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Blind Source Separation and Equalization Based on Support Vector Regression for MIMO Systems

IEICE TRANSACTIONS ON COMMUNICATIONS 2018年第3期E101B卷 698-708页

作者： Sun, Chao Yang, Ling Du, Juan Sun, Fenggang Chen, Li Xi, Haipeng Du, Shenglei Lanzhou Univ Sch Informat Sci & Engn Lanzhou 730000 Gansu Peoples R China Shandong Agr Univ Sch Informat Sci & Engn Tai An 271000 Shandong Peoples R China

In this paper, we first propose two batch blind source separation and equalization algorithms based on support vector regression (SVR) for linear time-invariant multiple input multiple output (MIMO) systems. The proposed algorithms combine the conventional cost function of SVR with error functions of classical on-line algorithm for blind equalization: both error functions of constant modulus algorithm (CMA) and radius directed algorithm (RDA) are contained in the penalty term of SVR. To recover all sources simultaneously, the cross-correlations of equalizer outputs are included in the cost functions. Simulation experiments show that the proposed algorithms can recover all sources successfully and compensate channel distortion simultaneously. With the use of iterative re-weighted least square (IRWLS) solution of SVR, the proposed algorithms exhibit low computational complexity. Compared with traditional algorithms, the new algorithms only require fewer samples to achieve convergence and perform a lower residual interference. For multilevel signals, the single algorithms based on constant modulus property usually show a relatively high residual error, then we propose two dual-mode blind source separation and equalization schemes. Between them, the dual-mode scheme based on SVR merely requires fewer samples to achieve convergence and further reduces the residual interference.

关键词： MIMO systems blind source separation blind equalization support vector regression constant modulus algorithm radius directed algorithm

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Pilot decontamination for multi-cell massive MIMO systems using asynchronous pilot design and data-aided channel estimation

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PHYSICAL COMMUNICATION 2018年 30卷 76-85页

作者： Huy-Dung Han Dang-An Nguyen Van-Duc Nguyen Tien-Hoa Nguyen Zia, Muhammad Hanoi Univ Sci & Technol Sch Elect & Telecommun Hanoi Vietnam Quaid I Azam Univ Dept Elect Islamabad Pakistan

In this work, we investigate the pilot contamination problem in multi-cell massive multi-input multi-output (MIMO) systems. The conventional approaches to address pilot contamination for multi-cell MIMO systems impose orthogonal pilots constraint across multiple users and cells, which leads to bandwidth inefficiency under large number of active users. We propose an uplink (UL) transmission protocol in which the pilot segments of users partially overlap across cells and even overlap with data from other cells, which provides more freedom in system designing. We also apply semi-blind algorithms at base station (BS) in order to separate the data streams of each user. Our analysis shows that semi-blind receiver removes pilot contamination effectively under large UL data length. The simulation results demonstrate that the performance of the proposed protocol with semi-blind receiver employing constant modulus algorithm (CMA) is superior as compared to the existing schemes. (C) 2018 Elsevier B.V. All rights reserved.

关键词： Massive MIMO Pilot contamination Least square estimation constant modulus algorithm

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Blind Equalization of Multilevel Signals via Support Vector Regression 10

Blind Equalization of Multilevel Signals via Support Vector ...

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10th International Conference on Advanced Computational Intelligence (ICACI)

作者： Sun, Chao Yang, Ling Chen, Li Zhang, Jiliang Yang, Rong Lanzhou Univ Sch Informat Sci & Engn Lanzhou Gansu Peoples R China

ISBN: (纸本)9781538643624

In this paper, two families of batch algorithms are constructed in the support vector regression (SVR) framework for blind equalization of multilevel signals. Specifically, the error functions of constant modulus algorithm CMA(p, 2) and multimodulus algorithm MMA(p,2) are contained in the penalty term of the SVR. Simulation results show that the proposed MMA(p,2)-based algorithms perform better than the CMA(p,2)based ones, which exhibit lower residual intersymbol interference (ISI) and higher probability of convergence. With respect to conventional dual-mode scheme, the MMA(p,2)-based algorithms show better performance in the case of higher noise or smaller data block, therefore they are robust and more suitable for multilevel signals. In addition, they avoid tedious switching mechanism of dual-mode scheme and overcome phase rotation.

关键词： blind equalization batch algorithm support vector regression constant modulus algorithm multimodulus algorithm

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Blind Channel Equalization using Variational Autoencoders

Blind Channel Equalization using Variational Autoencoders

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IEEE International Conference on Communications (ICC) / Workshop on Integrating UAVs into 5G

作者： Caciularu, Avi Burshtein, David Tel Aviv Univ Sch Elect Engn IL-6997801 Tel Aviv Israel

ISBN: (纸本)9781538643280

A new maximum likelihood estimation approach for blind channel equalization, using variational autoencoders (VAEs), is introduced. Significant and consistent improvements in the error rate of the reconstructed symbols, compared to constant modulus equalizers, are demonstrated. In fact, for the channels that were examined, the performance of the new VAE blind channel equalizer was close to the performance of a non-blind adaptive linear minimum mean square error equalizer. The new equalization method enables a significantly lower latency channel acquisition compared to the constant modulus algorithm (CMA). The VAE uses a convolutional neural network with two layers and a very small number of free parameters. Although the computational complexity of the new equalizer is higher compared to CMA, it is still reasonable, and the number of free parameters to estimate is small.

关键词： Variational autoencoders blind channel equalization deep learning convolutional neural networks constant modulus algorithm maximum likelihood

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Fractionally Nyquist Sample Spaced ARMA Blind Equalizer for Direct Signal Recovery in Passive Bistatic Radar

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Chinese Journal of Electronics 2017年第3期27卷 658-666页

作者： WANG Feng SHEN Wei JIANG Defu WEI Shuang Array and Information Processing Laboratory College of Computer and Information Hohai University Nanjing Research Institute of Electronics Technology

This paper proposes a modified signal processing structure based on the fractionally Nyquist sample spaced structure for passive bistatic *** recover the direct signal from the multipath clutter,an equalizer of the Auto regressive moving average(ARMA)type is proposed based on the fractionally Nyquist sample spaced constant modulus *** with the conventional Nyquist sample spaced equalizer,the equalizer of the fractionally Nyquist sample spaced ARMA structure is more effective in dealing with deep fading multipath channels with zeros near the unit *** simulations and real data tests indicate that the proposed approach outperforms the conventional processing structure in terms of both clutter residual and mean square error.

关键词： Passive bistatic radar constant modulus algorithm Direct signal recovery Multipath clutter cancellation Fractionally spaced equalizer

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A CMA-FRESH Whitening Filter for Blind Interference Rejection

A CMA-FRESH Whitening Filter for Blind Interference Rejectio...

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作者： Jauhar, Ahmad Shujauddin Virginia Tech | University

The advent of spectrum sharing has increased the need for robust interference rejection methods. The Citizens Broadband Radio Service (CBRS) band is soon to be occupied by LTE waveforms and License Assisted Access (LAA) will have LTE signals coexisting with other signals in the 5 GHz band. In anticipation of this need, we present a method for interference rejection of cyclostationary signals, which can also help avoid interference through better detection of low power co-channel signals. The method proposed in this thesis consists of a frequency-shift (FRESH) filter which acts as a whitening filter, canceling the interference by exploiting its cyclostationarity. It learns the cyclostationary characteristics of the interferer blindly, through a property restoration algorithm which aims to drive the spectrum to white noise. The property restoration algorithm, inspired by the constant modulus algorithm (CMA), is applied to each frequency bin to determine the optimal coefficients for the proposed CMA FRESH whitening filter (CFW). The performance of the CFW in interference rejection is compared to a time-invariant version, and proposed use cases are analyzed. The use cases consist of the rejection of a high powered, wider bandwidth interferer which is masking the signal-of-interest (SOI). The interferer is rejected blindly, with no knowledge of its characteristics. We analyzed signal detection performance in the case that the SOI is another user with much lower power, for multiple types of SOIs ranging from BPSK to OFDM. We also deal with the case that the SOI is to be received and demodulated; we recover it and compare resulting bit error rates to state of the art FRESH filters. The results show significantly better signal detection and recovery.

关键词： Cyclostationarity FRESH filter constant modulus algorithm Interference Rejection Signal Detection Hidden Node Problem Spectrum Sharing Thesis

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An improved CMA for dispersion compensation in 100 Gbps DP-QPSK optical signal transmission system

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OPTIK 2017年 136卷 480-486页

作者： Qin, Jiangyi Liu, Chunwu Huang, Zhiping Su, Shaojing Zhang, Yimeng Natl Univ Def Technol Coll Mechatron Engn & Automat Changsha 410073 Hunan Peoples R China

An improved constant modulus algorithm (CMA) for dispersion compensation in 100 Gbps Dual Polarization-Quadrature Phase Shift Keying (DP-QPSK) optical signal transmission system is proposed to achieve better reliability receiving performances. In the receiver, we combine variable step size and Mean-Square Error (MSE) to improve the conventional CMA. Compared to conventional CMA, the proposed algorithm has a better performance in adapting the time varying channel and the strong noise. Meanwhile, the proposed algorithm has a faster convergence rate than the previous one. Simulation results show that the improved CMA can achieve the dispersion and polarization demultiplexing of 100 Gbps DP-QPSK optical signal transmission system efficiently. (C) 2017 Elsevier GmbH. All rights reserved.

关键词： Optical communications constant modulus algorithm Dispersion compensation Variable step size Mean-square error

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Kuiper Test based Modulation Level Classification under Unknown Frequency Selective Channels 5

Kuiper Test based Modulation Level Classification under Unkn...

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5th IEEE Global Conference on Signal and Information Processing (GlobalSIP)

作者： Chaudhari, Shailesh Cabric, Danijela Univ Calif Los Angeles Dept Elect Engn Los Angeles CA 90024 USA

ISBN: (纸本)9781509059904

In this paper, we address the problem of identifying the modulation level of the received signal under an unknown frequency selective channel. The modulation level classification is performed using reduced-complexity Kuiper (rcK) test which utilizes the distribution of signal features such as magnitude of the received samples or phase difference in consecutive received samples. However, in frequency selective channels, these features are severely distorted resulting in a poor classification performance. We propose to use constant modulus algorithm (CMA) to mitigate the impact of the frequency selective channel on the signal feature. Simulation and analytical results show that the proposed CMA-rcK technique outperforms state-of-the-art cumulant-based technique as well as blind equalizer-based technique that uses Alphabet Matched algorithm.

关键词： Alphabet matched algorithm constant modulus algorithm reduced-complexity Kuiper cumulants

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MIMO Equalization of 16-QAM Signal Blocks using an FFT-based Alphabet-Matched CMA 51

MIMO Equalization of 16-QAM Signal Blocks using an FFT-based...

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51st Annual Conference on Information Sciences and Systems (CISS)

作者： Taiwo, Peter O. Cole-Rhodes, Arlene Morgan State Univ Elect & Comp Engn Dept Baltimore MD 21251 USA

ISBN: (纸本)9781509047802

In this work we investigate the blind equalization of signal blocks of data, which have been transmitted over a multiple-input/multiple-output channel using 16-QAM modulation. We apply the Fast Fourier Transform (FFT) in order to improve the efficiency of the blind equalizer update. Our equalizer is based on a cost function, which is specified as the sum of the constant modulus algorithm (CMA) and the alphabet-matched algorithm (AMA). The equalization is done using a block processing multistage approach as was introduced in [3], but with an FFT implementation. In this work, a 3-input/7-output MIMO communication system is considered, and the performance of the MIMO equalizer is analyzed using Monte Carlo simulations. Performance is measured based on the average symbol error rate (SER) and the total number of equalized cases. In addition, initial comparative results are provided for a fixed number of transmit antennas, but with varying numbers of receive antennas.

关键词： Blind equalization constant modulus algorithm Alphabet matched algorithm FFT Channel estimation MIMO Communication system

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constant modulus algorithms using hyperbolic Givens rotations

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SIGNAL PROCESSING 2014年 104卷 412-423页

作者： Ikhlef, A. Iferroujene, R. Boudjellal, A. Abed-Meraim, K. Belouchrani, A. Univ British Columbia ECE Dept Vancouver BC V6T 1Z4 Canada Ecole Natl Polytech EE Dept Algiers 16200 Algeria Polytech Orleans PRISME Lab F-45067 Orleans France

We propose two new algorithms to minimize the constant modulus (CM) criterion in the context of blind source separation. The first algorithm, referred to as Givens CMA (G-CMA), uses unitary Givens rotations and proceeds in two stages: prewhitening step, which reduces the channel matrix to a unitary one followed by a separation step where the resulting unitary matrix is computed as a product of Givens rotations. However, for small sample sizes, the prewhitening does not make the channel matrix close enough to unitary and hence applying Givens rotations alone does not provide satisfactory performance. To remediate to this problem, we propose to use Hyperbolic rotations in conjunction with Givens rotations. This second algorithm, referred to as Hyperbolic G-CMA (HG-CMA), is shown to outperform the G-CMA as well as the Analytical CMA (ACMA). The last part of this paper is dedicated to an efficient adaptive implementation of the HG-CMA and to performance assessment through numerical experiments. (C) 2014 Elsevier B.V. All rights reserved.

关键词： Blind source separation constant modulus algorithm Adaptive CMA Sliding window Hyperbolic rotations Givens rotations

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