Superimposed Channel Estimation in OTFS Modulation Using Compressive Sensing

TL;DR

This paper introduces a superimposed channel estimation method for OTFS that leverages sparsity in the delay-Doppler domain, eliminating pilot overhead and improving robustness in high-speed wireless environments.

Contribution

It proposes a novel superimposed channel estimation technique using sparse recovery and message passing, reducing pilot overhead in OTFS systems.

Findings

Achieves accurate channel estimation without pilot overhead.

Does not suffer from high peak-to-average power ratio.

Enhances detection performance in high Doppler scenarios.

Abstract

Orthogonal time frequency space (OTFS) technique is a two-dimensional modulation method that multiplexes information symbols in the delay-Doppler (DD) domain. OTFS combats high Doppler shift existing in high speed wireless communication. However, conventional channel estimation in OTFS suffers from high pilot overhead because guard symbols occupy a significant part of the DD domain grids. In this paper, a superimposed channel estimation is proposed which can completely estimate channel parameters without considering pilot overhead and performance degradation. As the channel state information (CSI) in the DD domain is sparse, a sparse recovery algorithm orthogonal matching pursuit (OMP) is used. Besides, our proposed method does not suffer from high peak to average power ratio (PAPR). To detect information symbols, a message passing (MP) detector, which exploits the sparsity of DD channel representation, is employed.