增强自适应二阶网格细化OTFS系统信道估计

IF 4.4 3区计算机科学 Q2 TELECOMMUNICATIONS

IEEE Communications Letters Pub Date : 2025-07-07 DOI:10.1109/LCOMM.2025.3586688

Peng Liu;Meng Tang;Hao Wang

{"title":"增强自适应二阶网格细化OTFS系统信道估计","authors":"Peng Liu;Meng Tang;Hao Wang","doi":"10.1109/LCOMM.2025.3586688","DOIUrl":null,"url":null,"abstract":"In orthogonal time frequency space (OTFS) modulation, the virtual grid in the delay-Doppler (DD) domain is critical for estimating fractional channel. However, the resolution of the DD grid influences both algorithmic complexity and channel estimation (CE) performance. This letter proposes an adaptive second-order grid refinement (ASGR) scheme, which effectively balances computational efficiency and CE precision. To accurately estimate the doubly fractional channel in the OTFS system, a second-order Taylor expansion is used to approximate the measurement matrix. A fast Bayesian compressive sensing (FBCS) is then employed for preliminary hyperparameter estimation to reduce computational load. Subsequently, the pivotal parameters on the grid are adaptively adjusted, and the evolved points are inserted into the original grid to achieve local refinement. Simulation results show that the proposed ASGR achieves a performance gain of 4-6 dB over the off-grid FBCS.","PeriodicalId":13197,"journal":{"name":"IEEE Communications Letters","volume":"29 9","pages":"2093-2097"},"PeriodicalIF":4.4000,"publicationDate":"2025-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Enhanced Adaptive Second-Order Grid Refinement Channel Estimation for OTFS Systems\",\"authors\":\"Peng Liu;Meng Tang;Hao Wang\",\"doi\":\"10.1109/LCOMM.2025.3586688\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In orthogonal time frequency space (OTFS) modulation, the virtual grid in the delay-Doppler (DD) domain is critical for estimating fractional channel. However, the resolution of the DD grid influences both algorithmic complexity and channel estimation (CE) performance. This letter proposes an adaptive second-order grid refinement (ASGR) scheme, which effectively balances computational efficiency and CE precision. To accurately estimate the doubly fractional channel in the OTFS system, a second-order Taylor expansion is used to approximate the measurement matrix. A fast Bayesian compressive sensing (FBCS) is then employed for preliminary hyperparameter estimation to reduce computational load. Subsequently, the pivotal parameters on the grid are adaptively adjusted, and the evolved points are inserted into the original grid to achieve local refinement. Simulation results show that the proposed ASGR achieves a performance gain of 4-6 dB over the off-grid FBCS.\",\"PeriodicalId\":13197,\"journal\":{\"name\":\"IEEE Communications Letters\",\"volume\":\"29 9\",\"pages\":\"2093-2097\"},\"PeriodicalIF\":4.4000,\"publicationDate\":\"2025-07-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Communications Letters\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/11072479/\",\"RegionNum\":3,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"TELECOMMUNICATIONS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Communications Letters","FirstCategoryId":"94","ListUrlMain":"https://ieeexplore.ieee.org/document/11072479/","RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"TELECOMMUNICATIONS","Score":null,"Total":0}

引用次数: 0

摘要

在正交时频空间（OTFS）调制中，延迟多普勒（DD）域的虚拟网格是估计分数信道的关键。然而，DD网格的分辨率会影响算法复杂度和信道估计性能。本文提出了一种自适应二阶网格细化（ASGR）方案，该方案有效地平衡了计算效率和CE精度。为了准确估计OTFS系统中的双分数阶信道，采用二阶泰勒展开式近似测量矩阵。然后采用快速贝叶斯压缩感知（FBCS）进行初步超参数估计，以减少计算量。随后，自适应调整网格上的关键参数，并将进化点插入原始网格中，实现局部细化。仿真结果表明，与离网FBCS相比，该方法的性能提高了4 ~ 6db。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

Enhanced Adaptive Second-Order Grid Refinement Channel Estimation for OTFS Systems

In orthogonal time frequency space (OTFS) modulation, the virtual grid in the delay-Doppler (DD) domain is critical for estimating fractional channel. However, the resolution of the DD grid influences both algorithmic complexity and channel estimation (CE) performance. This letter proposes an adaptive second-order grid refinement (ASGR) scheme, which effectively balances computational efficiency and CE precision. To accurately estimate the doubly fractional channel in the OTFS system, a second-order Taylor expansion is used to approximate the measurement matrix. A fast Bayesian compressive sensing (FBCS) is then employed for preliminary hyperparameter estimation to reduce computational load. Subsequently, the pivotal parameters on the grid are adaptively adjusted, and the evolved points are inserted into the original grid to achieve local refinement. Simulation results show that the proposed ASGR achieves a performance gain of 4-6 dB over the off-grid FBCS.

求助全文

通过发布文献求助，成功后即可免费获取论文全文。去求助

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.