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Channel estimation algorithm for IRS-OTFS systems via sparse signal recovery
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Jianping ZHOU1, 2, Jiahui DUAN2, Zufan ZHANG2
Journal of Chongqing University of Posts and Telecommunications(Natural Science Edition) | 2025, 37(5) : 658 - 667
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Journal of Chongqing University of Posts and Telecommunications(Natural Science Edition) | 2025, 37(5): 658-667
• New-Generation Mobile Communication •
Channel estimation algorithm for IRS-OTFS systems via sparse signal recovery
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Jianping ZHOU1, 2, Jiahui DUAN2, Zufan ZHANG2
Affiliations
  • 1School of Information Engineering, Sanming University, Fujian 365004, P. R. China
  • 2School of Communications and Information Engineering, Chongqing University of Posts and Telecommunications, Chongqing 400065, P. R. China
doi: 10.3979/j.issn.1673-825X.202412140311
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This study focuses on the problem of fractional channel parameters affecting channel estimation performance in intelligent reflecting surface-orthogonal time frequency space（IRS-OTFS）communication systems. A channel estimation method for IRS-OTFS systems is proposed by leveraging the sparsity of OTFS channels in the delay-Doppler（DD）domain. First, the joint sparsity channel estimation problem among channel parameters is transformed into a sparse signal recovery problem. Next, the fast iterative shrinkage/thresholding algorithm（FISTA）is introduced to solve this problem. The inputoutput relationship of the IRS-OTFS communication system is then derived. To address the issue of manual parameter tuning in traditional FISTA, a network architecture based on the FISTA algorithm is proposed. This architecture unfolds the iterative process of the sparse signal recovery algorithm into a neural network. The network is designed to automatically learn the optimal hyperparameters and nonlinear functions within the algorithm. Theoretical analysis and simulation results demonstrate that, under the same channel transmission conditions, the proposed algorithm achieves lower estimation error com pared to the benchmark algorithm.

intelligent reflecting surface (IRS)  /  orthogonal time frequency space (OTFS)  /  channel estimation  /  sparse signal recovery
Jianping ZHOU, Jiahui DUAN, Zufan ZHANG. Channel estimation algorithm for IRS-OTFS systems via sparse signal recovery[J]. Journal of Chongqing University of Posts and Telecommunications(Natural Science Edition), 2025 , 37 (5) : 658 -667 . DOI: 10.3979/j.issn.1673-825X.202412140311
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Year 2025 volume 37 Issue 5
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Article Info
doi: 10.3979/j.issn.1673-825X.202412140311
  • Receive Date：2024-12-14
  • Online Date：2026-04-16
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  • Received：2024-12-14
  • Revised：2025-09-18
Affiliations
    1School of Information Engineering, Sanming University, Fujian 365004, P. R. China
    2School of Communications and Information Engineering, Chongqing University of Posts and Telecommunications, Chongqing 400065, P. R. China
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