摘要
周围环境中不断增加的物联网设备带来了巨大的机遇,但也带来了挑战,包括有限的电池寿命、低计算能力和多址接入的可扩展性.反向散射通信使得无处不在的物联网设备能够以超低功耗的方式进行通信,然而,支持大规模并发通信也是反向散射通信需要研究的问题之一.针对大规模标签并发通信误码率(BER)较高、传输速率低等问题,设计基于编码的码分多址(CDMA)接入技术,以支持多标签反向散射并发可靠通信.首先,该系统利用沃尔什(Walsh)码等正交性较强的码片区分标签并结合纠错编码,以增强抗干扰能力;其次利用相关检测与译码联合解码以降低误码率,实现信道的可靠通信;最后,在此基础上,基于K均值聚类算法(K-means clustering algorithm)设计标签分组机制,充分利用时-码2维资源扩充容量.实验表明,该方案能够实现100+个标签的可靠通信,误码率约2%、吞吐量达到了39 Mbps.
The increasing number of the Internet of things(IoT)devices in our environment presents significant opportunities as well as challenges,including limited battery life,low computing power,and scalability for multiple access.Recent advances in backscatter communication have enabled ubiquitous IoT devices to communicate in an energy-effective manner.However,a fundamental challenge in backscatter communication is to design a multiple access protocol to support concurrent communications from numerous tags.Aiming at tackling the high bit error rate and low transmission rate of large-scale tag concurrent communication,we design a coding-based code division multiple access technique to facilitate multi-tag backscattering with reliable communication.Firstly,the chip discrimination tags with strong orthogonality such as Walsh code are combined with error correction coding to enhance the anti-interference ability.Secondly,the joint decoding of correlation detection and decoding is used to reduce the bit error rate and realize the reliable communication from the backscatter link.Finally,a grouping algorithm is designed to cluster tags based on the K-means clustering algorithm,which fully utilizes the time-code resources and enhances the capacity.Experimental results demonstrate that our scheme can achieve reliable communication with 100+tags,with a bit error rate of approximately 2%,and the achieved throughput of 39 Mbps.
作者
何昕
吴帆
祝玉军
许勇
杨盘隆
He Xin;Wu Fan;Zhu Yujun;Xu Yong;Yang Panlong(School of Computer and Information,Anhui Normal University,Wuhu,Anhui 241002;School of Computer Science,Nanjing University of Information Science and Technology,Nanjing 210044;School of Computer Science and Technology,University of Science and Technology of China,Hefei 230026)
出处
《计算机研究与发展》
EI
CSCD
北大核心
2024年第12期3098-3107,共10页
Journal of Computer Research and Development
基金
国家重点研发计划项目(2018YFB2100302)
国家自然科学基金项目(62072004,61702011)。
