Low-dimensional subspace estimation of continuous-doppler-spread channel in OTFS systems

Qu, H., Liu, G., Zhang, L. , Imran, M. A. and Wen, S. (2021) Low-dimensional subspace estimation of continuous-doppler-spread channel in OTFS systems. IEEE Transactions on Communications, 69(7), pp. 4717-4731. (doi: 10.1109/TCOMM.2021.3072744)

Abstract

Orthogonal time frequency space (OTFS) has shown to be a promising modulation technology that achieves the robust wireless transmission in high-mobility environments. The high mobility incurred Doppler effect in OTFS system, is represented as a continuous and relatively large band in the Doppler frequency. It yields the equivalent channel responses (ECRs) in the system change significantly within one symbol block, posing a challenge to channel estimation (CE) or tracking. In order to tackle this issue, in this paper, a set of transform-domain basis functions is designed to span a low-dimensional subspace for modeling the OTFS channel. Then, the CE can be performed by estimating a few projection coefficients of ECRs in the developed subspace, with training pilots. According to the individual transmission characteristic of OTFS signal, we propose a corner-inserted pilot pattern, which targets the low pilot overhead and satisfactory CE performance. Moreover, an OTFS signal detector, leveraging the time-domain channel equalization, linear-complexity interference cancellation and delay-Doppler domain maximal ratio combining detection, is developed to retrieve the transmitted data symbols. The simulations show the precisely estimated ECRs enable the detector to ideally demodulate 256-ary quadrature amplitude modulation signaling, under a velocity of 550 km/h at 5.9 GHz carrier frequency.

• Item Type: Articles
• Additional Information: This work was supported in part by the National Natural Science Foundation of China under Grants 62071097, U20A20184, and in part by the 111 Project under Grant B17008. (Corresponding author: Guanghui Liu).
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Imran, Professor Muhammad and Zhang, Professor Lei
• Authors: Qu, H., Liu, G., Zhang, L., Imran, M. A., and Wen, S.
• College/School: College of Science and Engineering > School of Engineering > Systems Power and Energy
• Journal Name: IEEE Transactions on Communications
• Publisher: IEEE
• ISSN: 0090-6778
• ISSN (Online): 1558-0857
• Published Online: 12 April 2021
• Copyright Holders: Copyright © 2021 IEEE
• First Published: First published in IEEE Transactions on Communications 69(7): 4717-4731
• Publisher Policy: Reproduced in accordance with the publisher copyright policy