factor of 10. The BER gap becomes even smaller with increasing window size, allowing for a complexity/performance trade-off.

Original language	English
Article number	3326168
Pages (from-to)	3320-3324
Number of pages	5
Journal	IEEE Communications Letters
Volume	27
Issue number	12
DOIs	https://doi.org/10.1109/LCOMM.2023.3326168
Publication status	Published - Dec 2023

Funding

This research is supported by the Dutch Technology Foundation TTW, which is part of the Netherlands Organisation for Scientific Research (NWO) and is partly funded by the Ministry of Economic Affairs under the project Integrated Cooperative Automated Vehicles (i-CAVE).

Keywords

Covariance matrices
Delays
Doppler shift
Equalizers
LMMSE equalization
OTFS
Symbols
Time-domain analysis
Transforms
turbo equalization
oTFS

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10.1109/LCOMM.2023.3326168

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title = "A Sliding-Window LMMSE Turbo Equalization Scheme for OTFS",

abstract = "This letter discusses a recently proposed linear minimum mean square error (LMMSE) turbo equalization scheme for OTFS. The complexity of the LMMSE-based equalizer, measured by the number of complex multiply-and-addition operations, scales with the cube of the number of transmitted symbols in an OTFS frame. To lower the complexity, we propose to limit the number of symbols in the equalization process by introducing a sliding window and exploiting the periodicity properties of the delay-Doppler domain. We demonstrate that for a practical channel model, which introduces fractional delay and Doppler shifts, even a narrow sliding window provides a bit error rate (BER) performance within 0.17 dB compared to the unconstrained LMMSE-based turbo equalizer. At the same time, the complexity of the sliding window LMMSE turbo equalizer is reduced by a factor of 10. The BER gap becomes even smaller with increasing window size, allowing for a complexity/performance trade-off.",

keywords = "Covariance matrices, Delays, Doppler shift, Equalizers, LMMSE equalization, OTFS, Symbols, Time-domain analysis, Transforms, turbo equalization, oTFS",

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AB - This letter discusses a recently proposed linear minimum mean square error (LMMSE) turbo equalization scheme for OTFS. The complexity of the LMMSE-based equalizer, measured by the number of complex multiply-and-addition operations, scales with the cube of the number of transmitted symbols in an OTFS frame. To lower the complexity, we propose to limit the number of symbols in the equalization process by introducing a sliding window and exploiting the periodicity properties of the delay-Doppler domain. We demonstrate that for a practical channel model, which introduces fractional delay and Doppler shifts, even a narrow sliding window provides a bit error rate (BER) performance within 0.17 dB compared to the unconstrained LMMSE-based turbo equalizer. At the same time, the complexity of the sliding window LMMSE turbo equalizer is reduced by a factor of 10. The BER gap becomes even smaller with increasing window size, allowing for a complexity/performance trade-off.

KW - Covariance matrices

KW - Delays

KW - Doppler shift

KW - Equalizers

KW - LMMSE equalization

KW - OTFS

KW - Symbols

KW - Time-domain analysis

KW - Transforms

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KW - oTFS

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A Sliding-Window LMMSE Turbo Equalization Scheme for OTFS

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