通信学报2023，Vol.44Issue(11)：201-212,12.DOI:10.11959/j.issn.1000-436x.2023200
基于扩散模型的室内定位射频指纹数据增强方法
Radio frequency fingerprint data augmentation for indoor localization based on diffusion model
摘要
Abstract
The radio frequency fingerprint indoor localization method ensures the accuracy by collecting a sufficient amount of fingerprints in the offline state to build a dense fingerprint database.A data augmentation method called FPDiffusion was proposed based on diffusion model to reduce the cost of fingerprint acquisition.Firstly,a temporal graph representation of the fingerprint sequence was constructed,the forward process of the diffusion model was accomplished by adding Gaussian noise,and a U-Net was utilized for the reverse process.The loss function of the network was de-signed according to the characteristics of radio frequency fingerprints.Finally,the computational process for generating dense fingerprints based on sparse fingerprints was presented.Experimental results demonstrate that FPDiffusion achieves 76%and 28%localization error reduction on K-nearest neighbor(KNN)and convolutional neural network(CNN)respectively,and significantly improves localization accuracy on KNN compared to Gaussian process regression(GPR)and GPR-GAN when only a small amount of labeled fingerprints is available.关键词
扩散模型/数据增强/射频指纹/室内定位Key words
diffusion model/data augmentation/radio frequency fingerprint/indoor localization分类
信息技术与安全科学引用本文复制引用
艾浩军,曾维珂,陶荆杰,徐锦盈,常含笑..基于扩散模型的室内定位射频指纹数据增强方法[J].通信学报,2023,44(11):201-212,12.基金项目
国家自然科学基金资助项目(No.61971316) （No.61971316）
国家重点研发计划基金资助项目(No.2016YFB0502204) The National Natural Science Foundation of China(No.61971316),The National Key Research and Develop-ment Program of China(No.2016YFB0502204) （No.2016YFB0502204）
