The Study Of Parameters Estimation For Common Digital Communication Signals

In the electronic communications, non-cooperative communication systems arewidely used in many fields. For the government departments, in order to ensure thenormal operation of the legitimate communication, for military, in order to protect one’snormal communications or interfere with enemy communications, non-cooperativecommunication system is needed to monitor the unknown signal. In the non-cooperativecommunication, it’s important to receive the unknown signal effectively, estimateparameter, identify and demodulate the modulations blindly. Among them, theparameter estimation is an important prerequisite for the identification and blinddemodulation of the signal modulation. Digital communication signals are more widelyused than analog communication signals. Therefore, this paper focused on the parameterestimation of the commonly digital communication signals.This paper firstly introduced the signal model and the spectral characteristics ofcommonly digital signals, and then focuses on the symbol rate and the carrier frequencyestimation of the signals.For symbol rate estimation, it’s deduced that the squared spectrum of signal’scomplex envelope contains the line of symbol rate. Therefore, the symbol rates ofPSK/QAM/ASK signals are estimated from the squared spectrum of signal’s complexenvelope. Since the FSK signal’s complex envelope is a function of time, the symbolrate can’t be estimated by the squared spectrum. Based on the good mutation detectedcapability of the wavelet transform, the symbol rates including FSK signal’s symbol rateare estimated by the method of combining multiple wavelet scales. Because the I Roadand Q Road of OQPSK signal stagger half a symbol period, the above two methodscannot estimate its symbol rate. In this paper, we use the squared spectrum to estimatethe symbol rate of the OQPSK signal.For carrier frequency estimation, this paper focused on the PSK/QAM/FSK signals.For the known modulation and modulation order of PSK/QAM signals, the signalmodulation information is removed through the non-linear transformation, and then the signal carrier frequency is estimated by the combination of FFT and CZT method. Forthe blind Estimation for PSK/QAM carrier frequency, the phase information ofautocorrelation function is used to estimate the carrier frequency, and an improvedmethod is proposed to reduce the computational complexity of the algorithm. Accordingto the sub-carrier characteristics of the FSK signals, the power spectrum of the ARmodel of signals is applied to estimate the carrier frequency by extracting thesub-carrier frequencies. By adjusting the power spectrum of the amplitude values andsetting activity threshold, the performance of the algorithm in low SNR is improved.