title: Ð Ð°Ð·ÑÐ°Ð±Ð¾ÑÐºÐ° Ð°Ð»Ð³Ð¾ÑÐ¸ÑÐ¼Ð° ÑÑÑÑÐ°Ð½ÐµÐ½Ð¸Ñ Ð¸Ð½ÑÐµÑÑÐµÑÐµÐ½ÑÐ¸Ð¸ Ð² FTN-ÑÐ¸Ð³Ð½Ð°Ð»Ð°Ñ Ð½Ð° Ð¾ÑÐ½Ð¾Ð²Ðµ Ð¼ÐµÑÐ¾Ð´Ð¾Ð² Ð¼Ð°ÑÐ¸Ð½Ð½Ð¾Ð³Ð¾ Ð¾Ð±ÑÑÐµÐ½Ð¸Ñ
title: Ð²ÑÐ¿ÑÑÐºÐ½Ð°Ñ ÐºÐ²Ð°Ð»Ð¸ÑÐ¸ÐºÐ°ÑÐ¸Ð¾Ð½Ð½Ð°Ñ ÑÐ°Ð±Ð¾ÑÐ° Ð¼Ð°Ð³Ð¸ÑÑÑÐ°
titleType: Subtitle
title: Development a machine learning based interference cancellation algorithm for Faster-than-Nyquist signals
Creators: name: ÐÐ½ÑÐ·ÐµÐ², ÐÐ²Ð°Ð½
Publisher: name: Ð¡Ð°Ð½ÐºÑ-ÐÐµÑÐµÑÐ±ÑÑÐ³ÑÐºÐ¸Ð¹ Ð¿Ð¾Ð»Ð¸ÑÐµÑÐ½Ð¸ÑÐµÑÐºÐ¸Ð¹ ÑÐ½Ð¸Ð²ÐµÑÑÐ¸ÑÐµÑ ÐÐµÑÑÐ° ÐÐµÐ»Ð¸ÐºÐ¾Ð³Ð¾
Year: 2024
Subjects: Ð½ÐµÐ¹ÑÐ¾Ð½Ð½ÑÐµ ÑÐµÑÐ¸
Ð´ÐµÐ¼Ð¾Ð´ÑÐ»ÑÑÐ¸Ñ
Ð¼ÐµÐ¶ÑÐ¸Ð¼Ð²Ð¾Ð»ÑÐ½Ð°Ñ
Ð¸Ð½ÑÐµÑÑÐµÑÐµÐ½ÑÐ¸Ñ
Ð¼Ð°ÑÐ¸Ð½Ð½Ð¾Ðµ Ð¾Ð±ÑÑÐµÐ½Ð¸Ðµ
faster-than-nyquist
Ð°Ð²ÑÐ¾ÑÐ½ÐºÐ¾Ð´ÐµÑ
ÑÑÐ°Ð½ÑÑÐ¾ÑÐ¼ÐµÑ
neural networks
demodulation
intersymbol interference
machine learning
autoencoder
transformer

description: Ð Ð´Ð°Ð½Ð½Ð¾Ð¹ ÑÐ°Ð±Ð¾ÑÐµ Ð¸ÑÑÐ»ÐµÐ´ÑÑÑÑÑ Ð°Ð»Ð³Ð¾ÑÐ¸ÑÐ¼Ñ ÑÑÑÑÐ°Ð½ÐµÐ½Ð¸Ñ Ð¼ÐµÐ¶ÑÐ¸Ð¼Ð²Ð¾Ð»ÑÐ½Ð¾Ð¹ Ð¸Ð½ÑÐµÑÑÐµÑÐµÐ½ÑÐ¸Ð¸ Ð² ÑÐ¸Ð³Ð½Ð°Ð»Ð°Ñ Faster-than-Nyquist Ð½Ð° Ð¾ÑÐ½Ð¾Ð²Ðµ Ð¼Ð°ÑÐ¸Ð½Ð½Ð¾Ð³Ð¾ Ð¾Ð±ÑÑÐµÐ½Ð¸Ñ. Ð ÑÐ¾Ð´Ðµ ÑÐ°Ð±Ð¾ÑÑ Ð±ÑÐ»Ð¸ Ð¸ÑÑÐ»ÐµÐ´Ð¾Ð²Ð°Ð½Ñ ÑÑÑÐµÑÑÐ²ÑÑÑÐ¸Ðµ Ð¿Ð¾Ð´ÑÐ¾Ð´Ñ ÑÑÑÑÐ°Ð½ÐµÐ½Ð¸Ñ Ð¼ÐµÐ¶ÑÐ¸Ð¼Ð²Ð¾Ð»ÑÐ½Ð¾Ð¹ Ð¸Ð½ÑÐµÑÑÐµÑÐµÐ½ÑÐ¸Ð¸. ÐÑÐ»Ð¸ ÑÐ°Ð·ÑÐ°Ð±Ð¾ÑÐ°Ð½Ñ Ð´Ð²Ðµ Ð½ÐµÐ¹ÑÐ¾Ð½Ð½ÑÐµ ÑÐµÑÐ¸ Ñ ÑÐ°Ð·Ð»Ð¸ÑÐ½ÑÐ¼Ð¸ Ð°ÑÑÐ¸ÑÐµÐºÑÑÑÐ°Ð¼Ð¸: Ð¾Ð´Ð½Ð° Ð½Ð° Ð¾ÑÐ½Ð¾Ð²Ðµ ÑÐ²ÑÑÑÐ¾ÑÐ½Ð¾Ð³Ð¾ Ð°Ð²ÑÐ¾ÑÐ½ÐºÐ¾Ð´ÐµÑÐ°, Ð²ÑÐ¾ÑÐ°Ñ â Ð½Ð° Ð°ÑÑÐ¸ÑÐµÐºÑÑÑÐµ ÑÑÐ°Ð½ÑÑÐ¾ÑÐ¼ÐµÑÐ°. Ð Ð°Ð·ÑÐ°Ð±Ð¾ÑÐ°Ð½Ð½ÑÐµ Ð¼Ð¾Ð´ÐµÐ»Ð¸ Ð±ÑÐ»Ð¸ Ð¾Ð±ÑÑÐµÐ½Ñ Ð½Ð° ÑÐ°Ð·Ð»Ð¸ÑÐ½ÑÑ Ð½Ð°Ð±Ð¾ÑÐ°Ñ ÑÐ¸Ð³Ð½Ð°Ð»Ð¾Ð² Ñ Ð¾Ð¿ÑÐ¸Ð¼Ð¸Ð·Ð°ÑÐ¸ÐµÐ¹ Adam Ð¼ÐµÑÐ¾Ð´Ð¾Ð¼ Ð¾Ð±ÑÐ°ÑÐ½Ð¾Ð³Ð¾ ÑÐ°ÑÐ¿ÑÐ¾ÑÑÑÐ°Ð½ÐµÐ½Ð¸Ñ Ð¾ÑÐ¸Ð±ÐºÐ¸. ÐÑÐ»Ð¾ Ð¿ÑÐ¾Ð²ÐµÐ´ÐµÐ½Ð¾ Ð¸Ð¼Ð¸ÑÐ°ÑÐ¸Ð¾Ð½Ð½Ð¾Ðµ Ð¼Ð¾Ð´ÐµÐ»Ð¸ÑÐ¾Ð²Ð°Ð½Ð¸Ðµ Ð´Ð»Ñ Ð¾ÑÐµÐ½ÐºÐ¸ Ð¿Ð¾Ð¼ÐµÑÐ¾ÑÑÑÐ¾Ð¹ÑÐ¸Ð²Ð¾ÑÑÐ¸ Ð¿ÑÐ¸ÑÐ¼Ð° Ð¿ÑÐ¸ Ð¸ÑÐ¿Ð¾Ð»ÑÐ·Ð¾Ð²Ð°Ð½Ð¸Ð¸ Ð½ÐµÐ¹ÑÐ¾Ð½Ð½ÑÑ ÑÐµÑÐµÐ¹. ÐÐ¼Ð¸ÑÐ°ÑÐ¸Ð¾Ð½Ð½Ð¾Ðµ Ð¼Ð¾Ð´ÐµÐ»Ð¸ÑÐ¾Ð²Ð°Ð½Ð¸Ðµ Ð¿ÑÐ¾Ð²Ð¾Ð´Ð¸Ð»Ð¾ÑÑ Ð´Ð»Ñ Ð¼Ð¾Ð´ÑÐ»ÑÑÐ¸Ð¸ 4-PSK Ð¸ Ð¸Ð¼Ð¿ÑÐ»ÑÑÐ¾Ð² Ð²Ð¸Ð´Ð° ÐºÐ¾ÑÐµÐ½Ñ ÐºÐ²Ð°Ð´ÑÐ°ÑÐ½ÑÐ¹ Ð¸Ð· Ð¿ÑÐ¸Ð¿Ð¾Ð´Ð½ÑÑÐ¾Ð³Ð¾ ÐºÐ¾ÑÐ¸Ð½ÑÑÐ° Ñ ÑÐ°Ð·Ð»Ð¸ÑÐ½ÑÐ¼Ð¸ ÐºÐ¾ÑÑÑÐ¸ÑÐ¸ÐµÐ½ÑÐ°Ð¼Ð¸ ÑÐºÑÑÐ³Ð»ÐµÐ½Ð¸Ñ. Ð£ÑÑÐµÐ½Ñ ÑÐµÑÐ¼Ð¸Ð½Ð¾Ð»Ð¾Ð³Ð¸ÑÐµÑÐºÐ¸Ðµ Ð¾ÑÐ¾Ð±ÐµÐ½Ð½Ð¾ÑÑÐ¸ Ð¿ÑÐµÐ´Ð¼ÐµÑÐ½Ð¾Ð¹ Ð¾Ð±Ð»Ð°ÑÑÐ¸ Ð¸ Ð¿ÑÐ¸Ð¼ÐµÐ½ÐµÐ½Ñ Ð¿ÑÐ¾Ð³ÑÐ°Ð¼Ð¼Ð½ÑÐµ ÑÑÐµÐ´ÑÑÐ²Ð° Ð´Ð»Ñ ÑÐµÑÐµÐ½Ð¸Ñ Ð·Ð°Ð´Ð°Ñ. ÐÑÐ¸Ð¼ÐµÐ½ÐµÐ½Ð¾ ÑÐ¿ÐµÑÐ¸Ð°Ð»Ð¸Ð·Ð¸ÑÐ¾Ð²Ð°Ð½Ð½Ð¾Ðµ Ð¿ÑÐ¾Ð³ÑÐ°Ð¼Ð¼Ð½Ð¾-Ð¼Ð°ÑÐµÐ¼Ð°ÑÐ¸ÑÐµÑÐºÐ¾Ðµ Ð¾Ð±ÐµÑÐ¿ÐµÑÐµÐ½Ð¸Ðµ Matlab.
description: This work investigates machine learning-based algorithms for eliminating inter-symbol interference in Faster-than-Nyquist signals. During the work, existing approaches to eliminating intersymbol interference were investigated. Two neural networks with different architectures were developed. One is based on a convolutional autoencoder, the second is based on a transformer architecture. The developed models were trained on various sets of signals with Adam optimization using the backpropagation method. Simulation modeling was carried out to assess the noise immunity of reception when using neural networks. Simulations were carried out for 4-PSK modulation and square root raised cosine pulses with different roll-off factors. Terminological features of the subject area are taken into account and software tools are used to solve problems. Specialized software and mathematics were used (Matlab).