id: 05830259
dt: j
an: 05830259
au: Fernandes, Carlos A.R.; Favier, Gérard; Mota, João C.M.
ti: PARAFAC-based channel estimation and data recovery in nonlinear MIMO spread
    spectrum communication systems.
so: Signal Process. 91, No. 2, 311-322 (2011).
py: 2011
pu: Elsevier Science, Amsterdam
la: EN
cc: 
ut: PARAFAC decomposition; channel estimation; data recovery; MIMO Volterra;
    nonlinear channel; direct sequence spread spectrum; radio over fiber
ci: 
li: doi:10.1016/j.sigpro.2010.07.010
ab: Summary: 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.
rv: