Low Overhead and Scalable Time-Frequency Pilots Design for MIMO OTFS Channel Estimation
arXiv:2511.08504v2 Announce Type: replace Abstract: Orthogonal Time Frequency Space (OTFS) modulation has recently garnered attention for its robustness in high-mobility wireless communication environments. In OTFS, the data symbols are mapped to the Doppler-Delay (DD) domain. In this paper, we address low-overhead, scalable pilot-aided estimation of channel state information (CSI) for MIMO OTFS systems. Existing channel estimation techniques either require non-overlapping DD domain pilots with guard regions across multiple antennas, thus sacrificing significant communication rate as the number of transmit antennas increases, or allow pilots to overlap between antennas and rely on high-complexity methods to mitigate pilot pollution. We propose a novel pilot placement approach that embeds p
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Abstract:Orthogonal Time Frequency Space (OTFS) modulation has recently garnered attention for its robustness in high-mobility wireless communication environments. In OTFS, the data symbols are mapped to the Doppler-Delay (DD) domain. In this paper, we address low-overhead, scalable pilot-aided estimation of channel state information (CSI) for MIMO OTFS systems. Existing channel estimation techniques either require non-overlapping DD domain pilots with guard regions across multiple antennas, thus sacrificing significant communication rate as the number of transmit antennas increases, or allow pilots to overlap between antennas and rely on high-complexity methods to mitigate pilot pollution. We propose a novel pilot placement approach that embeds pilots within the time-frequency (TF) frame of each OTFS burst, along with a new use of TF and DD guard bins to preserve waveform orthogonality on the TF pilot bins and data integrity in the DD domain, respectively. The proposed pilot placement enables low-complexity coarse estimation of the channel parameters. Moreover, the pilot orthogonality allows the construction of a virtual array (VA), enabling the formulation of a sparse signal recovery (SSR) problem in which the coarse estimates are used to build a low-dimensional dictionary matrix. The SSR solution then yields high-resolution estimates of the channel parameters. Simulation results show that the proposed approach achieves good performance with very low overhead and is robust to pilot pollution. Importantly, the required overhead is independent of the number of transmit antennas, ensuring scalability to large MIMO arrays. The proposed approach accounts for practical rectangular transmit pulse shaping and receiver matched filtering, as well as fractional Doppler effects.
Subjects:
Signal Processing (eess.SP)
Cite as: arXiv:2511.08504 [eess.SP]
(or arXiv:2511.08504v2 [eess.SP] for this version)
https://doi.org/10.48550/arXiv.2511.08504
arXiv-issued DOI via DataCite
Submission history
From: Kailong Wang [view email] [v1] Tue, 11 Nov 2025 17:39:22 UTC (478 KB) [v2] Sun, 29 Mar 2026 23:29:34 UTC (199 KB)
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