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Continuous Phase Modulation Classification via Baum-Welch Algorithm

delete2018-07-01
delete18
PRE
AI
J
Jingwen Zhang
王方刚 (Fanggang Wang) *
钟章队 (Zhangdui Zhong)
S
Shilian Wang
DOI:10.1109/LCOMM.2018.2821171delete
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Abstract

Abstract

En 中文
Due to high spectral and power efficiency, continuous phase modulation (CPM) is widely adopted in wireless communications, such as satellite communications. In this letter, we investigate the classification of CPM signals in the presence of unknown fading channels. The time-varying phases of CPM are first formulated as a hidden Markov model (HMM) by observing its memorable property. Then, a likelihood-based classifier is proposed using the Baum-Welch algorithm, which is able to estimate the unknown parameters in the HMM. Simulation results show that the proposed algorithm outperforms the existing scheme using approximate entropy in terms of classification performance.
Keywords:
Baum-Welch algorithm
continuous phase modulation
modulation classification
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Journal

IEEE Communications Letters cover
IEEE Communications Letters
IF:
4.4
Papers:
1.3W
Citations:
2.2W

Organization

B
Beijing Jiaotong University
Scholars:
2.2W
Papers: 1.7W
Citations: 1.2W
N
national university of defense technology - china
Scholars:
1.8W
Papers: 1.4W
Citations: 9