PARAFAC-based channel estimation and data recovery in nonlinear MIMO spread spectrum communication systems

In this paper, a new tensorial modeling is first proposed for nonlinear multiple-input multiple-output (MIMO) direct sequence spread spectrum communication systems. The channel is modeled as an instantaneous MIMO Volterra system. Then, a direct data approach for joint blind channel estimation and da...

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Bibliographic Details
Published in:Signal processing 2011-02, Vol.91 (2), p.311-322
Main Authors: Fernandes, Carlos A.R., Favier, Gérard, Mota, João C.M.
Format: Article
Language:English
Subjects:
Applied sciences
Blinds
Channel estimation
Channels
Coding, codes
Communication systems
Computer Science
Data recovery
Detection, estimation, filtering, equalization, prediction
Direct sequence spread spectrum
Exact sciences and technology
Information theory
Information, signal and communications theory
Mathematical analysis
MIMO Volterra
Modulation, demodulation
Nonlinear channel
Nonlinearity
PARAFAC decomposition
Radio over fiber
Signal and communications theory
Signal and Image Processing
Signal, noise
Spreads
Telecommunications and information theory
Tensors
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Summary:In this paper, a new tensorial modeling is first proposed for nonlinear multiple-input multiple-output (MIMO) direct sequence spread spectrum communication systems. The channel is modeled as an instantaneous MIMO Volterra system. Then, a direct data approach for joint blind channel estimation and data recovery is developed using the parallel factor (PARAFAC) decomposition of a third-order tensor composed of received signals, exploiting space, time and code diversities. A blind channel estimation method based on the PARAFAC decomposition of a fifth-order tensor composed of covariances of the received signals is also proposed, considering phase shift keying (PSK) modulated transmitted signals. The proposed estimation algorithms are evaluated by simulating a nonlinear uplink MIMO radio over fiber (ROF) communication system.
ISSN:0165-1684
1872-7557
DOI:10.1016/j.sigpro.2010.07.010