Zobrazeno 1 - 10
of 2 234
pro vyhledávání: '"Modulation classification"'
Publikováno v:
IET Communications, Vol 18, Iss 18, Pp 1220-1230 (2024)
Abstract The wireless Internet of Things (IoT) is widely used for data transmission in power systems. Wireless communication is an important part of the IoT. The existing modulation classification algorithms have low classification accuracy when faci
Externí odkaz:
https://doaj.org/article/cb669d9cda1a4212bb682ba311c265e9
Publikováno v:
EURASIP Journal on Advances in Signal Processing, Vol 2024, Iss 1, Pp 1-16 (2024)
Abstract Automatic modulation classification (AMC) is an important process for future communication systems with prominent applications from spectrum management, and secure communication, to cognitive radio. The requirement for an efficient AMC class
Externí odkaz:
https://doaj.org/article/f3818b8c71d4485ca60539d77512b63f
Publikováno v:
JES: Journal of Engineering Sciences, Vol 52, Iss 4, Pp 46-61 (2024)
This paper presents an innovative deep-learning model for Automatic Modulation Classification (AMC) in wireless communication systems. The proposed architecture integrates Convolutional Neural Network (CNN) and Long Short-Term Memory (LSTM) networks,
Externí odkaz:
https://doaj.org/article/d8a04f2de1704a76a646257164e011fb
Autor:
Venkatramanan M, Chinnadurai M
Publikováno v:
Measurement Science Review, Vol 24, Iss 2, Pp 47-53 (2024)
In a Multiple-Input Multiple-Output Orthogonal Frequency Division Multiplexing (MIMO-OFDM) method, multiple antennas can be used on either the transmitter or receiver end to improve the system capacity, data throughput, and robustness. OFDM has been
Externí odkaz:
https://doaj.org/article/cbfce93889a54bd88b5b99c146436f71
Akademický článek
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Publikováno v:
IEEE Access, Vol 12, Pp 80327-80344 (2024)
Performance of radio frequency machine learning (RFML) models for classification tasks such as specific emitter identification (SEI) and automatic modulation classification (AMC) have improved greatly since their introduction, especially when measure
Externí odkaz:
https://doaj.org/article/ff17706b2a594d7eac6f6adfa6eacb69
Autor:
N. Ussipov, S. Akhtanov, Z. Zhanabaev, D. Turlykozhayeva, B. Karibayev, T. Namazbayev, D. Almen, A. Akhmetali, Xiao Tang
Publikováno v:
IEEE Access, Vol 12, Pp 68463-68470 (2024)
Automatic Modulation Classification (AMC) is an essential technology that is widely applied into various communications scenarios. In recent years, many Machine Learning and Deep-Learning methods have been introduced into AMC, and a lot of them apply
Externí odkaz:
https://doaj.org/article/49e4927036a84032aabca82f32566d69
Publikováno v:
IEEE Open Journal of the Computer Society, Vol 5, Pp 50-61 (2024)
This paper presents a new low-area and low-power Field Programmable Gate Array (FPGA) implementation of a Radio Frequency (RF) modulation classifier based on the Density-Based Spatial Clustering of Applications with Noise (DBSCAN) algorithm, known as
Externí odkaz:
https://doaj.org/article/b8930719b4d940c590238a7f0066356f
Autor:
Ziad Elkhatib, Firuz Kamalov, Sherif Moussa, Adel Ben Mnaouer, Mustapha C.E. Yagoub, Halim Yanikomeroglu
Publikováno v:
IEEE Access, Vol 12, Pp 17552-17570 (2024)
We present an automatic signal modulation classification model using combinatorial deep learning technique. Our proposed deep learning model increase accuracy for low Signal-to-Noise Ratio (SNR) and maintain a high classification accuracy for high SN
Externí odkaz:
https://doaj.org/article/31467303170b4be0aa5e36839c5dda6f
Publikováno v:
IEEE Access, Vol 12, Pp 9267-9276 (2024)
Recent advances in deep learning (DL) have led many contemporary automatic modulation classification (AMC) techniques to use deep networks in classifying the modulation type of incoming signals at the receiver. However, current DL-based methods face
Externí odkaz:
https://doaj.org/article/35d537234ba64720baf5d49b243fb9e0