Genetic Algorithm Based MIMO Equalization Parameter Optimization Technology for Mode-Division Multiplexed System
In the digital signal processing unit of the mode-division multiplexed system,the multi-input and multi-output(MIMO)equalization technology is usually used to compensate for the signal bit error rate(BER)degradation disturbed by various mode-dependent noises.The performance of MIMO equalization algorithm depends heavily on the step size factor μ and the number of taps K,so before welding the equalizers,it's important to determine the optimal value of μ-K combination in MIMO equalization algorithm.A genetic algorithm(GA)based MIMO equalization parameter optimization scheme,name-ly GA-MIMO,is proposed to improve the efficiency of the parameter optimization,which is used to reduce the computational costs required during parameter optimization with the minimum BER output.In order to verify the performance of GA-MI-MO,a point-to-point communication experimental system based on 10 km six-mode fiber is constructed.The new scheme is used to compensate the parallelly transmitted six-channel data,and the performance is compared with the steepest descent method and iterative algorithm.The experimental results show that the proposed GA scheme achieves the hit rate of the opti-mal μ-K parameters in MIMO equalization up to 99.98%,and the global search function of GA algorithm helps save the num-ber of calls to the equalization algorithm of 86.14%and 90.3%compared with the steepest descent algorithm and iterative al-gorithm,respectively,effectively reducing the computational cost of locating μ-K parameters.
mode-division multiplexingmulti-input and multi-outputgenetic algorithmfew-mode fiberleast mean square