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Delay-Doppler-Domain Channel Estimation and Reduced-Complexity Detection of Faster-than-Nyquist Signaling Aided OTFS

Zekun Hong, Shinya Sugiura, Chao Xu, Lajos Hanzo

TL;DR

The paper tackles efficient channel estimation and data detection for OTFS-modulated faster-than-Nyquist signaling over doubly selective channels. It derives the DD-domain input-output relation under root-raised-cosine shaping, and introduces a four-step FTN-based pilot (FTNP) channel estimator along with a sparse, LU-based, reduced-complexity LMMSE equalizer. Results show OTFS-FTN achieving higher information rates than Nyquist OTFS at comparable BER, with notable 2 dB BER gains at moderate-to-high rates for the same transmission rate. The work demonstrates practical gains in spectral efficiency and Doppler resilience for high-mobility scenarios using realistic pulse shaping and low-complexity receivers.

Abstract

We conceive a novel channel estimation and data detection scheme for OTFS-modulated faster-than-Nyquist (FTN) transmission over doubly selective fading channels, aiming for enhancing the spectral efficiency and Doppler resilience. The delay-Doppler (DD) domain's input-output relationship of OTFS-FTN signaling is derived by employing a root-raised cosine (RRC) shaping filter. More specifically, we design our DD-domain channel estimator for FTN-based pilot transmission, where the pilot symbol interval is lower than that defined by the classic Nyquist criterion. Moreover, we propose a reduced-complexity linear minimum mean square error equalizer, supporting noise whitening, where the FTN-induced inter-symbol interference (ISI) matrix is approximated by a sparse one. Our performance results demonstrate that the proposed OTFS-FTN scheme is capable of enhancing the achievable information rate, while attaining a comparable BER performance to both that of its Nyquist-based OTFS counterpart and to other FTN transmission schemes, which employ the same RRC shaping filter.

Delay-Doppler-Domain Channel Estimation and Reduced-Complexity Detection of Faster-than-Nyquist Signaling Aided OTFS

TL;DR

The paper tackles efficient channel estimation and data detection for OTFS-modulated faster-than-Nyquist signaling over doubly selective channels. It derives the DD-domain input-output relation under root-raised-cosine shaping, and introduces a four-step FTN-based pilot (FTNP) channel estimator along with a sparse, LU-based, reduced-complexity LMMSE equalizer. Results show OTFS-FTN achieving higher information rates than Nyquist OTFS at comparable BER, with notable 2 dB BER gains at moderate-to-high rates for the same transmission rate. The work demonstrates practical gains in spectral efficiency and Doppler resilience for high-mobility scenarios using realistic pulse shaping and low-complexity receivers.

Abstract

We conceive a novel channel estimation and data detection scheme for OTFS-modulated faster-than-Nyquist (FTN) transmission over doubly selective fading channels, aiming for enhancing the spectral efficiency and Doppler resilience. The delay-Doppler (DD) domain's input-output relationship of OTFS-FTN signaling is derived by employing a root-raised cosine (RRC) shaping filter. More specifically, we design our DD-domain channel estimator for FTN-based pilot transmission, where the pilot symbol interval is lower than that defined by the classic Nyquist criterion. Moreover, we propose a reduced-complexity linear minimum mean square error equalizer, supporting noise whitening, where the FTN-induced inter-symbol interference (ISI) matrix is approximated by a sparse one. Our performance results demonstrate that the proposed OTFS-FTN scheme is capable of enhancing the achievable information rate, while attaining a comparable BER performance to both that of its Nyquist-based OTFS counterpart and to other FTN transmission schemes, which employ the same RRC shaping filter.
Paper Structure (12 sections, 7 equations, 18 figures, 3 tables, 3 algorithms)

This paper contains 12 sections, 7 equations, 18 figures, 3 tables, 3 algorithms.

Table of Contents

  1. INTRODUCTION
  2. System Model
  3. Transmit Signal
  4. Channel Model
  5. Receive Signal
  6. FTNP-Based Channel Estimation
  7. LMMSE-Based OTFS-FTN Receiver
  8. Low-Complexity LMMSE Equalizer
  9. Achievable Information Rate
  10. Performance Results
  11. Conclusions
  12. Proof of Theorem 1: OTFS-FTN Input-Output Relationship in Delay-Doppler Domain for RRC Pulses

Figures (18)

  • Figure 1: Schematic of the proposed OTFS-FTN transceiver.
  • Figure 2: DD-domain frame structure of $\mathbf{X}$, including the pilot symbol, guard symbols, and data symbols.
  • Figure 3: The structure of LU decompositon for $\mathbf{W}_1$.
  • Figure 4: Modeling errors of the channels and weights: (a) $\epsilon_0=\left\|\mathbf{H}_{\mathrm{t}}-\mathbf{H}_{\mathrm{s}}\right\|_F^2$, and (b) $\epsilon_1=\left\|\mathbf{W}_{\mathrm{t}}-\mathbf{W}_{\mathrm{1}}\right\|_F^2$.
  • Figure 5: NMSE of the proposed FTNP-based channel estimation for different false alarm rates.
  • ...and 13 more figures