MIMO Blind Equalizer Research Based On DNA Genetic Shuffled Frog Leaping Algorithm

Intersymbol interference is an unavoidable problem in the process of communication, it will make a big difference to the quality of communication,however, by the use of blind equalization algorithm, the signal can be received effectively, thus getting a good effect when restoring signal. Actually, the traditional blind equalization algorithm has a very slow convergence speed and large mean square error. In this thesis, blind equalization algorithm aiming in improving the shortcomings of traditional blind equalization algorithm is proposed, which consists the DNA genetic algorithm, the new DNA genetic algorithm and shuffled frog leaping algorithm ,then the performance of blind equalization algorithm can be optimized. The research content mainly includes the following aspects:1. DNA genetic leapfrog optimized algorithm based on constant modulus blind equalization algorithm is proposed. Because of the constant modulus blind equalization algorithm has slow convergence rate and big mean square error, the shuffled frog leaping algorithm has stronger ability of optimization, fewer parameters and good versatility advantages, but it is easy to fall into local convergence, if we directly use the optimal frog position vector as the initial weight vector of constant modulus blind equalization, it can not get good results. DNA genetic algorithm has strong global search capability advantages, this paper use DNA genetic algorithm to optimize the SFLA and get DNA genetic leapfrog algorithm, this algorithm remedies shortcomings of SFLA, the algorithm has stronger ability of optimization and faster convergence speed. This thesis firstly uses DNA genetic leapfrog algorithm to search out the best individual frogs, and then uses its location vector as the initial weight vector of constant modulus blind equalization, and then DNA genetic optimized leapfrog algorithm based on constant modulus blind equalization algorithm is proposed. The simulation results show that compared with norm blind equalization algorithm based on hybrid leapfrog optimization and norm blind equalization algorithm, the mean square error of new algorithm reduced 8dB and 12dB and the convergence speed improved 200 and 900 steps.2. MIMO multi modulus blind equalization algorithm based on the optimization of new DNA genetic leapfrog is proposed. Because of the MIMO communication system has the advantages of large capacity and high spectral efficiency, has become a research hotspot in the field of communication content, but the MIMO communication system is still affected by intersymbol interference, using multi-modulus blind equalization algorithm not only can realize blind equalization function, but also can recovery carrier phase. In this thesis, the multi-mode blind equalization algorithm is used to recover the received signal in the MIMO system,but the multi-mode blind equalization still has model error. The DNA genetic algorithm operation is ordinary crossover operator and ordinary mutation operator, in order to further improve the performance of DNA to optimize SFLA, this thesis proposes a new crossover operator and a new mutation operator, it increases the diversity of population, improves the global search ability, thus the MIMO multi-modulus blind equalization algorithm based on the optimization of new DNA genetic leapfrog is proposed. The simulation results show that compared with the MIMO system multi-mode blind equalization algorithm,The intersymbol interference of the new algorithm reduced 3dB and the convergence rate increased by 2,000 steps.3. Blind equalization algorithm for correlated MIMO channels based on the optimation of new DNA genetic leapfrog is proposed. The quality of wireless communication system for transmitting signals directly affected by the channel performance, this thesis Compares the BER of Gauss, Rayleigh and Rice and correlated MIMO channel, the result shows that when SNR is above 16dB, correlated MIMO channel has the minimum bit error rate, so when the SNR is above 16dB, use the MIMO channel. The simulation used the new DNA leapfrog optimization of the performance of the MIMO to test the different channel blind equalization algorithm including the MIMO channel, the Rician and the Rayleigh, Gaussian channel. The algorithm convergence speed in the MIMO channel is faster than the others by 300,200 and 100 steps. The intersymbol interference reduced by 3, 2.7 and 1.5dB.