Name
Title | ||
|---|---|---|
Blind joint identification and equalization of Wiener-Hammerstein communication channels using PARATUCK-2 tensor decomposition |
Abstract | ||
|---|---|---|
In this paper, we consider the blind joint identification and equalization of Wiener-Hammerstein nonlinear communication channels. By considering a special design of the input signal, we show that output data can be organized into a third-order tensor. We show that the obtained tensor has a PARATUCK-2 representation. We derive new results on uniqueness of the PARATUCK-2 model by considering structural constraints such as Toeplitz and Vander-monde forms for some of its matrix factors. We also constrain the input signal to belong to a finite alphabet. Then an Alternating Least Squares (ALS) algorithm is proposed for estimating the factors of the PARATUCK-2 model and therefore the parameters of the Wiener-Hammerstein channel and the unknown input signal. The performances of the proposed joint identification and equalization method are illustrated by means of simulation results. |
Year | Venue | Keywords |
|---|---|---|
2007 | EUSIPCO | blind source separation,channel coding,channel estimation,tensors,paratuck-2 tensor decomposition,wiener-hammerstein nonlinear communication channels,alternating least squares algorithm,blind joint identification and equalization,finite alphabet,third-order tensor,tensile stress,matrix decomposition,polynomials,estimation,signal processing |
Field | DocType | ISBN |
Signal processing,Mathematical optimization,Tensor,Equalization (audio),Polynomial,Matrix (mathematics),Matrix decomposition,Algorithm,Toeplitz matrix,Blind equalization,Mathematics | Conference | 978-839-2134-04-6 |
Citations | PageRank | References |
9 | 0.64 | 4 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Alain Y. Kibangou | 1 | 95 | 12.01 |
| GéRard Favier | 2 | 514 | 46.41 |