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IEEE Symposium on Computers and Communications (IEEE ISCC)

作者： Rocha, Danilo S. Favier, Gerard Fernandes, C. Alexandre R. Fed Univ Ceara UFC Dept Teleinformat Engn Fortaleza Ceara Brazil UCA CNRS I3S Lab Sophia Antipolis France

ISBN: (纸本)9781538669501

A three-hop AF MIMO relay system with tensor coding at the source and the relays is considered in this paper. The signals received at destination form a fifth-order tensor that satisfies a high-order nested Tucker decomposition, characterized by the concatenation of three Tucker models. We propose a receiver based on an alternating least square algorithm to jointly estimate the symbol matrix and the channels of each hop. Monte Carlo simulation results are provided to illustrate the behavior of the proposed system and of the semi-blind receiver. These simulation results show a performance closest to the one of the zero-forcing receiver, yielding a significant SER improvement due to the relay-assisted link when compared to the direct link.

关键词： MIMO systems nested Tucker decomposition semi-blind receivers tensor coding tensor models three-hop relaying

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Multi-filters guided low-rank tensor coding for image inpainting

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SIGNAL PROCESSING-IMAGE COMMUNICATION 2019年 73卷 70-83页

作者： Liu, Qiegen Li, Sanqian Xiao, Jing Zhang, Minghui Nanchang Univ Dept Elect Informat Engn Nanchang 330031 Jiangxi Peoples R China Wuhan Univ Sch Comp Sci Natl Engn Res Ctr Multimedia Software Wuhan 430072 Peoples R China

Image inpainting is a classical yet challenging inverse ill-posed problem. In this paper, we introduce the multi-filters guided low-rank tensor coding as a prior information to tackle it. The key innovation is to formulate multiple feature-domain tensors by convoluting the target image with multi-filters. Furthermore, by exploring a low-rank tensor coding, it can reduce the redundancy between sparse feature vectors at neighboring locations and improve the efficiency of the overall representation. The resulting non-convex model is iteratively tackled by gradient descent procedure for updating the image and by low-rank pursuit procedure for updating the multi-view features. Besides, we explore an aggregation version of proposed method for further improving the inpainting performance. Experimental results demonstrate that the proposed algorithms can faithfully recover image and outperform the current state-of-the-art approaches in terms of visual inspection, the quantitative peak signal-to-noise ratio (PSNR), and structural similarity (SSIM).

关键词： Image inpainting Multi-filters Low-rank tensor coding Higher-order singular value decomposition Gradient descent Weighted aggregation

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tensor-TRAIN MODELING FOR MIMO-OFDM tensor coding-AND-FORWARDING RELAY SYSTEMS 27

TENSOR-TRAIN MODELING FOR MIMO-OFDM TENSOR CODING-AND-FORWAR...

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27th European Signal Processing Conference (EUSIPCO)

作者： Zniyed, Yassine Boyer, Remy de Almeida, Andre L. F. Favier, Gerard Univ Paris Sud CNRS L2S Cent Supelec Gif Sur Yvette France Univ Lille CRIStAL Villeneuve Dascq France Univ Cote Azur Lab I3S CNRS Sophia Antiplois France

ISBN: (纸本)9789082797039

In tins paper, we consider a new one-way two-hop amplify-and-forward (AF) relaying scheme with a tensor space-time coding under frequency-selective fading channels. The signals received at the destination of the multi-input multi-output (MIMO) system define a 6-order tensor which satisfies a tensor-train decomposition (TTD). We propose a new TTD based receiver for a joint channel and symbol estimation. The proposed receiver avoids the use of long training sequences and resort to very few pilots to provide unique estimates of the individual channel matrices and the symbol matrix. Numerical simulations show the performance of the new proposed TTD-based semi-blind receiver.

关键词： Channel estimation MIMO relay systems tensor coding tensor-train decomposition semi-blind receiver

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Multi-filters Guided Low-rank tensor coding for Image Inpainting 2

Multi-filters Guided Low-rank Tensor Coding for Image Inpain...

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2nd International Conference on Image, Vision and Computing (ICIVC)

作者： Li, Sanqian Liu, Qiegen Nanchang Univ Dept Elect Informat Engn Nanchang 330031 Jiangxi Peoples R China

ISBN: (纸本)9781509062386

Image inpainting is a classical inverse ill-posed problem. In this paper, we introduce a multi-filters guided low-rank tensor coding as a priori information to tackle it. The key innovation is to formulate multiple feature-domain tensors by convoluting the target image with multi-filters. Furthermore, by exploring a low-rank tensor coding, it can reduce the redundancy between sparse feature vectors at neighboring locations and improve the efficiency of the overall representation. The resulting non-convex model is iteratively tackled by gradient descent and low-rank pursuit procedure. The experimental results demonstrate that the proposed algorithm can faithfully recover image and outperform the current state-of-the-art approach.

关键词： image inpainting multi-filters low-rank tensor coding HOSVD decomposition gradient descent procedure

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Nested Tucker tensor decomposition with application to MIMO relay systems using tensor space-time coding (TSTC)

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SIGNAL PROCESSING 2016年 128卷 318-331页

作者： Favier, Gerard Fernandes, C. Alexandre R. de Almeida, Andre L. F. Univ Nice Sophia Antipolis Lab I3S CNRS Sophia Antipolis France Univ Fed Ceara Campus Sobral Fortaleza Ceara Brazil Univ Fed Ceara Dept Teleinformat Engn Fortaleza Ceara Brazil

The aim of this paper is twofold. In a first part, we present a new tensor decomposition that we call Tucker train decomposition or nested Tucker decomposition (NTD). NTD can be viewed as a particular case of tensor-train decomposition recently proposed for representing and approximating high-dimensional tensors in a compact way. NTD of a fourth-order tensor is more specially analysed in terms of parameter estimation and uniqueness issue. In a second part, We show that the use of a tensor space-time coding (TSTC) structure at both the source node and the relay node of a one-way two-hop multi input multi-output (MIMO) relay communication system leads to a nested Tucker decomposition of the fourth-order tensor formed by the signals received at the destination. Two semi-blind receivers are then proposed for jointly estimating the transmitted information symbols and the two individual relay channels. The first one is iterative, based on a three-step alternating least squares (ALS) algorithm, whereas the second one;denoted 2LSKP, is a closed-form solution based on the LS estimations of two Kronecker products. Two supervised receivers are also derived by using a (short) pilot-assisted closed form solution for calculating channel estimates. These estimates are exploited either for initializing the ALS receiver or for designing a zero-forcing (ZF) receiver. Extensive Monte Carlo simulation results are provided to demonstrate the performance of the proposed relay system. (C) 2016 Elsevier B.V. All rights reserved.

关键词： Channel estimation Nested Tucker model MIMO systems Relay systems Semi-blind receivers Space-time coding Symbol estimation tensor decompositions tensor coding

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tensor modelling of MIMO communication systems with performance analysis and Kronecker receivers

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SIGNAL PROCESSING 2018年 145卷 304-316页

作者： da Costa, Michele Nazareth Favier, Gerard Romano, Joao Marcos T. Univ Estadual Campinas DSPCom Lab Campinas SP Brazil Univ Nice Sophia Antipolis CNRS Lab I3S Sophia Antipolis France

The purpose of this paper is manifold. In a first part, we present a new alternating least squares (ALS)-based method for estimating the matrix factors of a Kronecker product, the so-called Kronecker ALS. (KALS) method. Four other methods are also briefly described. In a second part, we consider the design of multiple-input multiple-output (MIMO) wireless communication systems using tensor modelling. Eight systems are presented in a unified way, and their theoretical performance is compared in terms of maximal diversity gain. Exploiting a Kronecker product of symbol and channel matrices, and applying the algorithms introduced in the first part, we propose three semi-blind and two supervised receivers, called Kronecker receivers, for jointly estimating the channel and the transmitted symbols. Necessary identifiability conditions are established. Finally, extensive Monte Carlo simulation results are provided to compare the performance of three tensor-based systems, on the one hand, and of the five proposed Kronecker receivers for the tensor space-time-frequency (TSTF) coding system, on the other hand. (C) 2017 Elsevier B.V. All rights reserved.

关键词： Channel estimation Kronecker product MIMO Systems Semi-blind receivers tensor coding tensor modelling

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