基于卷积神经网络的高速无线局域网分组丢失和错误原因识别方法  

A Multi-classification Approach to Discriminate Causes of Packet Losses and Errors for High Throughput Wireless LAN Based on Convolution Neural Network

作　　者：张宁[1] 黄庭培[2] 蔡丽萍[2] 李世宝[1] ZHANG Ning;HUANG Ting-pei;CAI Li-ping;LI Shi-bao(School of Ocean and Space Information, China University of Petroleum(East China), Qingdao 266580, China;College of Computer Science and Technology, China University of Petroleum(East China), Qingdao 266580, China)

机构地区：[1]中国石油大学(华东)海洋与空间信息学院,山东青岛266580 [2]中国石油大学(华东)计算机科学与技术学院,山东青岛266580

出　　处：《计算机与现代化》2020年第6期14-21,共8页Computer and Modernization

基　　金：国家自然科学基金资助项目(61872385,61673396,61772551,61801517);中央高校基本科研专项资金资助项目(18CX02133A,18CX02134A,18CX02137A)。

摘　　要：无线网络中分组丢失和错误是由信道错误和冲突所导致的。有效识别分组丢失和错误的原因是实现高性能IEEE 802.11n协议的基础。本文主要研究分组丢失和错误原因的识别方法,提高识别原因的准确率,降低识别开销。本文基于监督学习理论提出MPLEC,它是一种轻量级的、准确的分组丢失和错误识别分类方法。MPLEC通过大量实地场景统计实验对分组接收情况进行分析,提取链路层RSSI(Received Signal Strength Indication)、CSI(Channel State Information)组成的特征向量作为监督学习模型的输入。通过监督学习方法对多类MPLEC分类模型进行离线训练和检验,结果表明MPLEC获得至少87%的准确率。最后基于MPLEC的CSMA/CA协议验证了MPLEC的识别性能。实验结果表明,与原有退避算法相比,本文方法可以将重传成功的概率提高25%,时间利用率提高7.8%。Channel errors and collisions are two major factors that cause packet loss and errors in wireless networks.The reason for effectively identifying packet loss and errors is the basis for implementing the high performance IEEE 802.11n protocol.This paper focuses on how to improve the accuracy of discriminating the causes of packet losses and errors with low overhead.Based on the supervised learning theory,this paper proposes a light-weighted discriminator,named MPLEC,to differentiate the root causes of packet losses and errors with high accuracy and timeliness.MPLEC analyzes the packet reception situation through a large number of field scene statistical experiments,extracts the feature vector composed of RSSI and CSI as the input of the supervised learning model,and performs offline training and inspection on the multi-class MPLEC classification model through supervised learning method.The result indicates that the accuracy rate of MPLEC is as high as 87%.Finally,this paper applies the MPLEC to the CSMA/CA protocol to evaluate its performance.The experimental results show that compared with the original backoff algorithm,this method can increase the probability of successful retransmission by 25%and increase the time utilization by 7.8%.

关 键 词：无线局域网 冲突 信道衰落 监督学习 

分 类 号：TP393.2[自动化与计算机技术—计算机应用技术]