title: Ð Ð°Ð·ÑÐ°Ð±Ð¾ÑÐºÐ° Ð°Ð»Ð³Ð¾ÑÐ¸ÑÐ¼Ð° Ð¾ÑÐµÐ½ÐºÐ¸ ÐºÐ¾ÑÑÑÐ¸ÑÐ¸ÐµÐ½ÑÐ° ÑÐ±Ð»Ð¸Ð¶ÐµÐ½Ð¸Ñ FTN-ÑÐ¸Ð³Ð½Ð°Ð»Ð¾Ð² 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 of an algorithm for estimating the packing ratio of FTN-signals based on machine learning methods
Creators: name: Ð¡ÑÑÐ°Ð½Ð¾Ð², ÐÑÑÐµÐ¼
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: FTN-ÑÐ¸Ð³Ð½Ð°Ð»Ñ
RRC-Ð¸Ð¼Ð¿ÑÐ»ÑÑ
ÐºÐ¾ÑÑÑÐ¸ÑÐ¸ÐµÐ½Ñ ÑÐ±Ð»Ð¸Ð¶ÐµÐ½Ð¸Ñ
ÐºÐ¾ÑÑÑÐ¸ÑÐ¸ÐµÐ½Ñ ÑÐºÑÑÐ³Ð»ÐµÐ½Ð¸Ñ
ÐºÐ»Ð°ÑÑÐ¸ÑÐ¸ÐºÐ°ÑÐ¸Ñ Ð¿Ð°ÑÐ°Ð¼ÐµÑÑÐ¾Ð²
Ð¼Ð°ÑÐ¸Ð½Ð½Ð¾Ðµ Ð¾Ð±ÑÑÐµÐ½Ð¸Ðµ
Ð½ÐµÐ¹ÑÐ¾Ð½Ð½ÑÐµ ÑÐµÑÐ¸
FTN-signals
RRC-pulse
packing ratio
roll-off factor
parameters classification
machine learning
neural networks

description: ÐÐ±ÑÐµÐºÑ Ð¸ÑÑÐ»ÐµÐ´Ð¾Ð²Ð°Ð½Ð¸Ñ â ÐºÐ¾ÑÑÑÐ¸ÑÐ¸ÐµÐ½Ñ ÑÐ±Ð»Ð¸Ð¶ÐµÐ½Ð¸Ñ FTN-ÑÐ¸Ð³Ð½Ð°Ð»Ð¾Ð². Ð¦ÐµÐ»Ñ ÑÐ°Ð±Ð¾ÑÑ â ÑÐ°Ð·ÑÐ°Ð±Ð¾ÑÐºÐ° Ð°Ð»Ð³Ð¾ÑÐ¸ÑÐ¼Ð° Ð¾ÑÐµÐ½ÐºÐ¸ ÐºÐ¾ÑÑÑÐ¸ÑÐ¸ÐµÐ½ÑÐ° ÑÐ±Ð»Ð¸Ð¶ÐµÐ½Ð¸Ñ FTN-ÑÐ¸Ð³Ð½Ð°Ð»Ð¾Ð². Ð Ð¿ÑÐ¾ÑÐµÑÑÐµ Ð¸ÑÑÐ»ÐµÐ´Ð¾Ð²Ð°Ð½Ð¸Ñ ÑÐ°ÑÑÐ¼Ð¾ÑÑÐµÐ½Ñ ÑÐµÐ¾ÑÐµÑÐ¸ÑÐµÑÐºÐ¸Ðµ ÑÐ²ÐµÐ´ÐµÐ½Ð¸Ñ Ð¾Ð± FTN-ÑÐ¸Ð³Ð½Ð°Ð»Ð°Ñ Ð¸ Ð¸Ñ Ð¿Ð°ÑÐ°Ð¼ÐµÑÑÐ°Ñ, Ð° ÑÐ°ÐºÐ¶Ðµ Ð½ÐµÐºÐ¾ÑÐ¾ÑÑÐµ ÑÑÑÐµÑÑÐ²ÑÑÑÐ¸Ðµ Ð¸ÑÑÐ»ÐµÐ´Ð¾Ð²Ð°Ð½Ð¸Ñ, Ð¿Ð¾ÑÐ²ÑÑÐµÐ½Ð½ÑÐµ ÑÐ°ÑÐ¿Ð¾Ð·Ð½Ð°Ð²Ð°Ð½Ð¸Ñ Ð°Ð´Ð°Ð¿ÑÐ¸Ð²Ð½ÑÑ Ð¿Ð°ÑÐ°Ð¼ÐµÑÑÐ¾Ð² ÑÐ¸Ð³Ð½Ð°Ð»Ð¾Ð²: Ð¼ÐµÑÐ¾Ð´Ð° Ð¼Ð¾Ð´ÑÐ»ÑÑÐ¸Ð¸, ÐºÐ¾ÑÑÑÐ¸ÑÐ¸ÐµÐ½ÑÐ° ÑÐ¿Ð»Ð¾ÑÐ½ÐµÐ½Ð¸Ñ, ÐºÐ¾ÑÑÑÐ¸ÑÐ¸ÐµÐ½ÑÐ° ÑÐ±Ð»Ð¸Ð¶ÐµÐ½Ð¸Ñ. ÐÐ¾ÑÑÑÐ¾ÐµÐ½Ð° Ð¼Ð¾Ð´ÐµÐ»Ñ ÑÐ¾ÑÐ¼Ð¸ÑÐ¾Ð²Ð°Ð½Ð¸Ñ, Ð¿ÐµÑÐµÐ´Ð°ÑÐ¸ Ð¸ Ð¿ÑÐ¸ÐµÐ¼Ð° FTN-ÑÐ¸Ð³Ð½Ð°Ð»Ð¾Ð² Ñ Ð¿Ð¾Ð¼Ð¾ÑÑÑ ÑÐ¾Ð³Ð»Ð°ÑÐ¾Ð²Ð°Ð½Ð½Ð¾Ð¹ ÑÐ¸Ð»ÑÑÑÐ°ÑÐ¸Ð¸. ÐÐ° Ð¾ÑÐ½Ð¾Ð²Ðµ Ð¼Ð¾Ð´ÐµÐ»ÐµÐ¹ Ð¸ÑÐºÑÑÑÑÐ²ÐµÐ½Ð½ÑÑ Ð½ÐµÐ¹ÑÐ¾Ð½Ð½ÑÑ ÑÐµÑÐµÐ¹ ÑÐ°Ð·ÑÐ°Ð±Ð¾ÑÐ°Ð½ ÐºÐ»Ð°ÑÑÐ¸ÑÐ¸ÐºÐ°ÑÐ¾Ñ ÐºÐ¾ÑÑÑÐ¸ÑÐ¸ÐµÐ½ÑÐ° ÑÐ±Ð»Ð¸Ð¶ÐµÐ½Ð¸Ñ, Ð² ÐºÐ°ÑÐµÑÑÐ²Ðµ Ð²ÑÐ¾Ð´Ð½ÑÑ Ð´Ð°Ð½Ð½ÑÑ ÐºÐ¾ÑÐ¾ÑÐ¾Ð³Ð¾ Ð¸ÑÐ¿Ð¾Ð»ÑÐ·Ð¾Ð²Ð°Ð½Ñ Ð¾ÑÐµÐ½ÐºÐ¸ Ð¼Ð¾Ð´ÑÐ»ÑÑÐ¸Ð¾Ð½Ð½ÑÑ ÑÐ¸Ð¼Ð²Ð¾Ð»Ð¾Ð² Ð¿ÑÐ¸Ð½Ð¸Ð¼Ð°ÐµÐ¼Ð¾Ð³Ð¾ ÑÐ¸Ð³Ð½Ð°Ð»Ð°. Ð Ð°ÑÑÐ¼Ð¾ÑÑÐµÐ½Ð¾ Ð²Ð»Ð¸ÑÐ½Ð¸Ðµ Ð¿Ð°ÑÐ°Ð¼ÐµÑÑÐ¾Ð² RRC-Ð¸Ð¼Ð¿ÑÐ»ÑÑÐ°, Ð¾ÑÐ½Ð¾ÑÐµÐ½Ð¸Ñ ÑÐ¸Ð³Ð½Ð°Ð»/ÑÑÐ¼, Ð° ÑÐ°ÐºÐ¶Ðµ Ð½Ð°ÑÑÑÐ¾ÐµÑÐ½ÑÑ Ð¿Ð°ÑÐ°Ð¼ÐµÑÑÐ¾Ð² ÐºÐ»Ð°ÑÑÐ¸ÑÐ¸ÐºÐ°ÑÐ¾ÑÐ° Ð½Ð° ÑÐ¾ÑÐ½Ð¾ÑÑÑ Ð¿ÑÐ°Ð²Ð¸Ð»ÑÐ½Ð¾Ð¹ ÐºÐ»Ð°ÑÑÐ¸ÑÐ¸ÐºÐ°ÑÐ¸Ð¸ ÐºÐ¾ÑÑÑÐ¸ÑÐ¸ÐµÐ½ÑÐ° ÑÐ±Ð»Ð¸Ð¶ÐµÐ½Ð¸Ñ, Ð¾Ð¿ÑÐµÐ´ÐµÐ»ÐµÐ½Ñ Ð¿Ð°ÑÐ°Ð¼ÐµÑÑÑ, Ð¾Ð±ÐµÑÐ¿ÐµÑÐ¸Ð²Ð°ÑÑÐ¸Ðµ Ð¼Ð°ÐºÑÐ¸Ð¼Ð°Ð»ÑÐ½ÑÑ ÑÐ¾ÑÐ½Ð¾ÑÑÑ. ÐÐ° Ð¸Ñ Ð¾ÑÐ½Ð¾Ð²Ðµ ÑÐ°Ð·ÑÐ°Ð±Ð¾ÑÐ°Ð½Ð° ÑÑÐµÐ¼Ð° ÐºÐ»Ð°ÑÑÐ¸ÑÐ¸ÐºÐ°ÑÐ¾ÑÐ° Ñ Ð½Ð°ÐºÐ¾Ð¿Ð»ÐµÐ½Ð¸ÑÐ¼Ð¸ ÑÑÐ°ÑÐ¸ÑÑÐ¸ÐºÐ¸ Ð¿Ð¾ ÑÐµÑÐµÐ½Ð¸ÑÐ¼. ÐÐ°Ð¹Ð´ÐµÐ½Ð¾ Ð¼Ð¸Ð½Ð¸Ð¼Ð°Ð»ÑÐ½Ð¾Ðµ ÐºÐ¾Ð»Ð¸ÑÐµÑÑÐ²Ð¾ Ð°Ð½Ð°Ð»Ð¸Ð·Ð¸ÑÑÐµÐ¼ÑÑ ÑÐ¸Ð¼Ð²Ð¾Ð»Ð¾Ð², Ð½ÐµÐ¾Ð±ÑÐ¾Ð´Ð¸Ð¼ÑÑ Ð´Ð»Ñ Ð´Ð¾ÑÑÐ¸Ð¶ÐµÐ½Ð¸Ñ Ð²ÐµÑÐ¾ÑÑÐ½Ð¾ÑÑÐ¸ Ð¿ÑÐ°Ð²Ð¸Ð»ÑÐ½Ð¾Ð¹ ÐºÐ»Ð°ÑÑÐ¸ÑÐ¸ÐºÐ°ÑÐ¸Ð¸ Ð½Ðµ Ð¼ÐµÐ½ÐµÐµ 99%. 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, IDE Spyder.
description: The object of study is packing ratio of FTN-signals. The aim is to develop an algorithm for estimating the packing ratio of FTN-signals. During the study, theoretical information about FTN-signals and their parameters, as well as some existing studies devoted to the recognition of adaptive signal parameters: modulation method, compression factor, packing ratio, were considered. A model for the generation, transmission and reception of FTN-signals using matched filtering has been constructed. Based on artificial neural network models, a packing ratio classifier has been developed, the input data of which is based on estimates of the modulation symbols of the received signal. The influence of the parameters of the forming RRC-pulse, the signal-to-noise ratio, as well as the classifierâs own tuning parameters on the accuracy of the correct classification of the packing ratio is considered, and the parameters that ensure maximum accuracy are determined. Based on these parameters, a classifier scheme with solutions statistics accumulation has been developed. The minimum number of analyzed symbols required to achieve a probability of correct classification of the packing ratio of at least 99% has been found. The 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, IDE Spyder.