Страница публикации

Non-convex Optimization in Digital Pre-distortion of the Signal

Тип публикации: Статья в журнале

Тип материала: Текст

Авторы: Maslovskiy A., Pasechnyuk D., Gasnikov A., Anikin A., Rogozin A., Gornov A., Antonov L., Vlasov R., Nikolaeva A., Begicheva M.

Журнал: Communications in Computer and Information Science: 20th Intern. Conf. on Mathematical Optimization Theory and Operations Research (MOTOR 2021 Virtual, Online, 5 - 10 July 2021)

Язык публикации: english

Серия книг: Communications in Computer and Information Science

Том: 1476

Номера страниц: 54 - 70

Количество страниц: 17

Год публикации: 2021

Отчетный год: 2021

DOI: 10.1007/978-3-030-86433-0_4

Аннотация: This paper reviews application of modern optimization methods for functionals describing Digital Pre-distortion (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.

Индексируется WOS: Нет

Индексируется Scopus: Нет

Индексируется УБС: Нет

Индексируется РИНЦ: Нет

Индексируется ВАК: Нет

Индексируется CORE: Нет