A suboptimal algorithm for modulation classification

• Published in: IEEE transactions on aerospace and electronic systems Vol. 33; no. 1; pp. 38 - 45
• Main Authors: Yawpo Yang, Soliman, S.S.
• Format: Journal Article
• Language: English
• Published: New York, NY IEEE 01.01.1997; Institute of Electrical and Electronics Engineers
• Subjects: Additive white noise; Applied sciences; AWGN; Binary phase shift keying; Classification algorithms; Density functional theory; Exact sciences and technology; Information, signal and communications theory; Modulation, demodulation; Monte Carlo methods; Phase modulation; Probability; Quadrature phase shift keying; Signal and communications theory; Statistics; Telecommunications and information theory; Performance evaluation; Statistical method; Phase shift keying; M ary modulation; Classification; Quadrature modulation; Automatic recognition; Algorithm
• ISSN: 0018-9251; 1557-9603
• DOI: 10.1109/7.570706

In this paper we present a suboptimal algorithm for modulation classification to classify the general M-ary phase-shifted keying (MPSK) signal buried in additive white Gaussian noise (AWGN). We first derive the phase density functions of MPSK signals, then develop the required statistics for modulation classification and demonstrate a classifier for CW, binary phase-shifted keying (BPSK), quadrature phase-shifted keying (QPSK), and 8PSK. The structure of the proposed classifier is flexible and is easy to expand. The performance of classifier is evaluated in terms of the probability of successful classification. An example (BPSK/QPSK case) is provided to demonstrate the capabilities of the proposed classifier. The performance is evaluated through the theoretical approach and the Monte Carlo computer simulations and is compared with that previously published in 1992. It is shown that the performance of the proposed classifier is better. Further improvement in performance can be obtained by increasing the length of observation interval.