Wireless Networking

In the process of target tracking and localization in bearing-only sensor network, it is an essential and significant challenge to solve the problem of plug-and-play expansion while enhancing the accuracy of state estimation and stability of the system. This paper proposes the distributed cubature information filtering method based on the two-layer factor graph.

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The "RF Jamming Dataset for Vehicular Wireless Networks" presents a comprehensive collection of data used in the research paper titled "RF Jamming Classification Using Relative Speed Estimation in Vehicular Wireless Networks." This dataset comprises diverse scenarios of RF jamming attacks and interference in Vehicular Ad-hoc Networks (VANETs), along with corresponding ground truth labels. The dataset is designed to support the evaluation and development of detection algorithms for RF jamming attacks in VANETs.

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978 Views

The most popular and active area of data mining study is sentiment analysis. Twitter is a crucial platform for collecting and distributing people's thoughts, feelings, views, and attitudes regarding specific entities. There are several social media networks available today. In light of this, sentiment analysis in natural language processing (NLP) field became fascinating. Different techniques have been developed for sentiment analysis. However, there is still a need for improvement in terms of accuracy and system effectiveness.

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A hybrid control algorithm, which combines channel selection and transmission power control for Sub-1GHz wireless sensor network systems, is proposed in this paper. By measuring and evaluating the status of candidate channels, the hybrid control algorithm can identify a channel with minimal interference for transmission. Moreover, by analyzing link quality estimators and employing a fuzzy controller, the system can adaptively adjust transmission power based on the surrounding environment of nodes. Unstable frequencies can be avoided through frequency hopping, either.

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This dataset presents a collection of real-world RF signals encompassing three prominent wireless communication technologies: Wi-Fi (IEEE 802.11ax), LTE, and 5G. The data aims to facilitate advanced research in spectrum analysis, interference identification, and wireless communication optimization. The signals were meticulously captured under varying conditions to ensure a broad representation of real-world scenarios, including different modulation schemes, channel conditions, and data rates.

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760 Views

5G Network slicing is one of the key enabling technologies that offer dedicated logical resources to different applications on the same physical network. However, a Denial-of-Service (DoS) or Distributed Denial-of-Service (DDoS) attack can severely damage the performance and functionality of network slices. Furthermore, recent DoS/DDoS attack detection techniques are based on the available data sets which are collected from simulated 5G networks rather than from 5G network slices.

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907 Views

This dataset contains adversarial attacks on Deep Learning (DL) when it is employed for the classification of wireless modulated communication signals. The attack is executed with an obfuscating waveform that is embedded in the transmitted signal in such a way that prevents the extraction of clean data for training from a wireless eavesdropper. At the same time it allows a legitimate receiver (LRx) to demodulate the data.

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This dataset contains adversarial attacks on Deep Learning (DL) when it is employed for the classification of
wireless modulated communication signals. The attack is executed with an obfuscating waveform that is embedded in the
transmitted signal in such a way that prevents the extraction of clean data for training from a wireless eavesdropper. At the
same time it allows a legitimate receiver (LRx) to demodulate the data. The scheme works for both single carrier and multi-carrier

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96 Views

In communication and networking research, obtaining large, real-world datasets related to the physical layer has always been challenging, especially in IoT and Health IoT. In particular, there is a significant interest in datasets that help characterize physical layer properties without interferences from any other communications signals.

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439 Views

Modern, industrial use cases for wireless communications are related to mobile applications such as moving robotics in industrial environments. For the design of communication systems, the behavior of the radio channel, especially over time, is of great importance. Most of the existing data sets for industrial radio channels originate from static measurement procedures, containing an arbitrary subset of the environment.

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351 Views

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