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Application of Attention Technique for Digital Pre-distortion

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Advances in Optimization and Applications (OPTIMA 2022)

Abstract

This paper reviews application of modern optimization methods for functionals describing digital predistortion (DPD) of signals with orthogonal frequency division multiplexing (OFDM) modulation. The considered family of model functionals is determined by the class of cascade Wiener–Hammerstein models, which can be represented as a computational graph consisting of various nonlinear blocks. To assess optimization methods with the best convergence depth and rate as a properties of this models family we multilaterally consider modern techniques used in optimizing neural networks and numerous numerical methods used to optimize non-convex multimodal functions.

The research emphasizes the most effective of the considered techniques and describes several useful observations about the model properties and optimization methods behavior.

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Correspondence to Aleksandr Maslovskiy .

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Maslovskiy, A., Kunitsyn, A., Gasnikov, A. (2022). Application of Attention Technique for Digital Pre-distortion. In: Olenev, N., Evtushenko, Y., Jaćimović, M., Khachay, M., Malkova, V., Pospelov, I. (eds) Advances in Optimization and Applications. OPTIMA 2022. Communications in Computer and Information Science, vol 1739. Springer, Cham. https://doi.org/10.1007/978-3-031-22990-9_12

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  • DOI: https://doi.org/10.1007/978-3-031-22990-9_12

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-22989-3

  • Online ISBN: 978-3-031-22990-9

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