Search arXivSearch

arXiv · 2608.03293

Prior-Aided Iterative Channel Reconstruction with Optimized Frame Structure for DSE Mitigation in CP-OTFS-Based LEO Satellite Systems

Abstract

Orthogonal time frequency space (OTFS) modulation has emerged as a promising solution to mitigate the severe Doppler shift in low Earth orbit (LEO) satellite communications. However, the frequency-dependent Doppler shift induced by the high mobility of LEO satellites leads to the Doppler squint effect (DSE). This effect compromises the channel sparsity in the delay-Doppler (DD) domain, rendering existing channel estimation methods ineffective. To overcome this challenge, this paper proposes a DSE-resilient transmission scheme for cyclic prefix OTFS (CP-OTFS)-based LEO satellite systems. Specifically, we analyze the input-output relationship of the CPOTFS- based LEO satellite communication system and derive a DSE-aware representation of the satellite-terrestrial channel in the DD domain. To efficiently capture DSE-aware channel characteristics, we propose a novel OTFS frame structure that allows the energy distribution of the received signal to serve as prior information for channel estimation. Meanwhile, this frame structure strategically allocates pilot symbols to achieve uniform energy distribution and reduce the peak-to-average power ratio (PAPR), while imposing a time-domain waveform continuity constraint to suppress out-of-band emission (OOBE) caused by rectangular pulses. Based on the frame structure, we propose a prior-aided iterative channel reconstruction (PAICR) algorithm to mitigate the severe power leakage induced by DSE. The proposed algorithm iteratively extracts and removes dominant channel components using Doppler-domain received signal energy observations, with a convergence criterion ensuring reliable termination. Furthermore, a Cramer-Rao lower bound is derived to provide a theoretical benchmark for evaluating the algorithm's performance.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Yiyan Cheng, Tiejun Lv, Yashuai Cao, Xuehan Wang, Mugen Peng. 2026-08-04. Prior-Aided Iterative Channel Reconstruction with Optimized Frame Structure for DSE Mitigation in CP-OTFS-Based LEO Satellite Systems. https://arxiv.org/abs/2608.03293

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

Multi-Carrier Rydberg Atomic Quantum Receivers with Enhanced Bandwidth Feature for Communication and Sensing

Rydberg atomic quantum receivers (RAQRs) have attracted significant attention in recent years due to their ultra-high sensitivity. Although capable of precisely detecting the amplitude and phase of weak signals, conventional RAQRs face inherent limitations in accurately receiving wideband RF signals, due to the discrete nature of atomic energy levels and their intrinsic instantaneous bandwidth constraints. These limitations hinder their direct application to multi-carrier communication and sensing. To address this issue, this paper proposes a multi-carrier Rydberg atomic quantum receiver (MC-RAQR) structure with five energy levels. We derive the amplitude and phase of the MC-RAQR and extract the baseband electrical signal for signal processing. In terms of multi-carrier communication and sensing, we analyze the channel capacity and accuracy of angle of arrival (AoA) and distance parameters, respectively. Numerical results validate our proposed model, showing that the MC-RAQR can achieve up to a bandwidth of 11.7 MHz, which is 17-fold larger than the conventional RAQRs. As a result, the channel capacity and the resolution for multi-target sensing are improved significantly. Specifically, the channel capacity of MC-RAQR is 110-fold and 2.8-fold larger than the classical RF receivers and RAQRs, respectively. For sensing performance, the RMSE of AoA estimation for MC-RAQR exhibits 7.6-fold reduction, compared with the conventional RAQRs. Furthermore, the RMSE of distance estimation is $634$-fold smaller than that of the root-CRB of classical RF receivers, showing the superior performance of the MC-RAQR. This demonstrates its compatibility with waveforms such as orthogonal frequency-division multiplexing (OFDM) and its significant advantages for multi-carrier signal reception.

eess.SP

Channel Estimation in MIMO Systems Aided by Microwave Linear Analog Computers (MiLACs)

Microwave linear analog computers (MiLACs) have recently emerged as a promising solution for future gigantic multiple-input multiple-output (MIMO) systems, enabling beamforming with greatly reduced hardware and computational cost. However, channel estimation for MiLAC-aided systems remains an open problem. Conventional least squares (LS) and minimum mean square error (MMSE) estimation rely on intensive digital computation, which undermines the computational advantage offered by MiLACs. In this letter, we propose efficient LS and MMSE channel estimation schemes for MiLAC-aided MIMO systems. By designing the training precoder and combiner implemented by lossless and reciprocal MiLACs, the proposed schemes perform LS and MMSE estimation in the analog domain, leaving only simple digital scaling. They achieve identical estimation performance to their digital counterparts while significantly reducing computational complexity. Numerical results verify the effectiveness of the proposed schemes.

eess.SP

Joint Subcarrier Phase Recovery for Nonlinearity Mitigation

We propose a low-complexity phase recovery scheme that simultaneously mitigates laser phase noise and fiber nonlinearity across several subcarriers. In a long single-span link with Raman amplification, the scheme achieves 0.9 dB gain with 99 real multiplications per complex symbol.

eess.SP