Tensor algebra and multidimensional harmonic retrieval in signal processing for MIMO radar
IEEE Transactions on Signal Processing
LVA/ICA'10 Proceedings of the 9th international conference on Latent variable analysis and signal separation
Tensor space-time (TST) coding for MIMO wireless communication systems
Signal Processing
Block component analysis, a new concept for blind source separation
LVA/ICA'12 Proceedings of the 10th international conference on Latent Variable Analysis and Signal Separation
A combination of parallel factor and independent component analysis
Signal Processing
SIAM Journal on Matrix Analysis and Applications
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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.