DocumentCode :
67028
Title :
On Recursive Blind Equalization in Sensor Networks
Author :
Chengpu Yu ; Lihua Xie
Author_Institution :
Sch. of Electr. & Electron. Eng., Nangyang Technol. Univ., Singapore, Singapore
Volume :
63
Issue :
3
fYear :
2015
fDate :
Feb.1, 2015
Firstpage :
662
Lastpage :
672
Abstract :
In this paper, we study the distributed blind equalization of networked single-input multi-output (SIMO) systems. An indirect distributed equalization framework is presented, which estimates the transfer functions followed by the associated equalizers. Two distributed indirect equalization algorithms are proposed: one depends on multiple average consensus operations, and the other relies on the combination of innovation and one average consensus operation. The former generates an approximate equalizer for which the associated estimation error is determined by the number of average consensus operations, while the latter can provide an accurate equalizer estimation under some mild conditions. The proposed algorithms estimate the desired equalizer recursively and recover the source signal in real time. Furthermore, the distributed equalization under a time-varying topology is investigated as well. Convergence properties of the proposed algorithms are established and numerical simulations are carried out to show the performances of the proposed algorithms.
Keywords :
blind equalisers; convergence of numerical methods; recursive estimation; telecommunication network topology; transfer functions; wireless sensor networks; SIMO system; approximate equalizer; distributed indirect equalization algorithm; distributed recursive blind equalization; multiple average consensus operation; single input multioutput system; source signal recovery; time-varying topology; transfer function estimation; wireless sensor network; Blind equalizers; Delays; Equations; Estimation; Signal processing algorithms; Topology; Blind channel equalization; consensus based gradient method; mutually referenced equalizers;
fLanguage :
English
Journal_Title :
Signal Processing, IEEE Transactions on
Publisher :
ieee
ISSN :
1053-587X
Type :
jour
DOI :
10.1109/TSP.2014.2376884
Filename :
6971232
Link To Document :
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