Abstract
Several different approaches to the design of blind channel equalization algorithms for digital communications have been described in the literature, including steepest-descent algorithms, algorithms based on the use of high-order statistics, and algorithms based on the maximum-likelihood criterion. In this paper, we focus on algorithms based on maximum likelihood optimization for jointly estimating the channel characteristics and the data sequence.
This work was supported in part by the National Science Foundation under grant MIP-9115526
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Proakis, J.G. (1995). Adaptive Algorithms for Blind Channel Equalization. In: Bojanczyk, A., Cybenko, G. (eds) Linear Algebra for Signal Processing. The IMA Volumes in Mathematics and its Applications, vol 69. Springer, New York, NY. https://doi.org/10.1007/978-1-4612-4228-4_8
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DOI: https://doi.org/10.1007/978-1-4612-4228-4_8
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