Research On Blind Equalization Algorithm For AUV Underwater Communication Under Impulse Noise

Autonomous underwater robots(AUV)are flexible,efficient and easy to operate without the need for a cable connection to the console,but the multipath effect of the AUV underwater channel causes severe inter-code interference,which is a major factor in high BER.The blind equalization technique can effectively eliminate the effect of inter-code interference,but the Alpha-stable distribution noise in the underwater channel causes a serious degradation of the performance of the CMA,so it is important to improve the performance of the CMA in the Alpha-stable distribution noise environment to reduce the BER of the communication system.Firstly,this paper investigates the environmental noise,multipath effect and Doppler effect of the AUV underwater channel,and chooses Alpha-stable distributed noise to model the marine environmental noise,analyses the factors affecting the reliability of AUV underwater acoustic communication,and establishes the mathematical models of time-invariant underwater channel and time-varying underwater channel.To address the performance degradation of the CMA in the impulsive noise environment,the FLOSCMA with the introduction of the minimum dispersion coefficient criterion improves the resistance to impulsive noise,but still suffers from slow convergence speed and large steady-state error.The SAPSO and FLOSCMA are combined so that the cost function of the FLOSCMA is used as the fitness function of the SAPSO,and the SAPSO is used to iteratively search for the global optimal solution,which is used as the initial weight vector of the equalizer.The underwater acoustic simulation results show that the algorithm converges faster and has lower inter-code interference.For the FLOSCMA algorithm when it is difficult to obtain channel noise information to adjust the parameters,the performance of the algorithm degrades.In this paper,we introduce the Maximum Versoria Criterion(MVC),modify the cost function of the CMA algorithm and re-derive the power vector iteration formula,the error signal of the improved CMA algorithm does not participate in the power vector iteration directly,but participates in the power vector iteration after a certain transformation,this transformation improves the ability of the CMA algorithm to suppress the impulse noise This transformation improves the ability of the CMA algorithm to suppress impulse noise.This transformation improves the ability of the CMA algorithm to suppress impulse noise.The hyperbolic tangent function is also used to adjust the step size of the weight vector iteration to speed up convergence,and the SAPSO algorithm is used to optimise the initial weight vector of the CMA algorithm to obtain a lower steady-state error.The simulation of the Underwater channel shows that the new algorithm not only has a fast convergence speed and low steady-state error,but also does not need to obtain channel noise information,which is widely applicable and still has a good equalization performance in the face of strong impulsive noise interference.To balance the mutual constraints of convergence speed and steady-state error of the MVC-CMA,the MVC-CMA and the DDLMS algorithm are combined by switching and weighting association methods,and adaptive weighting coefficients are introduced into the DDLMS algorithm to improve the resistance to impulse noise.The MVC-CMA is chosen as the cold start algorithm in the early stage,the MVC-CMA+DDLMS weighting mode in the middle stage,and the DDLMS algorithm in the late stage,with smoother switching between the two algorithms.