A Cyclic Shift Embedded Pilot based Channel Estimation for Multi-User MIMO-OTFS systems with fractional delay and Doppler

TL;DR

This paper introduces a cyclic shift embedded pilot scheme for multi-user MIMO-OTFS systems that significantly reduces pilot overhead while maintaining high estimation accuracy in high-mobility scenarios.

Contribution

It proposes a novel cyclic shift embedded pilot structure and a multi-dimensional channel estimation algorithm for multi-user MIMO-OTFS systems, reducing pilot overhead by over 30%.

Findings

Over 30% reduction in pilot overhead.

Superior channel estimation performance.

Balanced complexity and accuracy.

Abstract

Orthogonal time frequency space (OTFS) modulation has been proposed to meet the demand for reliable communication in high-mobility scenarios for future wireless networks. However, in multi-user OTFS systems, conventional embedded pilot schemes require independent pilot allocation for each user, leading to linearly increasing pilot overhead. To address these issues, in this paper, we investigate the uplink channel estimation and pilot design for multi-user multiple-input multiple-output (MIMO)-OTFS systems. We propose a multi-dimensional decomposition-based channel estimation algorithm. Specifically, the proposed algorithm first estimates the angles of arrivals (AoAs) via subspace decomposition-based method. A spatial projection matrix, constructed from the estimated AOAs, decouples the received signal by propagation path subspace, effectively mitigating inter-path interference. The remaining fractional delay and Doppler can be obtained by a compressed sensing (CS)-based off-grid channel estimation method. Furthermore, to reduce the pilot overhead in multi-user OTFS systems, this paper proposes a novel cyclic shift embedded pilot (CSEP) structure, which can reuse users through cyclic shift-orthogonality of Zadoff-Chu (ZC) sequences. Compared with conventional embedded pilot structures, the CSEP structure can save over 30\% of pilot overhead. Finally, an imporved channel estimation method based on the CSEP structure is proposed. Simulation results demonstrate that it achieves superior performance in channel estimation. Moreover, the proposed CSEP structure and channel estimation algorithm achieve a favorable balance between computational complexity, estimation accuracy, and bit error rate (BER) performance.