A Sparsity-Agnostic SL0 Channel Estimation Approach for OTFS Systems

IF 3.7 3区计算机科学 Q2 TELECOMMUNICATIONS

IEEE Communications Letters Pub Date : 2025-03-26 DOI:10.1109/LCOMM.2025.3554379

Xin Wang;Can Zheng;Pengjiang Hu;Junan Yang;Chung G. Kang

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引用次数: 0

Abstract

Orthogonal time frequency space (OTFS) modulation has been shown to support reliable communication in high mobility scenarios. Due to the sparsity of the delay-Doppler (DD) domain, most existing algorithms utilize compressed sensing (CS) for OTFS channel estimation, while requiring a known channel sparsity. However, in cases that the sparsity is not readily accessible, the estimation accuracy of these CS algorithms decreases dramatically. In this letter, we propose a Smoothed

$\ell _{0}$

(SL0) algorithm free of prior knowledge about channel sparsity for OTFS channel estimation. We obtain a novel vector expression of the input-output relationship in the DD domain and formulate it as a sparse signal recovery problem. In the case of unknown sparsity, a low-complexity SL0 algorithm is introduced to solve the problem with a faster reconstruction speed. Simulation results show that the proposed algorithm has significant advantages in estimation accuracy and complexity compared to algorithms that also do not require channel sparsity.

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一种OTFS系统稀疏不可知的SL0信道估计方法

正交时频空间（OTFS）调制已被证明支持高移动场景下的可靠通信。由于延迟多普勒（DD）域的稀疏性，大多数现有算法利用压缩感知（CS）进行OTFS信道估计，同时需要已知的信道稀疏性。然而，在稀疏度不容易获得的情况下，这些CS算法的估计精度会急剧下降。在这封信中，我们提出了一种平滑的$\ well _{0}$ （SL0）算法，该算法不需要关于OTFS信道稀疏性的先验知识。我们在DD域中得到了一种新的输入输出关系向量表达式，并将其表述为一个稀疏信号恢复问题。在稀疏度未知的情况下，引入低复杂度的SL0算法，以更快的重建速度解决问题。仿真结果表明，与不需要信道稀疏性的算法相比，该算法在估计精度和复杂度方面具有显著的优势。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

IEEE Communications Letters 工程技术-电信学

CiteScore

8.10

自引率

7.30%

发文量

590

审稿时长

2.8 months

期刊介绍： The IEEE Communications Letters publishes short papers in a rapid publication cycle on advances in the state-of-the-art of communication over different media and channels including wire, underground, waveguide, optical fiber, and storage channels. Both theoretical contributions (including new techniques, concepts, and analyses) and practical contributions (including system experiments and prototypes, and new applications) are encouraged. This journal focuses on the physical layer and the link layer of communication systems.