电讯技术2025，Vol.65Issue(7)：1078-1086,9.DOI:10.20079/j.issn.1001-893x.250114002
应用距离裁剪策略的改进k均值聚类量化算法
Improved k-Means Clustering Quantization Algorithm with Distance Trimming Strategy
摘要
Abstract
A distance-based sample screening strategy is proposed to enhance key consistency during physical layer key generation.The strategy evaluates classification uncertainty by calculating the Euclidean distance difference between samples and clustering centers,then eliminates high-uncertainty samples to reduce noise interference.Simulation results show that when applied to k-Means quantization and compensated k-Means quantization,the classification inconsistency rate decreases by 8.1%and 11.7%for 5-bit quantization,and by 63.4%and 89.3%for 1-bit quantization,respectively.关键词
物理层安全/密钥生成/信道量化:k均值聚类/距离裁剪策略Key words
physical layer security/key generation/channel quantization/k-Means clustering/distance trimming strategy分类
信息技术与安全科学引用本文复制引用
查坤,安永丽,刘英超,宋文丰..应用距离裁剪策略的改进k均值聚类量化算法[J].电讯技术,2025,65(7):1078-1086,9.基金项目
唐山市人才项目(B202302013) （B202302013）
唐山市科技项目(24130215C) （24130215C）
