Likelihood-ratio approaches to automatic modulation classification
Adaptive modulation and automatic modulation classification are highly demanded in
software-defined radio (SDR) for both commercial and military applications. Various design …
software-defined radio (SDR) for both commercial and military applications. Various design …
A spatiotemporal multi-channel learning framework for automatic modulation recognition
J Xu, C Luo, G Parr, Y Luo - IEEE Wireless Communications …, 2020 - ieeexplore.ieee.org
Automatic modulation recognition (AMR) plays a vital role in modern communication
systems. This letter proposes a novel three-stream deep learning framework to extract the …
systems. This letter proposes a novel three-stream deep learning framework to extract the …
Survey of automatic modulation classification techniques: classical approaches and new trends
The automatic recognition of the modulation format of a detected signal, the intermediate
step between signal detection and demodulation, is a major task of an intelligent receiver …
step between signal detection and demodulation, is a major task of an intelligent receiver …
On the likelihood-based approach to modulation classification
F Hameed, OA Dobre… - IEEE transactions on …, 2009 - ieeexplore.ieee.org
In this paper, likelihood-based algorithms are explored for linear digital modulation
classification. Hybrid likelihood ratio test (HLRT)-and quasi HLRT (QHLRT)-based …
classification. Hybrid likelihood ratio test (HLRT)-and quasi HLRT (QHLRT)-based …
Real-time radio technology and modulation classification via an LSTM auto-encoder
Identification of the type of communication technology and/or modulation scheme based on
detected radio signal are challenging problems encountered in a variety of applications …
detected radio signal are challenging problems encountered in a variety of applications …
Deep cascading network architecture for robust automatic modulation classification
BACKGROUND: Automatic modulation classification (AMC) plays a crucial role in cognitive
radio, such as industrial automation, transmitter identification, and spectrum resource …
radio, such as industrial automation, transmitter identification, and spectrum resource …
Novel automatic modulation classification using cumulant features for communications via multipath channels
Nowadays, automatic modulation classification (AMC) plays an important role in both
cooperative and non-cooperative communication applications. Very often, multipath fading …
cooperative and non-cooperative communication applications. Very often, multipath fading …
Automatic modulation classification for cognitive radios using cyclic feature detection
B Ramkumar - IEEE Circuits and Systems Magazine, 2009 - ieeexplore.ieee.org
Cognitive radios have become a key research area in communications over the past few
years. Automatic modulation classification (AMC) is an important component that improves …
years. Automatic modulation classification (AMC) is an important component that improves …
Low complexity automatic modulation classification based on order-statistics
In this paper, we propose three automatic modulation classification classifiers based on
order-statistics and reduced order-statistics, where the order-statistics are the random …
order-statistics and reduced order-statistics, where the order-statistics are the random …
Blind modulation classification: a concept whose time has come
We address the problem of identifying the modulation format of an incoming signal. We
review many existing techniques for digital modulation recognition in a systematic way …
review many existing techniques for digital modulation recognition in a systematic way …