Research On Modulation Recognition Of Digital Communication Signals

In modern telecommunication field, modulation recognition technology of communication signal is widely used in electronic countermeasures(ECM),spectrum management, adaptive reception and cognitive radio. In existing literature, the modulation recognition method for communication signal mainly can be divided into two types. One is the likelihood-ratio hypotheses-test method based on decision-theoretic and the other is pattern recognition method based on feature extraction. Though the former can be used to achieve great results of recognition, it exists the problem of complex computation amount and it is also very sensitive to frequency offset, phase offset and timing error.Compared with likelihood-ratio hypotheses-test method, pattern recognition method has lower calculated complexity and higher efficiency. On the other hand, the identification effect can be great only if the characteristic parameters are chosen reasonably and it also has relatively high stability. So the paper is focused on the feature extraction criterion.Using the method of wavelet transform, the paper extracts the characteristic parameters of PSK, ASK and FSK signals and classifies the signals effectively. On the premise of additive white gaussian noise, we illustrate the selection of scale factor and extract the characteristic parameters of signals by the amplitude coefficient of wavelet transform. The communication signals are simulated by the tool of MATLAB, and we illustrate the effectiveness of the algorithm through simulation.The paper also researches how to classify the BPSK signal and QPSK signal based on high-order cumulants in the condition of multipath channels. In wireless communication, it usually exists multipath fading phenomenon in the process of transmitting in real channel. In multipath channels, the performance will be declined and the algorithm based on general modulation recognition will be invalid. Aiming at solving the above issues, this paper proposed the combined modulation recognition algorithm of fourth-order cumulant and sixth-order cumulant. When the multipath number is 2, the proposed method can have better effect on anti-multipath interference compared with fourth-order cumulant in theory. The simulation results show that in multipath fading condition, the proposed algorithm for classifying the BPSK signal and QPSK signal has higher recognition rate than that based on fourth-order cumulant algorithm. In multipath channel of SNR equal to 2dB, the identification ratio of the BPSK signal and QPSK signal almost reaches 100%. In the process of identifying the BPSK signal, the identification performance based on the combined fourth-order cumulant and sixth-order cumulant algorithm is better than that based on fourth-order cumulant algorithm.