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A recognition algorithm for BPSK/QPSK signals based on generalized Pareto distribution
- Source :
- 2017 13th IEEE International Conference on Electronic Measurement & Instruments (ICEMI).
- Publication Year :
- 2017
- Publisher :
- IEEE, 2017.
-
Abstract
- In this paper, an algorithm for recognizing BPSK/QPSK signal is proposed. Extreme value theory is introduced, and an exceedance sequence is built from the modified spectrum obtained by the squaring operation of the observed signal, and the problem of recognizing the BPSK/QPSK signal is transformed to the problem of whether the distribution of the exceedance sequence approximately follows its standard generalized Pareto distribution or not. Finally, the Kolmogorov — Smirnov test is applied to perform the goodness-of-fit test of the generalized Pareto distribution of the exceedance sequence to complete the task of BPSK/QPSK signal recognition. Computer simulation results show that the recognition performance is good when the signal-to-noise ratio is moderate and does not require prior information such as noise variance.
- Subjects :
- Sequence
Computer science
Noise (signal processing)
Feature extraction
020302 automobile design & engineering
020206 networking & telecommunications
02 engineering and technology
Signal
Computer Science::Performance
Signal-to-noise ratio
0203 mechanical engineering
Generalized Pareto distribution
0202 electrical engineering, electronic engineering, information engineering
Extreme value theory
Algorithm
Computer Science::Information Theory
Phase-shift keying
Subjects
Details
- Database :
- OpenAIRE
- Journal :
- 2017 13th IEEE International Conference on Electronic Measurement & Instruments (ICEMI)
- Accession number :
- edsair.doi...........49bc09335c833e9880fb639c0bffb2be