电子学报2024，Vol.52Issue(5)：1601-1608,8.DOI:10.12263/DZXB.20230241
面向模分复用系统的遗传-MIMO均衡参数优化技术
Genetic Algorithm Based MIMO Equalization Parameter Optimization Technology for Mode-Division Multiplexed System
摘要
Abstract
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.关键词
模分复用/多输入多输出/遗传算法/少模光纤/最小均方误差Key words
mode-division multiplexing/multi-input and multi-output/genetic algorithm/few-mode fiber/least mean square分类
信息技术与安全科学引用本文复制引用
赵天烽,文峰,冯变霞,武保剑,许渤,邱昆..面向模分复用系统的遗传-MIMO均衡参数优化技术[J].电子学报,2024,52(5):1601-1608,8.基金项目
国家重点研发计划(No.2018YFB1801001) National Key Research and Development Program of China(No.2018YFB1801001) （No.2018YFB1801001）
