中南民族大学学报（自然科学版）2025，Vol.44Issue(6)：826-832,7.DOI:10.20056/j.cnki.ZNMDZK.20250611
不可靠通信下的联邦抗干扰模型优化方案
Optimization scheme of federated anti-interference model with unreliable communication
摘要
Abstract
Aiming at the possible information loss in the communication process caused by interference to the wireless channel in the Cellular Vehicle to Everything(C-V2X)communication scenario,the impact of the above unreliable communication link is reduced by optimizing the anti-interference model update mechanism of the Federated Learning Distributed Stochastic Gradient Descent(FL-DSGD).Firstly,the communication link between the vehicle and the base station and the transmission model parameters are established;Then,when the communication link is unreliable,leading to partial loss of model parameters in the transmission process,according to the link reliability mixed weight matrix,the local model stored on the vehicle and the global model stored in the base station are used to participate in the model update of the current round of federated learning to fill in the missing model parameters.Simulation results show that when the communication link is unreliable,the communication rounds required for FL-DSGD scheme to achieve 90%training accuracy and 85%test accuracy are about 50%of the communication rounds required for the distributed baseline scheme.关键词
联邦学习/车联网/随机梯度下降Key words
federated learning/vehicle to everything/stochastic gradient descent分类
信息技术与安全科学引用本文复制引用
李中捷,郭海榕,邱凡..不可靠通信下的联邦抗干扰模型优化方案[J].中南民族大学学报（自然科学版）,2025,44(6):826-832,7.基金项目
国家自然科学基金资助项目(61379028) （61379028）
湖北省自然科学基金资助项目(2022CFB905) （2022CFB905）
中央高校基本科研业务费专项资金资助(CZY23027) （CZY23027）
