一种基于深度神经网络的电波传播损耗模型构建方法  

A Construction Methodof Radio Wave Propagation Loss Model Based on Deep Neural Network

作　　者：肖逸凡 周敏 李佳霖 李炳呈 XIAO Yifan;ZHOU Min;LI Jialin;LI Bingcheng(College of Communication Engineering,Army Engineering University of PLA,Nanjing 210007,China)

机构地区：[1]陆军工程大学通信工程学院,江苏南京210007

出　　处：《电声技术》2022年第5期112-115,121,共5页Audio Engineering

摘　　要：将传统经验模型用于电波传播损耗计算,存在泛化性差等问题,在复杂传播环境下难以取得良好的计算效果。针对该问题,本文从数据驱动的角度出发,设计了一种基于深度神经网络的电波传播损耗模型构建方法并进行了仿真验证。首先,基于辐射源与接收机的距离特征及环境特征,构建一定地域内电磁环境感知数据与地形数据的联合数据集,作为本模型的数据源;其次,构建深度神经网络,迭代训练网络参数,并通过网格搜索法优化超参数;最后,运用联合数据集与深度神经网络模型开展计算机仿真实验。结果表明,提出的方法在复杂地域电波传播损耗计算方面能够取得良好的预测精度。If the traditional empirical model is used to calculate the radio wave propagation loss, there will be some problems such as poor generalization, and it is difficult to achieve good calculation results in complex propagation environment. Aiming at this problem,from the perspective of data drive, this paper designs a wave propagation loss model construction method based on deep neural network and simulates it. Firstly, based on the distance and environment characteristics of the radiation source and receiver, a joint dataset of electromagnetic environment perception data and terrain data in a certain region is constructed as the data source of the proposed propagation loss model. Then, the deep neural network is constructed, the network parameters are iteratively trained, and the hyperparameters are optimized by mesh search method. Finally, the computer simulation experiments are carried out using the joint dataset and the deep neural network model, and the results show that the proposed method can achieve good prediction accuracy in the calculation of the radio wave propagation loss in complex regions.

关 键 词：电波传播损耗 深度神经网络 超参数调优 

分 类 号：TP311.1[自动化与计算机技术—计算机软件与理论]