In this paper, we first introduce two new classes of constrained tensor models that call generalized PARATUCK- (N1, N) and Tucker- models. A space-time-frequency (TSTF) coding structure is then proposed for MIMO OFDM-CDMA wireless communication systems. Two semi-blind receivers relying on the PARATUCK model are derived solving problem joint channel symbol estimation. One iterative based a two-step alternating least squares (ALS) algorithm. The other one closed-form low-complexity solution...

In two-hop amplify-and-forward (AF) relay systems, a source node sends information to one or several nodes that amplify and retransmit the received signals destination node, without decoding. Such AF relaying-based cooperative communications allow improve communication reliability due increased channel gains space diversity at node. this paper, we consider scheme, with simplified Khatri-Rao space-time (KRST) coding transmission (source). We show third-order tensor of by satisfies PARAFAC...

In cooperative communication systems, multiple-input multiple-output (MIMO) amplify-and-forward (AF) relaying is a promising solution for upcoming wireless standards due to its intrinsic benefits in terms of extended coverage and increased spatial diversity. However, the deployment MIMO AF relays faces some key challenges such as need channel state information (CSI) partial channels associated with different links, which required by transmit optimization techniques. this paper, we consider...

In this letter, we first present explicit relations between block-oriented nonlinear representations and Volterra models. For an identification purpose, show that the estimation of diagonal coefficients kernels associated with considered structures is sufficient to recover overall model. An alternating least squares-type algorithm provided carry out model identification.

In this paper, we formulate a new tensor decomposition herein called constrained factor (CONFAC) decomposition. It consists in decomposing third-order into triple sum of rank-one factors, where interactions involving the components different factors are allowed. The interaction pattern is controlled by three constraint matrices columns which canonical vectors. Each matrix associated with given dimension, or mode, tensor. explicit use these provides degrees freedom to CONFAC for modeling...

SUMMARY Discrete‐time Volterra models are widely used in various application areas. Their usefulness is mainly because of their ability to approximate an arbitrary precision any fading memory nonlinear system and property linearity with respect parameters, the kernels coefficients. The main drawback these parametric complexity implying need estimate a huge number parameters. Considering order higher than two as symmetric tensors, we use parallel factor (PARAFAC) decomposition derive...

We first introduce a new class of tensor models for fourth-order tensors, referred to as "nested PARAFAC models." Then, we present space-time-frequency (STF) coding scheme multiple antenna orthogonal frequency division multiplexing systems. This scheme, called double Khatri-Rao STF (D-KRSTF) coding, combines time-domain spreading with space-frequency precoding and provides an extension space-time (KRST) . show that the received signals define satisfying two nested models, semi-blind receiver...

In this paper, we first propose a generalized fourth-order PARATUCK2 tensor model for multiple-input multiple-output (MIMO) communication systems with space-time-frequency (STF) spreading-multiplexing. The core of the proposed is composed two third-order interaction tensors that define joint time and frequency allocation data streams to transmit antennas, thus allowing adjust multiplexing degree spreading redundancy in three domains: space (transmit antennas), (blocks) (subcarriers). Then,...

In this letter, we consider a one-way two-hop AF relaying scheme employing two independent Khatri-Rao space-time (KRST) codings at the source and relay nodes. The signals received destination form fourth-order tensor whose dimensions correspond to four signal diversities, which satisfies nested PARAFAC model. Exploiting structure, derive matrix unfoldings expressed in terms of products are used propose closed-form semi-blind receiver allowing jointly estimate information symbols individual...

In this paper, we present an overview of constrained parallel factor (PARAFAC) models where the constraints model linear dependencies among columns matrices tensor decomposition or, alternatively, pattern interactions between different modes which are captured by equivalent core tensor. Some prerequisites with a particular emphasis on mode combination using Kronecker products canonical vectors that makes easier matricization operations, first introduced. This product‐based approach is also...

The canonical polyadic decomposition (CPD) of high-order tensors, also known as Candecomp/Parafac, is very useful for representing and analyzing multidimensional data. This paper considers a CPD model having structured matrix factors, e.g. Toeplitz, Hankel or circulant matrices, studies its associated estimation problem. arises in signal processing applications such Wiener-Hammerstein system identification cumulant-based wireless communication channel estimation. After introducing general...

In this paper, we consider an uplink multiple-antenna code-division multiple-access (CDMA) system linking several mobile users to one base station. For system, a constrained third-order tensor decomposition is introduced for modeling the transmitter as well received signal. The structure of proposed characterized by two constraint matrices that have meaningful physical interpretation in our context. They can be viewed canonical allocation define users' data streams and spreading codes...

In the context of big data, high-order tensor decompositions have to face a new challenge in terms storage and computational costs. The train (TT) decomposition provides very useful graph-based model reduction, whose cost grows linearly with order $D$. computation TT-core tensors TT-ranks can be done stable sequential (i.e., noniterative) way thanks popular TT-SVD algorithm. this paper, we exploit ideas developed for hierarchical/tree Tucker TT decomposition. Specifically, efficient...

This letter is concerned with the parameter estimation of linear and nonlinear subsystems parallel-cascade Wiener systems (PCWS). We first present relationship between a PCWS its associated Volterra model. show that coefficients can be obtained using joint diagonalization third-order kernel slices. Then, are estimated least square algorithm. The proposed method illustrated by means simulation results.