File(s) under permanent embargo
Novel Z-Domain precoding method for blind separation of spatially correlated signals
journal contribution
posted on 2013-01-01, 00:00 authored by Yong XiangYong Xiang, D Peng, Yang Xiang, S GuoIn this paper, we address the problem of blind separation of spatially correlated signals, which is encountered in some emerging applications, e.g., distributed wireless sensor networks and wireless surveillance systems. We preprocess the source signals in transmitters prior to transmission. Specifically, the source signals are first filtered by a set of properly designed precoders and then the coded signals are transmitted. On the receiving side, the Z-domain features of the precoders are exploited to separate the coded signals, from which the source signals are recovered. Based on the proposed precoders, a closed-form algorithm is derived to estimate the coded signals and the source signals. Unlike traditional blind source separation approaches, the proposed method does not require the source signals to be uncorrelated, sparse, or nonnegative. Compared with the existing precoder-based approach, the new method uses precoders with much lower order, which reduces the delay in data transmission and is easier to implement in practice.
History
Journal
IEEE transactions on neural networks and learning systemsVolume
24Issue
1Pagination
94 - 105Publisher
IEEELocation
Piscataway, N.J.Publisher DOI
ISSN
2162-237XeISSN
2162-2388Language
engPublication classification
C1 Refereed article in a scholarly journalCopyright notice
2013, IEEEUsage metrics
Read the peer-reviewed publication
Categories
Keywords
blind source separationcorrelated sourcessecond-order statisticsZ-domain precodingScience & TechnologyTechnologyComputer Science, Artificial IntelligenceComputer Science, Hardware & ArchitectureComputer Science, Theory & MethodsEngineering, Electrical & ElectronicComputer ScienceEngineeringNONNEGATIVE MATRIX FACTORIZATIONFIR-MIMO-CHANNELSCOMPONENT ANALYSISSOURCE EXTRACTIONGRADIENTINTERNETDESIGNALGORITHMSMIXTURESAMPLIFY