Direct blind channel equalization via the programmable canonical correlation analysis
| Autor: | Shiann-Jeng Yu |
|---|---|
| Rok vydání: | 2001 |
| Předmět: |
Engineering
Signal processing business.industry Noise (signal processing) Adaptive filter Control and Systems Engineering Signal Processing Electronic engineering Weight Computer Vision and Pattern Recognition Electrical and Electronic Engineering Canonical correlation business Algorithm Software Eigendecomposition of a matrix Eigenvalues and eigenvectors Communication channel |
| Zdroj: | Signal Processing. 81:1715-1724 |
| ISSN: | 0165-1684 |
| Popis: | This paper concerns direct blind channel equalization using the programmable canonical correlation analysis (PCCA). The PCCA-based equalizer calculates the weight vector for spatial filter based on signal cyclostationarity. The design problem of the PCCA is to solve an eigenproblem and find the first dominant eigenvector as the weight vector. In this paper, we investigate the maximum eigenvalue and express it as a function of two output signal-to-interference plus noise ratios. We also study the effect of small channel coefficients on the maximum eigenvalue and present a detection method for the PCCA to guarantee the equalization performance better than a specified performance requirement. Finally, several simulation examples are provided to show the effectiveness of the proposed approach. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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