Performance Analysis of Coded OTFS Systems Over High-Mobility Channels

Li, Shuangyang; Yuan, Jinhong; Yuan, Weijie; Wei, Zhiqiang; Bai, Baoming; Ng, Derrick Wing Kwan

doi:10.1109/twc.2021.3071493

Cited by 131 publications

(78 citation statements)

References 34 publications

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“…According to the derivations and analysis in Sec. III-A, it is clear that the challenge of linear equalization is how to efficiently solve (15), especially when the number of antennas and length of transmission block are large. In mathematics, the LSMR is a conjugate gradient based iterative algorithm to solve large and sparse equation as (15).…”

Section: B the Proposed Ts-domain Channel Equalizationmentioning

confidence: 99%

“…III-A, it is clear that the challenge of linear equalization is how to efficiently solve (15), especially when the number of antennas and length of transmission block are large. In mathematics, the LSMR is a conjugate gradient based iterative algorithm to solve large and sparse equation as (15). It is similar to the well-known least-squares QR decomposition (LSQR) approach [42], but has faster convergence speed and better numerical stability.…”

Section: B the Proposed Ts-domain Channel Equalizationmentioning

confidence: 99%

“…Then, the TF-domain data is modulated by a multi-carrier scheme, e.g., OFDM [13], [14]. Through this procedure, the transmitted data symbols can be equally impacted by the doubly-dispersive channel, thus mitigating the performance loss [15].…”

Section: Introductionmentioning

confidence: 99%

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Efficient Channel Equalization and Symbol Detection for MIMO OTFS Systems

Liu

Imran

et al. 2022

IEEE Trans. Wireless Commun.

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The application of multiple-input multiple-output (MIMO) over orthogonal time frequency space (OTFS) modulation is envisioned to provide high-data-rate wireless transmission in high-mobility environments. However, in these communication scenarios, the multiple-dimensional interference, which can generate from space, delay and Doppler domains, challenges the channel equalization and symbol detection at the MIMO-OTFS receiver. To tackle this issue, we propose a time-space domain channel equalizer, relying on the mathematical least squares minimum residual algorithm, to remove the channel distortion on data symbols. The proposed channel equalizer adopts a recursion method to achieve symbol estimates, which can realize fast convergence by leveraging the sparsity of MIMO-OTFS channel matrix. Instead of directly remapping the equalized OTFS symbols into data bits, we develop an enhanced data detection (EDD) scheme to iteratively demodulate the superposed multi-antenna signal. The EDD can not only realize the linear-complexity interference cancellation, but also efficiently reap the spatial and multi-path diversities of MIMO-OTFS channel. The simulations show the proposed channel equalization and EDD algorithms enable the MIMO-OTFS receiver to robustly demodulate multi-stream 256-ary quadrature amplitude modulation symbols, under a maximum velocity of 550 km/h at 5.9 GHz carrier frequency.

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Section: B the Proposed Ts-domain Channel Equalizationmentioning

confidence: 99%

Section: B the Proposed Ts-domain Channel Equalizationmentioning

confidence: 99%

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Efficient Channel Equalization and Symbol Detection for MIMO OTFS Systems

Liu

Imran

et al. 2022

IEEE Trans. Wireless Commun.

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“…full diversity in [1]), which is desirable to provide reliable communications over doubly dispersive channels. In particular, it has been demonstrated that OTFS is resilient to severe delay-Doppler shifts and outperforms OFDM significantly for both uncoded [11] and coded [16], [17] systems.…”

Section: Introductionmentioning

confidence: 99%

Performance Analysis and Window Design for Channel Estimation of OTFS Modulation

Wei¹,

Yuan²,

Li³

et al. 2021

Preprint

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In this paper, we investigate the impacts of transmitter and receiver windows on orthogonal time-frequency space (OTFS) modulation and propose a window design to improve the OTFS channel estimation performance. Assuming ideal pulse shaping filters at the transceiver, we first identify the role of window in effective channel and the reduced channel sparsity with conventional rectangular window. Then, we characterize the impacts of windowing on the effective channel estimation performance for OTFS modulation. Based on the revealed insights, we propose to apply a Dolph-Chebyshev (DC) window at either the transmitter or the receiver to effectively enhance the sparsity of the effective channel. As such, the channel spread due to the fractional Doppler is significantly reduced, which leads to a lower error floor in channel estimation compared with that of the rectangular window. Simulation results verify the accuracy of the obtained analytical results and confirm the superiority of the proposed window designs in improving the channel estimation performance over the conventional rectangular or Sine windows.

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“…Besides, OTFS directly exploits the multipath fading and channel fluctuations via the DD domain multiplexing, which is inherently suitable to tackle the dynamics of time-variant channels, compared to the conventional OFDM technique. In particular, it has been demonstrated that OTFS is resilient to delay-Doppler shifts and outperforms OFDM significantly for both uncoded [12] and coded [1], [14], [15] systems. More importantly, the 2D transformation from the DD domain to the TF domain employed by an OTFS modulator allows each information symbol to experience the whole TF domain channel over an OTFS frame.…”

Section: Introductionmentioning

confidence: 99%

Transmitter and Receiver Window Designs for Orthogonal Time Frequency Space Modulation

Wei

Yuan

et al. 2020

Preprint

Self Cite

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In this paper, we investigate the impacts of transmitter and receiver windows on the performance of orthogonal time-frequency space (OTFS) modulation and propose window designs to improve the OTFS channel estimation and data detection performance. In particular, assuming ideal pulse shaping filters at the transceiver, we derive the impacts of windowing on the effective channel and its estimation performance in the delay-Doppler (DD) domain, the total average transmit power, and the effective noise covariance matrix. When the channel state information (CSI) is available at the transceiver, we analyze the minimum squared error (MSE) of data detection and propose an optimal transmitter window to minimize the detection MSE. The proposed optimal transmitter window is interpreted as a mercury/water filling power allocation scheme, where the mercury is firstly filled before pouring water to pre-equalize the TF domain channels. When the CSI is not available at the transmitter but can be estimated at the receiver, we propose to apply a Dolph-Chebyshev (DC) window at either the transmitter or the receiver, which can effectively enhance the sparsity of the effective channel in the DD domain. Thanks to the enhanced DD domain channel sparsity, the channel spread due to the fractional Doppler is significantly reduced, which leads to a lower error floor in both channel estimation and data detection compared with that of rectangular window. Simulation results verify the accuracy of the obtained analytical results and confirm the superiority of the proposed window designs in improving the channel estimation and data detection performance over the conventional rectangular window design.

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Performance Analysis of Coded OTFS Systems Over High-Mobility Channels

Cited by 131 publications

References 34 publications

Efficient Channel Equalization and Symbol Detection for MIMO OTFS Systems

Efficient Channel Equalization and Symbol Detection for MIMO OTFS Systems

Performance Analysis and Window Design for Channel Estimation of OTFS Modulation

Transmitter and Receiver Window Designs for Orthogonal Time Frequency Space Modulation

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