A Virtual Pilot-Assisted Channel Estimation Algorithm for MIMO-SCFDE Systems Over Fast Time-Varying Multipath Channels

Xie, Zhen; Chen, Xihong; Liu, Xiaopeng

doi:10.1109/tvt.2018.2810081

Cited by 10 publications

(14 citation statements)

References 31 publications

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“…In the MIMO-SCFDE system, in addition to solving the problems of noise and channel fading, the receiver also needs to adopt equalization technology to overcome multi-antenna interference (MAI) caused by the superposition of received signals from multiple receiving antennas [21]. When the signal is equalized, the equalization matrix corresponding to the sub-channel is first calculated according to the channel matrix, and then the frequency domain equalization (FDE) on each sub-channel is performed to compensate the frequency selectivity of the channel directly [22]. The commonly used linear equalization methods include zero-forcing (ZF) equalization and minimum mean square error (MMSE) equalization [23].…”

Section: System Modelmentioning

confidence: 99%

Model-Driven Deep Learning Scheme for Adaptive Transmission in MIMO-SCFDE System

Qiao

et al. 2020

IEEE Access

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Adaptive transmission (AT) is considered as one of the critical technologies to enhance the effectiveness of communication systems. In this paper, we propose a model-driven deep learning (DL) scheme for AT in multiple-input multiple-output single-carrier frequency-domain equalization (MIMO-SCFDE) systems, in which the adaptive modulation network (AMNet) and adaptive demodulation network (ADNet) are adopted to complete the modulation of the signal and the modulation recognition of the receiver. Under the target bit error rate (BER), the adaptive modulation (AM) scheme can adjust the modulation mode selection of different transmitting antennas adaptively according to the estimated channel information to improve the throughput. The features required by the AMNet are extracted from the received signal, and the labels are assigned according to the optimal modulation scheme got by analyzing the signal detection performance. Since the spectral correlation function has a powerful ability to suppress noise and the cyclic spectrum varies with the modulation mode, we take the preprocessed cyclic spectrogram as the input of ADNet to achieve the adaptive modulation recognition (AMR). Comparative experiments demonstrate that the proposed scheme gets better performance in terms of throughput and reliability in MIMO-SCFDE systems than the traditional scheme and the existing DL scheme.

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Section: System Modelmentioning

confidence: 99%

Model-Driven Deep Learning Scheme for Adaptive Transmission in MIMO-SCFDE System

Qiao

et al. 2020

IEEE Access

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“…where the MSE matrix Λ can be obtained by substituting (36), (37) into (30). Finally, the extrinsic information based on the equalized signalŝ m output by the robust equalizer and entered into the channel decoder can be obtained by (31) and (32).…”

Section: B Channel Estimation Modelmentioning

confidence: 99%

“…To elaborate, substantial research efforts have been invested in conceiving reliable channel estimation algorithms [28]- [30] and pilot transmission strategies [31]- [33] for classic SC transmissions. However, these processes are invarially prone to channel estimation errors.…”

Section: Introductionmentioning

confidence: 99%

Joint Iterative Channel Estimation and Frequency-Domain Turbo Equalization for Single-Carrier Spatial Modulation

Zhao

Xiao

Yang

et al. 2019

IEEE Trans. Commun.

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Single carrier frequency-domain turbo equalization (SC-FDTE) has gained widespread adoption in the emerging broadband spatial modulation (S-M) systems operating in frequency selective channels, where the channel model considered is a quasi-static Rayleigh fading channel. In this paper, a new class of robust FDTE designs based on the minimum meansquare error (MMSE) criterion is conceived for broadband single-carrier SM (SC-SM) systems relying on realistic imperfect channel knowledge. First, a robust time-domain soft-decision feedback (TDSDF) aided FDTE is proposed to cope with channel estimation errors at the receiver. Furthermore, its robust frequencydomain soft-decision feedback (FDSDF) aided counterpart is derived to offer a low-complexity approximate solution. Finally, by exploiting the carefully selected reliable soft-decision output of the channel decoder as pilots, we refine the resultant decision-directed channel estimation. As a benefit, the performance of the two robust FDTEs can be further improved. Both our simulation results and our extrinsic information transfer (EXIT) chart analysis demonstrate that the proposed robust FDTEs achieve significant performance improvements over the conventional FDTEs. Index Terms-Single-carrier (SC), spatial modulation (SM), frequency-domain turbo equalizer (FDTE), imperfect channel knowledge.

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“…When the impulse noise is present, the performance of the conventional zero forcing (ZF) algorithms is poor due to no particular measure to counteract the effects of noise. The basic shortcoming associated with the linear equalizer while coping with the severe ISI stands as a motivation behind developing enormous research regarding the suboptimal nonlinear equalizers, which possesses minimal computational complexity, like decision feedback equalizer (DFE) [12,13]. The highly available challenge regarding the MIMO receiver is related to the complexity and the main role of the MIMO channel equalizer / detector is related to the separation of spatially multiple data flows on the receiver terminal.…”

Section: Introductionmentioning

confidence: 99%

Fractional weighted ZF equalizer: A novel approach for channel equalization in MIMO-OFDM system under impulse noise environment

Girija

Rao

2021

CST

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Impulse noise is the major factor degrading the performance of the wireless system, imposing the need for the impulse noise mitigation strategy. Mainly, in the multiple-input multiple-output (MIMO) and orthogonal frequency-division multiplexing (OFDM) system contaminated with the impulse noise creates a major impact in the performance as the conventional zero-forcing (ZF) equalizer as there is no satisfactory results. Thus, the paper concentrates on the impulse noise mitigation strategy based on the fractional weighed zero-forcing (FWZF) equalizer, which is the integration of the fractional concept in the Zero-Forcing equalizer. The noise impacts in the MIMO-OFDM system are minimized and the performance is enhanced due to the usage of the fractional theory in the ZF equalizer as the equalization values of the previous instances are interpreted for the formulation of the effective equalization value in the current instance of the ZF equalizer. The performance of the methods is done based on the valuation metrics, Bit Error Rate (BER), Mean Square Error (MSE), and Symbol Error Rate (SER) with respect to the Signal-to-Noise Ratio (SNR) and dissimilar antenna array size. It is found that the proposed Fractional Weighed Zero-Forcing equalizer outperformed the existing methods with a minimal BER and SER of 0.063, and 0.1038 while analyzing the methods in the Rayleigh environment.

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A Virtual Pilot-Assisted Channel Estimation Algorithm for MIMO-SCFDE Systems Over Fast Time-Varying Multipath Channels

Cited by 10 publications

References 31 publications

Model-Driven Deep Learning Scheme for Adaptive Transmission in MIMO-SCFDE System

Model-Driven Deep Learning Scheme for Adaptive Transmission in MIMO-SCFDE System

Joint Iterative Channel Estimation and Frequency-Domain Turbo Equalization for Single-Carrier Spatial Modulation

Fractional weighted ZF equalizer: A novel approach for channel equalization in MIMO-OFDM system under impulse noise environment

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