摘要
针对经典的逆变换和舍弃法模拟信道噪声硬件实现复杂的问题,开发了一种基于谐波叠加(Sum-of-Sinusoids,So S)中心极限理论和Hadamard矩阵变换相结合的改进方法实时产生高斯噪声,推导了该方法输出随机变量幅值的理论分布,分析了利用可编程逻辑器件(Field-Programmable Gate Array,FPGA)硬件实现时,定点化位宽和查找表深度对输出精度和周期的影响。数值仿真表明,本文改进方法输出的幅值统计分布精度优于传统So S方法,尾巴精确度有所提高,重复周期也大大扩展,可以满足实际中信道噪声硬件模拟的需求。
Since the conventional generation methods,i.e.,the inversion method and rejection method,are very complicated for hardware implementation,we develop an improved method for reproducing channel noises with Gaussian distributions in real-time.By introducing the Hadamard matrix transformation,the proposed method modifies the Sum-of-Sinusoids(SoS)method based on the central limit theory.On this basis,the theoretical amplitude distribution of output random variables is derived,and then by utilizing the field programmable gate array(FPGA)hardware,the effects of the width of fixed-point data and the depth of look-up tables on the distribution and periodicity of output variables are analyzed.Numerical simulation results show that the amplitude distribution of the new method has higher precision than that of the traditional SoS method.In addition,the accuracy of the tail distribution and the repetition period are both improved significantly,which also shows the proposed method can meet the requirements of channel noise emulation in reality.
作者
杨志强
朱秋明
台鑫
刘亮
陈小敏
廖志忠
YANG Zhi-qiang;ZHU Qiu-ming;TAI Xin;LIU Liang;CHEN Xiao-min;LIAO Zhi-zhong(College of Electronic and Information Engineering,Nanjing University of Aeronautics and Astronautics, Nanjing,Jiangsu 211100,China;Heriot-Watt University,School of Engineering&Physical Sciences,Edinburgh, EH14 4AS,U.K;China Airborne Missile Academy,Luoyang,Henan 471009,China;The 41st Institute of China Electronics Technology Group Corporation,Qingdao,Shandong 233006,China)
出处
《信号处理》
CSCD
北大核心
2018年第7期787-792,共6页
Journal of Signal Processing
基金
国家重大科学仪器设备开发专项(2013YQ200607)
国家自然科学基金重点项目(61631020)
江苏省博士后基金资助(1601017C)
中央高校基本科研业务费青年科技创新基金(NS2016044)
江苏省物联网与控制技术重点实验室基金(NJ20160027)资助
关键词
信道噪声
高斯分布
模拟方法
中心极限理论
谐波叠加
channel noise
Gaussian distribution
generation method
central limit theory
sum-of-sinusoids(SoS)