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

Abstract : 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.
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https://hal.archives-ouvertes.fr/hal-01246047
Contributor : Gérard Favier <>
Submitted on : Friday, December 18, 2015 - 12:51:58 AM
Last modification on : Tuesday, May 26, 2020 - 6:50:34 PM

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Carlos Alexandre Rolim Fernandes, Gérard Favier, João César Moura Mota. PARAFAC-based channel estimation and data recovery in nonlinear MIMO spread spectrum communication systems . Signal Processing, Elsevier, 2011, 91 (2), pp.311-322. ⟨10.1016/j.sigpro.2010.07.010⟩. ⟨hal-01246047⟩

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