Research on Lightweight Sensing Technology Based on Single-Antenna Multicarrier

IF 8.9 1区 计算机科学 Q1 COMPUTER SCIENCE, INFORMATION SYSTEMS
Yu Jiang;Di Zhu;Jiadong Wang;Aiqun Hu
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Abstract

Channel state information (CSI) serves as a critical indicator of wireless signal conditions and is widely regarded by researchers for its sensitivity in detecting changes within the channel. However, traditional sensing technologies often require substantial data and intricate learning algorithms, highlighting an urgent need for advancements in lightweight sensing technologies. These technologies should leverage simpler terminal devices, reduced data volumes, and more straightforward classification algorithms to achieve sensing capability that are comparable to those offered by more complex and established methods. This article concentrates on the lightweight application of wireless sensing and encompasses the following key contributions: 1) the development of a lightweight sensing model utilizing a single-antenna multicarrier system, which introduces a CSI ratio model that adapts multiantenna techniques for single-antenna settings and 2) the enhancement of feature stability through the introduction of a complex-plane fitting method using artificial vector, alongside a dual receiver-based method for cross-scene feature generation aimed at producing stable and high-quality auxiliary features. Experimental results show that the feature extraction capability of the single-antenna multicarrier CSI ratio model is close to that of traditional multiantenna scheme. On the gait dataset, when the enhanced CSI ratio is used as a feature, the accuracy is nearly 100%, surpassing the 93% accuracy of the original amplitude feature. On the gesture dataset, the combination of the enhanced CSI ratio and position and environment independent features achieves an accuracy of 96%, which is superior to using the original CSI amplitude feature alone. An analysis of resource consumption shows that the lightweight SVM model incurs very low computational overhead during decision-making, validating the potential of this scheme in terms of efficiency and practical application.
基于单天线多载波的轻量化传感技术研究
信道状态信息(CSI)作为无线信号状态的重要指标,因其在检测信道内部变化方面的敏感性而受到研究人员的广泛关注。然而,传统的传感技术往往需要大量的数据和复杂的学习算法,因此迫切需要发展轻量化传感技术。这些技术应该利用更简单的终端设备、更少的数据量和更直接的分类算法来实现与更复杂和更成熟的方法提供的传感能力相媲美的传感能力。本文主要关注无线传感的轻量级应用,包括以下主要贡献:1)利用单天线多载波系统开发轻量级传感模型,该模型引入了适应单天线设置的多天线技术的CSI比率模型;2)通过引入使用人工向量的复杂平面拟合方法来增强特征稳定性,以及基于双接收器的跨场景特征生成方法,旨在产生稳定和高质量的辅助特征。实验结果表明,单天线多载波CSI比模型的特征提取能力接近传统多天线方案。在步态数据集上,当使用增强的CSI比率作为特征时,准确率接近100%,超过了原始幅度特征93%的准确率。在手势数据集上,将增强的CSI比与位置和环境无关的特征结合使用,准确率达到96%,优于单独使用原始CSI幅值特征。资源消耗分析表明,轻量级支持向量机模型在决策过程中产生的计算开销非常低,验证了该方案在效率和实际应用方面的潜力。
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来源期刊
IEEE Internet of Things Journal
IEEE Internet of Things Journal Computer Science-Information Systems
CiteScore
17.60
自引率
13.20%
发文量
1982
期刊介绍: The EEE Internet of Things (IoT) Journal publishes articles and review articles covering various aspects of IoT, including IoT system architecture, IoT enabling technologies, IoT communication and networking protocols such as network coding, and IoT services and applications. Topics encompass IoT's impacts on sensor technologies, big data management, and future internet design for applications like smart cities and smart homes. Fields of interest include IoT architecture such as things-centric, data-centric, service-oriented IoT architecture; IoT enabling technologies and systematic integration such as sensor technologies, big sensor data management, and future Internet design for IoT; IoT services, applications, and test-beds such as IoT service middleware, IoT application programming interface (API), IoT application design, and IoT trials/experiments; IoT standardization activities and technology development in different standard development organizations (SDO) such as IEEE, IETF, ITU, 3GPP, ETSI, etc.
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