A Novel CMA+DD_LMS Blind Equalization Algorithm for Underwater Acoustic Communication

Abstract

Abstract The performance of underwater acoustic communication system is affected seriously by inter-symbol interference caused by multipath effects. Therefore, a novel blind equalization algorithm based on constant modulus algorithm (CMA) and decision-directed least mean square (DD_LMS) is adopted to improve the equalization ability of the system. Firstly, the LMS algorithm is improved by introducing inverse hyperbolic sine function and three adjustment factors to control step-size and the appropriate parameter values are set through the simulation of three adjustment factors. Secondly, the error values of the step-size function are replaced with error expectations to improve the anti-noise performance. Finally, the improved step-size function is introduced into the CMA and DD_LMS algorithm and the difference of the iteration error of adjacent k times is used as the switching condition of the dual mode algorithm. The results show that the algorithm has good equalization and anti-noise performance at both high and low signal-to-noise ratio (SNR), especially at low SNR, its steady-state error is ~10 dB lower than the traditional CMA and its convergence speed is ~15% higher than the traditional CMA. This algorithm can be used to effectively improve the communication efficiency of the communication system of underwater robots, which has good application value.