Joint Channel and Data Estimation via Parametric Bilinear Inference for OTFS Demodulation

Ito, Kenta; Takahashi, Takumi; Furuta, Kengo et al.

IEEE Open Journal of the Communications Society, 2024, 5, 6090-6105

Number of Access:361（2025-08-14 18:27 Counts）

Identifier to cite or link to this item: https://hdl.handle.net/11094/98350

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Title
Joint Channel and Data Estimation via Parametric Bilinear Inference for OTFS Demodulation
Creator
CreatorName
Ito, Kenta
NRID
1000040844204 1000040844204
researchmap permalink
takumi_takahashi takumi_takahashi
Scopus Author ID
57193615052 57193615052
CreatorName
Takahashi, Takumi
CreatorName
Furuta, Kengo
NRID
1000010448087 1000010448087
CreatorName
Ibi, Shinsuke
CreatorName
Thadeu Freitas De Abreu, Giuseppe
Subject
Gaussian belief propagation
high-mobility communications
joint channel and data estimation
OTFS demodulation
parametric bilinear inference
Description
Ito K., Takahashi T., Furuta K., et al. Joint Channel and Data Estimation via Parametric Bilinear Inference for OTFS Demodulation. IEEE Open Journal of the Communications Society 5, 6090 (2024); https://doi.org/10.1109/OJCOMS.2024.3463202.
Abstract
This paper proposes a novel joint channel and data estimation (JCDE) algorithm via parametric bilinear Gaussian belief propagation (PBiGaBP) for orthogonal time frequency space (OTFS) demodulation. In doubly-selective fading channels, since the Doppler shift breaks the orthogonality between subcarriers, the signal demodulation process requires estimating the path gains and data symbols from the high-dimensional signals that are multiplexed in the frequency-time (FT) domain. To obtain highly accurate channel state information (CSI) using a typical channel estimation scheme based only on reference signals, an increase in pilot overhead to suppress inter-symbol interference (ISI) is unavoidable. In addition, large-scale matrix operations based on the size of OTFS-equivalent channels also pose problems in terms of computational cost. To address these issues, we focus on the fact that OTFS demodulation can be formulated as a large-scale parametric bilinear inference (PBI) problem, and solve it using the Gaussian belief propagation (GaBP) approach, which enables an approximate implementation of the sum-product algorithm (SPA), based on the central limit theorem (CLT), to design a low-complexity and high-accuracy JCDE algorithm using short pilots. Simulation results show that the proposed PBiGaBP-based JCDE algorithm outperforms the state-of-the-art (SotA) schemes and approaches the performance of idealized (genie-aided) scheme in terms of mean square error (MSE) and bit error rate (BER) performances.
Publisher
Institute of Electrical and Electronics Engineers Inc.
Source Title
IEEE Open Journal of the Communications Society
Volume (Issue)
5
Page
6090-6105
Date of Issued
2024-09-01
Language
English
Handle URL
https://hdl.handle.net/11094/98350
eISSN
2644125X
Relation.isIdenticalTo
DOI (Publisher Version)
https://doi.org/10.1109/OJCOMS.2024.3463202
Access Rights
open access
CopyRight
This article is licensed under a Creative Commons Attribution 4.0 International License.
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Category
学術雑誌論文 Journal Article