Semi-blind methods for communications

Zarzoso, Vicente; Comon, Pierre; Slock, Dirk

doi:10.1016/b978-0-12-374726-6.00020-5

Cited by 6 publications

(3 citation statements)

References 75 publications

(115 reference statements)

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“…Grouping together the mixing vectors in the mixing matrix and the sources in the vector , the observations meet the familiar linear mixing model (3) In this work, we denote the identity matrix of dimension as , and we define the weighted inner product between matrices (or vectors) of compatible dimension as (4) where is a positive definite hermitian matrix and if if (5) denotes the number of real degrees of freedom of the scalar elements of . Accordingly, the weighted metric is defined as…”

Section: Signal Model and Notationmentioning

confidence: 99%

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Bounded Component Analysis of Noisy Underdetermined and Overdetermined Mixtures

Cruces

2015

IEEE Trans. Signal Process.

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Our paper addresses the problem of the bounded component analysis of the observations in noisy mixtures. We present an original set of assumptions that guarantee the identifiability of the mixture in underdetermined mixtures and the separability of the sources in overdetermined mixtures. These assumptions are especially well suited for the blind identification of communication channels. Our proof of the identifiability of the mixing system is non-constructive. Thus, we develop a novel blind identification criterion for underdetermined and overdetermined mixtures, which is based on the least square fit of the perimeter of a set of projections of the observations. For the optimization of this criterion we propose the BCA-PM algorithm, which implements the natural gradient descent, along with an acceleration of the convergence designed for the neighbourhood of the solution. In situations of isotropic Gaussian noise and for reasonable signal to noise ratio, BCA-PM compares favorably with respect to other state-of-the-art methods, such as the ICA simultaneous diagonalization algorithms for underdetermined and overdetermined mixtures. The simulations also corroborate the advantages of using bounded component analysis for the blind identification of the channel with small datasets or when the transmitters cannot be regarded as statistically independent.Index Terms-Blind source separation, bounded component analysis, identifiability conditions, independent component analysis, separation of dependent sources, underdetermined mixtures.

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Section: Signal Model and Notationmentioning

confidence: 99%

“…The geometric properties of the constellations of the transmitted symbols have been extensively used for the identification and equalization of the communications channel [5]. Among them the finite alphabet property (FA) refers to the finite cardinality and knowledge of the alphabet of transmitted symbols.…”

Section: Introductionmentioning

confidence: 99%

Bounded Component Analysis of Noisy Underdetermined and Overdetermined Mixtures

Cruces

2015

IEEE Trans. Signal Process.

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“…Channel estimation is a key part when design any receivers, the number of channel in MIMO-OFDM systems will be increased with the growing of antennas and users' number rapidly, so the channel estimation of MIMO-OFDM systems is a very complex question. Semi-blind estimation method usually uses a little pilot and iterative method to reduce the complexity of blind estimation, and to a certain extent, it can improve the channel estimation in real time [4][5][6][7]. In nonlinear MIMO-OFDM systems, it is necessary for the intelligent signal processing method applied to deal with the problem of channel estimation [8][9][10][11][12].…”

Section: Introductionmentioning

confidence: 99%

Semi-blind channel estimation of MIMO-OFDM systems based on RBF network

Hao

Ling

2011

IET International Communication Conference on Wireless Mobile and Computing (CCWMC 2011)

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A Semi-blind channel estimation method of MIMO-OFDM systems based on RBF (Radial Basis Function) network is proposed in this paper, with the improved semi-blind cost function based on LS criterion, and using RBF network to substitute the function iteration. Then makes use of the improved PSO algorithm to optimize the parameter of RBF network, we also use the improved network to estimate the channel response. Finally, the simulation results show the advantages of RBF network when processing the problem of channel estimation.

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Simulation of Processes in the Problem of Blind Signal Identification

Kucherov

Khalimon

2023

Lecture Notes in Networks and Systems

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Semi-blind methods for communications

Cited by 6 publications

References 75 publications

Bounded Component Analysis of Noisy Underdetermined and Overdetermined Mixtures

Bounded Component Analysis of Noisy Underdetermined and Overdetermined Mixtures

Semi-blind channel estimation of MIMO-OFDM systems based on RBF network

Simulation of Processes in the Problem of Blind Signal Identification

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