Blind Equalization Algorithm Based On DNA Artificial Fish Swarm And CCS Realization

The complex of underwater acoustic channel may cause intersymbol interference, which seriously affects the quality of communication. Therefore, the blind equalization algorithm is used to improve the communication speed effectively. Aiming at the defects of traditional blind equalization algorithm such as slow convergence speed, large steady-state error, this paper optimizes the performance of blind equalization algorithm by using DNA restriction model, DNA genetic algorithm and artificial fish swarm algorithm. The research content includes mainly following several aspects:1. Multi-modulus algorithm based on artificial fish swarm intelligent optimization of DNA sequences is proposed. Aiming at the defect of slower convergence speed in the constant modulus blind equalization algorithm, constant modulus algorithm based on artificial fish swarm algorithm is proposed. The optimization of the initial weight vector of the equalizer is to find the extremum of the cost function by the artificial fish swarm algorithm. So, it can improve the performance of constant modulus algorithm. But, it has the shortcoming of phase rotation. And the artificial fish swarm algorithm is easy to fall into local search. In order to solve these problems, a multi-modulus algorithm based on artificial fish swarm intelligent optimization DNA sequences is proposed. In order to improve the global search capability of the algorithm, artificial fish swarm algorithm is constrained by the Hamming constraints.2. Weighted multi-modulus algorithm based on DNA encoding sequences optimized by artificial fish swarm and genetic algorithm is proposed. The artificial fish swarm algorithm in the late stage of convergence is easy to fall into local search. Therefore, the DNA genetic algorithm and artificial fish swarm algorithm combine the DNA genetic artificial fish swarm algorithm. The algorithm can greatly avoid the algorithm fall into local search. Through the multi constraint conditions and cost function, the DNA genetic artificial fish swarm algorithm is applied to the blind equalization algorithm. The weighted multi-modulus algorithm based on DNA encoding sequences optimized by artificial fish swarm and genetic algorithm is formed.3. Frequency domain weighted multi-modulus algorithm based on DNA sequences optimized by genetic artificial fish swarm with novel crossover and mutation is proposed. Currently, the operators of DNA genetic algorithm are the simple crossover operator, mutation operator and inversion operator. In order to improve the performance of DNA genetic algorithm, DNA genetic algorithm is improved by using a new crossover operator and mutation operator. In addition, chaos artificial fish swarm algorithm can reduce the probability of falling into local search by chaotic maps and perturbations. So, the frequency domain weighted multi-modulus algorithm based on DNA sequences optimized by genetic artificial fish swarm with novel crossover and mutation is proposed4. CCS software is a DSP integrated development environment. Through the CCS software simulation, the feasibility of the algorithm is further verified. Therefore, multi-modulus algorithm and weighted multi-modulus algorithm based on DNA encoding sequences optimized by artificial fish swarm and genetic algorithm are compiled with C language. Comparing mean square error and constellation, algorithm to verify the feasibility.It lays the foundation for hardware implementation with DSP and its application.