A novel joint channel estimation and equalization algorithm for MIMO-SCFDE systems over doubly selective channels

Xie, Zhen; Chen, Xihong; Li, Chenglong

doi:10.1016/j.dsp.2018.01.014

Cited by 8 publications

(5 citation statements)

References 23 publications

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“…Salman M B [14] proposed a receiver structure that combines the outputs of the fractional delayed bank of FDEs to overcome the performance degradation of FDE for highly frequency selective channels with nonlinear distortion. XIE Z D [15] studied a joint channel estimation and equalization algorithm over time-frequency doubly selective channels, which enhances the information interaction between the two and achieves the joint optimization of channel estimation and equalization. BAI G [16] designed a subnetwork for each of the three modules, channel estimation, noise power estimation, and channel equalization, and applied deep learning to the SC-FDE algorithm to reduce the amount of training data required for network convergence and improve the channel generalization capability.…”

Section: Related Workmentioning

confidence: 99%

An Estimated δ-Based Iterative Block Decision Feedback Equalization in SC-FDE System

et al. 2022

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We provide a novel nonlinear frequency domain equalization algorithm for the frequency domain equalization of an SC-FDE system by improving the classical iterative block decision feedback equalization (IBDFE) algorithm and applying δ estimation to the improved algorithm. The improvement of the IBDFE algorithm is carried out by replacing the ZF equalization in the feedback branch with the MMSE equalization and eliminating the iteration of the correlation factor, thus reducing the noise error and the computational complexity of the original algorithm. δ estimation can estimate residual inter-symbol interference in the signal after MMSE equalization and reject it, thus further improving the equalization accuracy. The simulation results show that the performance of the novel algorithm is better than that of the IBDFE algorithm with similar complexity, or the complexity of the novel algorithm is lower than that of the IBDFE algorithm with similar performance.

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Section: Related Workmentioning

confidence: 99%

An Estimated δ-Based Iterative Block Decision Feedback Equalization in SC-FDE System

et al. 2022

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“…Orthogonal frequency division multiplexing (OFDM) is an effective modulation scheme and has gained the most popularity. But the OFDM waveform is the superposition of many orthogonal subcarrier signals, so the peak to average power rate is very high 1 . Single‐carrier frequency domain equalization (SC‐FDE) is a new broadband wireless communication technology, which combines the advantages of single‐carrier transmission and OFDM.…”

Section: Introductionmentioning

confidence: 99%

The research on channel estimation and signal‐noise ratio estimation based on minimum error entropy kalman filter for single carrier frequency domain equalization system

Pengyu

Xiang

Liang

et al. 2022

Int J Communication

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In this paper, the channel estimation and signal-to-noise ratio (SNR) estimation technique of single-carrier frequency domain equalization (SC-FDE) system under low SNR in aeronautical multipath channel are studied, a SNR estimation algorithm which is easy to implement in engineering and an improved LS channel estimation algorithm based on Kalman filter using minimum error entropy (MEE-KF) are proposed. This paper first introduces the SC-FDE system and introduces the principle of MEE-KF, and then, the channel estimation flow based on MEE-KF is obtained by combining it with the traditional LS channel estimation algorithm, which makes the estimation results perform better. Simulation results show that after getting more accurate noise variance, the channel estimation results can better follow the changes of the channel after MEE-KF processing, so as to resist the doppler frequency offset effect and make the channel estimation results more accurate, that is the channel response results of the data part can be closer to the real situation, so that the communication performance of SC-FDE system has also been greatly improved.

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“…The authors of [10] utilize the virtual pilot to assist channel estimation and partial minimum-mean-square error (MMSE) equalization to improve the accuracy of the estimation. To solve the problem of lack of information interaction between channel estimation and channel equalization in doubly selection channels, the work in [11] proposes a novel joint channel estimation and equalization (JCEE) algorithm for MIMO-SCFDE systems that combines iterative expectation maximization-based least square (LS) channel estimation, MMSE equalization based on inter-frequency interference (IFI), time-domain IFI cancellation, and data detector. The traditional signal detection scheme effectively improves the system's bit error rate (BER) performance through the optimization of various algorithms.…”

Section: Introductionmentioning

confidence: 99%

A Novel Signal Detection Scheme Based on Adaptive Ensemble Deep Learning Algorithm in SC-FDE Systems

Qiao

et al. 2020

IEEE Access

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Reliable signal detection plays an essential role in enhancing the quality of signal transmission in wireless communication systems. In this paper, we combine signal detection theory with a deep learning model and propose a novel signal detection scheme based on adaptive ensemble long short term memory (AE-LSTM) neural network to handle wireless single carrier frequency domain equalization (SC-FDE) systems in an end-to-end manner. The feature information used for offline training of the deep learning model is extracted from the received signal containing channel state information (CSI) after the multi-path channel and fast Fourier transform (FFT), and the labels are assigned according to the constellation map adopted at the transmitter. To improve the adaptability of the system, we utilize the received power under different delays as the adaptive factor to integrate the output of each sub-network. Then the original data generated by the channel model is recovered by using the trained model instead of channel estimation and frequency domain equalization. Comparative experiments on SC-FDE symbol detection demonstrate that the proposed scheme achieves better performance in terms of reliability than the traditional scheme and the similar deep learning scheme.

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A novel joint channel estimation and equalization algorithm for MIMO-SCFDE systems over doubly selective channels

Cited by 8 publications

References 23 publications

An Estimated δ-Based Iterative Block Decision Feedback Equalization in SC-FDE System

An Estimated δ-Based Iterative Block Decision Feedback Equalization in SC-FDE System

The research on channel estimation and signal‐noise ratio estimation based on minimum error entropy kalman filter for single carrier frequency domain equalization system

A Novel Signal Detection Scheme Based on Adaptive Ensemble Deep Learning Algorithm in SC-FDE Systems

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