Equilibrium method of communication signals of underwater acoustic channel

Abstract

The invention provides an equilibrium method of communication signals of an underwater acoustic channel. Orthogonal WT is utilized to perform preprocessing on an input signal of an equalizer to reduce the signal to noise ratio of the signal, a CS algorithm with excellent global searching ability is introduced into an MMA and utilized to optimize a cost function of the MMA to obtain global optimal solution of an initial weight vector of the blind equalizer, and accordingly, equilibrium quality of the communication signals of the underwater acoustic channel is improved comprehensively. The equilibrium method of the communication signals of the underwater acoustic channel has the advantages of capturing the global optimal solution well, effectively solving the problems that the MMA is likely to be caught in local minimum, low in convergence rate, large in steady state error and the like, and being high in convergence rate, few in mean square error and high in equilibrium quality.

Description

technical field [0001] The invention relates to a data processing method, in particular to an equalization method for underwater acoustic channel communication signals. Background technique [0002] Due to the limited bandwidth and multipath propagation of underwater acoustic channel communication, the inter-symbol interference is serious. It is necessary to add equalization technology at the signal receiving end to improve the reliability of communication data and ensure the quality of communication. Blind equalization technology uses the statistical characteristics of the transmission sequence itself to restore the transmission information, which has higher frequency band utilization and better equalization timeliness. Adaptive equalization algorithm. In order to further improve channel frequency band utilization, high-order quadrature amplitude modulation (Quadrature Amplitude Modulation, QAM) is often used at the signal transmitting end. [0003] At present, the most w...

AI Technical Summary

Problems solved by technology

The multi-modulus blind equalization algorithm (Multi-Modulus Algorithm, MMA) uses the amplitude and phase information of the QAM signal at the same time, and the weighted multi-modulus blind equalization algorithm (Weighted Multi-Modulus Algorithm, WMMA) adaptively adjusts the cost function by the exponent power of the decision symbol The modulus value and the relevant information in the QAM signal constellation diagram can be further utilized. These two algorithms can effectively correct the phase ambiguity problem of the signal, but the weight vector is still iterated by the steepest descent method, which is easy to fall into a local minimum and cannot Obtain the global optimal solution, so it is still unable to solve the problems of slow convergence speed and large steady-state error after convergence

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