Symbol Detection for Coarsely Quantized OTFS

Fuente: arXiv
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Main Authors: He, Junwei, Zhang, Haochuan, Dong, Chao, Zhu, Huimin
Format: Preprint
Published: 2023
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author He, Junwei
Zhang, Haochuan
Dong, Chao
Zhu, Huimin
author_facet He, Junwei
Zhang, Haochuan
Dong, Chao
Zhu, Huimin
contents This paper explicitly models a coarse and noisy quantization in a communication system empowered by orthogonal time frequency space (OTFS) for cost and power efficiency. We first point out, with coarse quantization, the effective channel is imbalanced and thus no longer able to circularly shift the transmitted symbols along the delay-Doppler domain. Meanwhile, the effective channel is non-isotropic, which imposes a significant loss to symbol detection algorithms like the original approximate message passing (AMP). Although the algorithm of generalized expectation consistent for signal recovery (GEC-SR) can mitigate this loss, the complexity in computation is prohibitively high, mainly due to an dramatic increase in the matrix size of OTFS. In this context, we propose a low-complexity algorithm that incorporates into the GEC-SR a quick inversion of quasi-banded matrices, reducing the complexity from a cubic order to a linear order while keeping the performance at the same level.
format Preprint
id arxiv_https___arxiv_org_abs_2309_11759
institution arXiv
publishDate 2023
record_format arxiv
spellingShingle Symbol Detection for Coarsely Quantized OTFS
He, Junwei
Zhang, Haochuan
Dong, Chao
Zhu, Huimin
Information Theory
Signal Processing
This paper explicitly models a coarse and noisy quantization in a communication system empowered by orthogonal time frequency space (OTFS) for cost and power efficiency. We first point out, with coarse quantization, the effective channel is imbalanced and thus no longer able to circularly shift the transmitted symbols along the delay-Doppler domain. Meanwhile, the effective channel is non-isotropic, which imposes a significant loss to symbol detection algorithms like the original approximate message passing (AMP). Although the algorithm of generalized expectation consistent for signal recovery (GEC-SR) can mitigate this loss, the complexity in computation is prohibitively high, mainly due to an dramatic increase in the matrix size of OTFS. In this context, we propose a low-complexity algorithm that incorporates into the GEC-SR a quick inversion of quasi-banded matrices, reducing the complexity from a cubic order to a linear order while keeping the performance at the same level.
title Symbol Detection for Coarsely Quantized OTFS
topic Information Theory
Signal Processing
url https://arxiv.org/abs/2309.11759