Efficient Channel Equalization and Symbol Detection for MIMO OTFS Systems

Qu, Huiyang; Liu, Guanghui; Imran, Muhammad Ali; Wen, Shuangchun; Zhang, Lei

doi:10.1109/twc.2022.3151821

Cited by 21 publications

(3 citation statements)

References 48 publications

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“…where ρ is the number of multipath between receiver r-th RA and t-th TA [16], [38] for 1 ≤ r ≤ N r , 1 ≤ t ≤ N t , and h i,r,t represents the wireless channel coefficient corresponding to the i-th multi-path component. Let X DD,t ∈ C M ×N denote the DD-domain transmit symbol matrix for the t-th TA.…”

Section: Mimo-otfs System Modelmentioning

confidence: 99%

Online Bayesian Learning-Aided Sparse CSI Estimation in OTFS Modulated MIMO Systems for Ultra-High-Doppler Scenarios

Mehrotra,

Srivastava,

Asifa

et al. 2024

IEEE Trans. Commun.

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Bayesian learning-assisted channel state information (CSI) estimation schemes are conceived for single input single output (SISO) and multiple input multiple output (MIMO) orthogonal time frequency space (OTFS) modulated systems. To begin with, an end-to-end system model is derived in the delay-Doppler (DD)-domain, followed by an online CSI estimation (CE) framework for SISO-OTFS systems. Next, the sequential minimum mean square error (MMSE) estimator is derived for this model which utilizes expectation maximization (EM) based sparse Bayesian learning (SBL) for initialization of the online estimation procedure. Additionally, a low-complexity detection technique is developed for the system under consideration, which is accomplished via an analogous time-frequency (TF)-domain system model that leads to a block-diagonal TF-domain channel matrix. The paradigm designed for online CE is subsequently extended to MIMO-OTFS systems. The corresponding DDdomain CSI is shown to be simultaneously row and group sparse. Hence a novel EM-based row and group sparse Bayesian learning scheme is developed for determining the initialization parameters for the above online algorithm. As a further continuation, a low-complexity detector is also proposed for MIMO-OTFS systems based on an iterative block matrix inversion technique. Furthermore, time-recursive Bayesian Cramer-Rao lower bounds (BCRLBs) are derived to benchmark the MSE performance of the proposed schemes for both the systems. Finally, simulation results are presented to demonstrate the efficiency of the proposed online estimation techniques.

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Section: Mimo-otfs System Modelmentioning

confidence: 99%

Online Bayesian Learning-Aided Sparse CSI Estimation in OTFS Modulated MIMO Systems for Ultra-High-Doppler Scenarios

Mehrotra,

Srivastava,

Asifa

et al. 2024

IEEE Trans. Commun.

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“…In [31], the authors proposed a low-complexity detector and low-overhead pilot pattern for OTFS system with a large-scale antenna array at the receiver. A Bayesian learning aided simultaneous row and group sparse channel estimation method was proposed in [32] and an efficient symbol detection scheme was proposed in [33] for MIMO-OTFS systems. The authors in [34] applied a deterministic pilot pattern and developed an efficient channel estimation scheme for downlink massive MIMO-OTFS systems.…”

Section: Introductionmentioning

confidence: 99%

OTFS Signaling for SCMA With Coordinated Multi-Point Vehicle Communications

Deng

González

et al. 2023

IEEE Trans. Veh. Technol.

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This paper investigates an uplink coordinated multipoint (CoMP) coverage scenario, in which multiple mobile users are grouped for sparse code multiple access (SCMA), and served by the remote radio head (RRH) in front of them and the RRH behind them simultaneously. We apply orthogonal time frequency space (OTFS) modulation for each user to exploit the degrees of freedom arising from both the delay and Doppler domains. As the signals received by the RRHs in front of and behind the users experience respectively positive and negative Doppler frequency shifts, our proposed OTFS-based SCMA (OBSCMA) with CoMP system can effectively harvest extra Doppler and spatial diversity for better performance. Based on maximum likelihood (ML) detector, we analyze the single-user average bit error rate (ABER) bound as the benchmark of the ABER performance for our proposed OBSCMA with CoMP system. We also develop a customized Gaussian approximation with expectation propagation (GAEP) algorithm for multi-user detection and propose efficient algorithm structures for centralized and decentralized detectors. Our proposed OBSCMA with CoMP system leads to stronger performance than the existing solutions. The proposed centralized and decentralized detectors exhibit effective reception and robustness under channel state information uncertainty.

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“…The existing linear detectors such as zero-forcing (ZF) and linear minimum mean square error (LMMSE) [4] leading to severe performance loss. Recently, several studies [5], [6], [9] exploit the typical structure and characteristic of OTFS transmission matrix for interference cancellation and performance improvement. Unfortunately, the typical OTFS channel matrix structures do not always hold and the interference cancellation may cause error propagation.…”

Section: Introductionmentioning

confidence: 99%

Low-Complexity Memory AMP Detector for High-Mobility MIMO-OTFS SCMA Systems

Liu¹,

Huang²,

G.³

et al. 2023

Preprint

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Efficient signal detectors are rather important yet challenging to achieve satisfactory performance for large-scale communication systems. This paper considers a non-orthogonal sparse code multiple access (SCMA) configuration for multipleinput multiple-output (MIMO) systems with recently proposed orthogonal time frequency space (OTFS) modulation. We develop a novel low-complexity yet effective customized Memory approximate message passing (AMP) algorithm for channel equalization and multi-user detection. Specifically, the proposed Memory AMP detector enjoys the sparsity of the channel matrix and only applies matrix-vector multiplications in each iteration for low-complexity. To alleviate the performance degradation caused by positive reinforcement problem in the iterative process, all the preceding messages are utilized to guarantee the orthogonality principle in Memory AMP detector. Simulation results are finally provided to illustrate the superiority of our Memory AMP detector over the existing solutions.

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Efficient Channel Equalization and Symbol Detection for MIMO OTFS Systems

Cited by 21 publications

References 48 publications

Online Bayesian Learning-Aided Sparse CSI Estimation in OTFS Modulated MIMO Systems for Ultra-High-Doppler Scenarios

Online Bayesian Learning-Aided Sparse CSI Estimation in OTFS Modulated MIMO Systems for Ultra-High-Doppler Scenarios

OTFS Signaling for SCMA With Coordinated Multi-Point Vehicle Communications

Low-Complexity Memory AMP Detector for High-Mobility MIMO-OTFS SCMA Systems

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