Blind Equalization Of Underwater Acoustic Channel Based On Chaotic Artificial Bee Colony Algorithm For Tournament Selection

Competition among Marine powers is the international background of the development of Marine science and technology and the basic national policy of China.The collection and transmission of Marine information plays an important role in supporting Marine resources exploration,environmental monitoring,disaster early warning,fishery management,scientific investigation and offshore oil and gas exploitation.The underwater acoustic channel is a very complicated random channel with narrow frequency band and low transmission efficiency.The time-varying and multipath time-delay effect of underwater acoustic channel make the channel have time and frequency selective fading,which leads to serious inter-symbol interference in underwater acoustic channel.The traditional adaptive equalization technology can suppress the influence of multipath effect,but it takes up a lot of channel bandwidth and reduces the communication efficiency because it needs to send the training sequence periodically.Blind equalization improves communication efficiency because it does not need to send training sequence repeatedly.However,the traditional blind equalization technology has many shortcomings,such as large steady error,slow convergence speed and easy to fall into local minimum.Therefore,a Tournament-Selection of Chaotic Artificial Bee Colony Algorithm(TCABC)is proposed to optimize the blind equalization technique.This paper has mainly completed the following work:(1)A chaotic artificial bee colony algorithm for tournament selection is proposed.By using chaotic matrix to initialize the population,the evolution speed of the population is accelerated and the algorithm is prevented from falling into local optimum.Gaussian perturbation is applied to the new generation population to increase the diversity of population and prevent the algorithm from falling into local optimum.Finally,the tournament selection algorithm is used to calculate the probability of following and leading bees,which improves the global information utilization rate of the algorithm and avoids the precocity phenomenon.(2)Constant Modulus blind equalization Algorithm(CMA)was improved by using chaotic artificial bee colony Algorithm chosen from the tournament.The mean square error value between the equalized signal and the ideal noiseless signal was taken as the cost function of TCABC algorithm,the initial weight of CMA was taken as the honey source of the algorithm,and the global minimum value of the algorithm output was taken as the new initial tap coefficient of the equalizer,so as to optimize the CMA blind equalization algorithm.(3)Simulation verifies the effectiveness of TCABC Algorithm and TournamentSelection of Chaotic Artificial Bee Colony Algorithm-CMA(TCABC-CMA).In this paper,based on six basic test functions,the chaotic artificial bee colony algorithm selected by the tournament is compared with the traditional bee colony algorithm,particle swarm optimization algorithm,cuckoo algorithm,firefly algorithm and differential evolution algorithm for optimization simulation tests,to prove the effectiveness of the proposed algorithm.Then,the TCABC-CMA Algorithm and the improved Artificial Bee Colony algorithm-CMA(ABC-CMA)Algorithm were compared for signal equalization simulation to further verify the effectiveness of the proposed TCABC-CMAAlgorithm.The research shows that the convergence rate of the improved algorithm is better than the other five algorithms,and its applicability is greatly improved.After applying the chaotic artificial bee colony algorithm chosen in the championship to the blind equalization algorithm of underwater channel,the mean square error is significantly improved under the condition that the convergence speed is basically unchanged,which effectively improves the convergence precision of constellation and greatly enhances the effectiveness of the blind equalization technology.