Abstract
Channel prediction is an important technique for compensating fading channel in mobile communications. We proposed a channel prediction method based on complex-valued neural networks as a previous work. In this paper, we introduce a penalty function to the weight update in the complex-valued neural network to realize a learning dynamics that can self-optimize network structures according to fast changing communication environments. This presents an adaptive and highly accurate channel prediction method. We demonstrate the ability of the proposed method in a series of simulations.
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Ding, T., Hirose, A. (2014). Fading Channel Prediction Based on Self-optimizing Neural Networks. In: Loo, C.K., Yap, K.S., Wong, K.W., Teoh, A., Huang, K. (eds) Neural Information Processing. ICONIP 2014. Lecture Notes in Computer Science, vol 8834. Springer, Cham. https://doi.org/10.1007/978-3-319-12637-1_22
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DOI: https://doi.org/10.1007/978-3-319-12637-1_22
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-12636-4
Online ISBN: 978-3-319-12637-1
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