The Research Of Blind Equalization Algorithm In Vector Signal Analysis Based On Virtual Instrument

Higher requirement was put forward to the accurate measurement of digital modulation signal because of the rapid development of digital modulation techniques. Vector signal analyzer is able to achieve comprehensive measurement of vector signal. However, the signal will be affected by group delay in the transmission process, which will affect the demodulation and recovery for the vector signal analyzer, thereby increasing the instrument's measurement errors. With the improvement of transmission rate of modern communication signal, the impact of group delay distortion in signal transmission is also growing. Thus, in the vector signal analysis, in order to achieve accurate measurements in modulation domain, it's necessary to take appropriate compensation means to compensate for group delay distortion. Equalization technology is most commonly used signal compensation means on the receiving end, among which, blind equalization algorithm does not need to send training sequences, this excellent features make it is widely used in actual communication. Therefore, in this paper, commonly used algorithms CMA and MCMA were simulated and analyzed, and a correction strategy for the fixed step of MCMA algorithm was put forward by using the correlation of the input signal. In the realization of virtual vector signal analyzer, the blind equalization algorithm joined the software part to improve the measurement precision.The research work of this paper is as follows:First, the basic principle of the vector signal analysis and commonly used modulation signal display mode and measurement standard were studied. Group delay and channel group delay distortion was simulated, based on which, group delay distortion generated in the transmission process and the impact on measurement accuracy of vector signal analyzer were also studied.Second, the group delay distortion in signal transmission can be compensated by equalization algorithm, therefore, the classic Bussgang blind equalization algorithm is commonly used, and among which, constant modulus blind equalization algorithm(CMA) and the modified constant modulus blind equalization algorithm(MCMA) were simulated. Iteration efficiency, convergence errors and other properties were also compared. MCMA algorithm can overcome the shortcoming of CMA algorithm that is not sensitive to the lack of phase, but its cost function using a fixed size iterative step leads to that there is a mutual restraint between the step and the convergence stability. To solve this problem, we use the correlation between the input signals to correct the iterative step, so that steps can be continuously adjusted according to the correlation of the input signal to overcome the defects of fixed step, remaining ISI after signal convergence can be reduced by 4d B compared with the previous algorithm.Third, the vector signal analyzer based on virtual instrument was designed and implemented. PXI hardware development environment and Lab VIEW software programming were combined to realize the vector signal analysis. Software programming with Lab VIEW is used to achieve signal quadrature demodulation, modulation domains measurement and display of measurement results. What's more, blind equalization algorithm is added to compensate the group delay distortion of the signal transmission, aiming to improving the accuracy of measurement instrument.