A Block Component Model-Based Blind DS-CDMA Receiver

In this paper, we consider the problem of blind multiuser separation-equalization in the uplink of a wideband DS-CDMA system, in a multipath propagation environment with intersymbol-interference (ISI). To solve this problem, we propose a multilinear algebraic receiver that relies on a new third-order tensor decomposition and generalizes the parallel factor (PARAFAC) model. Our method is deterministic and exploits the temporal, spatial and spectral diversities to collect the received data in a third-order tensor. The specific algebraic structure of this tensor is then used to decompose it in a sum of user's contributions. The so-called block component model (BCM) receiver does not require knowledge of the spreading codes, the propagation parameters, nor statistical independence of the sources but relies instead on a fundamental uniqueness condition of the decomposition that guarantees identifiability of every user's contribution. The development of fast and reliable techniques to calculate this decomposition is important. We propose a blind receiver based either on an alternating least squares (ALS) algorithm or on a Levenberg-Marquardt (LM) algorithm. Simulations illustrate the performance of the algorithms.

[1]  Richard A. Harshman,et al.  Foundations of the PARAFAC procedure: Models and conditions for an "explanatory" multi-model factor analysis , 1970 .

[2]  Lieven De Lathauwer,et al.  Decompositions of a Higher-Order Tensor in Block Terms - Part II: Definitions and Uniqueness , 2008, SIAM J. Matrix Anal. Appl..

[3]  David E. Booth,et al.  Multi-Way Analysis: Applications in the Chemical Sciences , 2005, Technometrics.

[4]  P. Paatero,et al.  THREE-WAY (PARAFAC) FACTOR ANALYSIS : EXAMINATION AND COMPARISON OF ALTERNATIVE COMPUTATIONAL METHODS AS APPLIED TO ILL-CONDITIONED DATA , 1998 .

[5]  Rasmus Bro,et al.  Multi-way Analysis with Applications in the Chemical Sciences , 2004 .

[6]  Kaj Madsen,et al.  Methods for Non-Linear Least Squares Problems (2nd ed.) , 2004 .

[7]  Lieven De Lathauwer,et al.  A Link between the Canonical Decomposition in Multilinear Algebra and Simultaneous Matrix Diagonalization , 2006, SIAM J. Matrix Anal. Appl..

[8]  Kaj Madsen,et al.  Methods for Non-Linear Least Squares Problems , 1999 .

[9]  R. O. Schmidt,et al.  Multiple emitter location and signal Parameter estimation , 1986 .

[10]  Michail K. Tsatsanis,et al.  Blind adaptive algorithms for minimum variance CDMA receivers , 2001, IEEE Trans. Commun..

[11]  Joos Vandewalle,et al.  A Multilinear Singular Value Decomposition , 2000, SIAM J. Matrix Anal. Appl..

[12]  Lieven De Lathauwer,et al.  Tensor-based techniques for the blind separation of DS-CDMA signals , 2007, Signal Process..

[13]  Eric Moulines,et al.  Subspace methods for the blind identification of multichannel FIR filters , 1995, IEEE Trans. Signal Process..

[14]  Georgios B. Giannakis,et al.  Cyclostationary Signal Analysis , 2009 .

[15]  Salah Bourennane,et al.  Multiway Filtering Applied on Hyperspectral Images , 2006, ACIVS.

[16]  Lieven De Lathauwer,et al.  Decompositions of a Higher-Order Tensor in Block Terms - Part I: Lemmas for Partitioned Matrices , 2008, SIAM J. Matrix Anal. Appl..

[17]  W. Rayens,et al.  Two-factor degeneracies and a stabilization of PARAFAC , 1997 .

[18]  D. Marquardt An Algorithm for Least-Squares Estimation of Nonlinear Parameters , 1963 .

[19]  J. Kruskal Three-way arrays: rank and uniqueness of trilinear decompositions, with application to arithmetic complexity and statistics , 1977 .

[20]  Arogyaswami Paulraj,et al.  An analytical constant modulus algorithm , 1996, IEEE Trans. Signal Process..

[21]  J. Chang,et al.  Analysis of individual differences in multidimensional scaling via an n-way generalization of “Eckart-Young” decomposition , 1970 .

[22]  F. L. Hitchcock The Expression of a Tensor or a Polyadic as a Sum of Products , 1927 .

[23]  Upamanyu Madhow,et al.  Blind adaptive multiuser detection , 1995, IEEE Trans. Inf. Theory.

[24]  A. Stegeman,et al.  On Kruskal's uniqueness condition for the Candecomp/Parafac decomposition , 2007 .

[25]  Rasmus Bro,et al.  A comparison of algorithms for fitting the PARAFAC model , 2006, Comput. Stat. Data Anal..

[26]  S. Talwar,et al.  Blind estimation of multiple digital signals transmitted over FIR channels , 1995, IEEE Signal Processing Letters.

[27]  Thomas Kailath,et al.  ESPRIT-estimation of signal parameters via rotational invariance techniques , 1989, IEEE Trans. Acoust. Speech Signal Process..

[28]  J. Chisholm Approximation by Sequences of Padé Approximants in Regions of Meromorphy , 1966 .

[29]  Nikos D. Sidiropoulos,et al.  Cramer-Rao lower bounds for low-rank decomposition of multidimensional arrays , 2001, IEEE Trans. Signal Process..

[30]  Ananthram Swami,et al.  Bibliography on higher-order statistics , 1997, Signal Process..

[31]  Nikos D. Sidiropoulos,et al.  Blind PARAFAC receivers for DS-CDMA systems , 2000, IEEE Trans. Signal Process..

[32]  Lieven De Lathauwer,et al.  Blind Deconvolution of DS-CDMA Signals by Means of Decomposition in Rank-$(1,L,L)$ Terms , 2008, IEEE Transactions on Signal Processing.

[33]  R. Bro,et al.  A new efficient method for determining the number of components in PARAFAC models , 2003 .

[34]  F. L. Hitchcock Multiple Invariants and Generalized Rank of a P‐Way Matrix or Tensor , 1928 .

[35]  H. Kiers,et al.  Three-mode principal components analysis: choosing the numbers of components and sensitivity to local optima. , 2000, The British journal of mathematical and statistical psychology.

[36]  Inbar Fijalkow,et al.  A globally convergent approach for blind MIMO adaptive deconvolution , 2001, IEEE Trans. Signal Process..

[37]  A. V. D. Veen Algebraic methods for deterministic blind beamforming , 1998, Proc. IEEE.

[38]  M.K. Tsatsanis,et al.  Performance analysis of minimum variance CDMA receivers , 1998, IEEE Trans. Signal Process..

[39]  Arogyaswami Paulraj,et al.  A subspace approach to blind space-time signal processing for wireless communication systems , 1997, IEEE Trans. Signal Process..

[40]  L. Tucker,et al.  Some mathematical notes on three-mode factor analysis , 1966, Psychometrika.

[41]  S. Leurgans,et al.  A Decomposition for Three-Way Arrays , 1993, SIAM J. Matrix Anal. Appl..

[42]  D. Godard,et al.  Self-Recovering Equalization and Carrier Tracking in Two-Dimensional Data Communication Systems , 1980, IEEE Trans. Commun..

[43]  Murat Torlak,et al.  Blind adaptive CDMA processing for smart antennas using the block shanno constant modulus algorithm , 2006, IEEE Transactions on Signal Processing.

[44]  Pierre Comon,et al.  Independent component analysis, A new concept? , 1994, Signal Process..

[45]  K. Kwak,et al.  A modified constrained constant modulus approach to blind adaptive multiuser detection , 2001, IEEE Trans. Commun..

[46]  N.D. Sidiropoulos,et al.  Blind multiuser detection in W-CDMA systems with large delay spread , 2001, IEEE Signal Processing Letters.

[47]  H. Kiers,et al.  Selecting among three-mode principal component models of different types and complexities: a numerical convex hull based method. , 2006, The British journal of mathematical and statistical psychology.

[48]  Nikos D. Sidiropoulos,et al.  Parallel factor analysis in sensor array processing , 2000, IEEE Trans. Signal Process..

[49]  Lieven De Lathauwer,et al.  Decompositions of a Higher-Order Tensor in Block Terms - Part III: Alternating Least Squares Algorithms , 2008, SIAM J. Matrix Anal. Appl..

[50]  Zhengyuan Xu,et al.  Code-constrained blind detection of CDMA signals in multipath channels , 2002, IEEE Signal Processing Letters.

[51]  P. Kroonenberg Applied Multiway Data Analysis , 2008 .

[52]  Lieven De Lathauwer,et al.  A Block Factor Analysis Based Receiver for Blind Multi-User Access in Wireless Communications , 2006, 2006 IEEE International Conference on Acoustics Speech and Signal Processing Proceedings.

[53]  L. Lathauwer,et al.  Signal Processing based on Multilinear Algebra , 1997 .

[54]  André Lima Férrer de Almeida,et al.  PARAFAC-based unified tensor modeling for wireless communication systems with application to blind multiuser equalization , 2007, Signal Process..

[55]  Rodrigo C. de Lamare,et al.  Blind adaptive code-constrained constant modulus algorithms for CDMA interference suppression in multipath channels , 2005, IEEE Commun. Lett..