Learning based Delay-Doppler Channel Estimation with Interleaved Pilots in OTFS

Mattu, SR and Chockalingam, A (2022) Learning based Delay-Doppler Channel Estimation with Interleaved Pilots in OTFS. In: 96th IEEE Vehicular Technology Conference, VTC 2022-Fall 2022, 26 - 29 September 2022, London.

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Abstract

Traditionally, channel estimation in orthogonal time frequency space (OTFS) is carried out in the delay-Doppler (DD) domain by placing pilot symbols surrounded by guard bins in the DD grid. This results in reduced spectral efficiency as the guard bins do not carry information. In the absence of guard bins, there is leakage from pilot symbols to data symbols and vice versa. Therefore, in this paper, we consider an interleaved pilot (IP) placement scheme with a lattice-type arrangement (which does not have guard bins) and propose a deep learning architecture using recurrent neural networks (referred to as IPNet) for efficient estimation of DD domain channel state information. The proposed IPNet is trained to overcome the effects of leakage from data symbols and provide channel estimates with good accuracy (e.g., the proposed scheme achieves a normalized mean square error of about 0.01 at a pilot SNR of 25 dB). Our simulation results also show that the proposed IPNet architecture achieves good bit error performance while being spectrally efficient. For example, the proposed scheme uses 12 overhead bins (12 pilot bins and no guard bins) for channel estimation in a considered frame while the embedded pilot scheme uses 25 overhead bins (1 pilot bin and 24 guard bins). © 2022 IEEE.

Item Type:	Conference Paper
Publication:	IEEE Vehicular Technology Conference
Publisher:	Institute of Electrical and Electronics Engineers Inc.
Additional Information:	The copyright for this article belongs to Institute of Electrical and Electronics Engineers Inc.
Keywords:	Channel estimation; Channel state information; Frequency estimation; Mean square error; Network architecture; Signal to noise ratio; Spectrum efficiency, Data symbols; Deep learning; Delay-dopple channel estimation; Doppler; Doppler channels; Interleaved pilot; Orthogonal time frequency space modulation; Pilot symbols; Spectral efficiencies; Time-frequency space, Recurrent neural networks
Department/Centre:	Division of Electrical Sciences > Electrical Communication Engineering
Date Deposited:	16 Feb 2023 05:39
Last Modified:	16 Feb 2023 05:39
URI:	https://eprints.iisc.ac.in/id/eprint/80332

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