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.
Document type :
Journal articles
Liste complète des métadonnées

https://hal.archives-ouvertes.fr/hal-01246047
Contributor : Gérard Favier <>
Submitted on : Friday, December 18, 2015 - 12:51:58 AM
Last modification on : Monday, November 5, 2018 - 3:52:01 PM

Identifiers

Collections

Citation

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〉

Share

Metrics

Record views

128