Wireless Networking

In situations when the precise position of a machine is unknown, localization becomes crucial. It is crucial to identify and ascertain the machine's position. This research focuses on improving the position prediction accuracy over long-range networks using a unique machine learning-based technique. In order to increase the prediction accuracy of the reference point position on the data collected using the fingerprinting approach using LoRa technology, this study suggested an ML-based algorithm.

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In this paper a novel technique for modelling a radio frequency (RF) environment based on hypergraph theory is investigated for solving coexistence management of heterogeneous networks and efficient channel allocation for spectrum sharing. Conventionally, traditional graph theory is used to model interference relationships and exclusive channel allocation. The demand for wireless services is increasing, hence the need for efficient spectrum management techniques, such as spectrum sharing among coexistent networks.

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59 Views

JavaScript Object Notation (JSON) and eXtensible Markup Language (XML) are two data serialisation methods that have been compared over many applications including client-server transmission, internet communication, and large-scale data storage. Due to the smaller file size, JSON is faster for transmitting data. However, XML is better for sending complex data structures. This dataport contains C code project to compare performance of XML with JSON, considering factors such as time, memory, and power to identify efficient characteristics of each method. 

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33 Views

Recently, a novel method was proposed to estimate the distance between a couple of wireless transceivers and a reflecting obstacle by analyzing the frequency dependence of the RSS. Although the resolution of this method is rather coarse for typical 2.4 GHz systems, a traffic monitoring system based on that novel approach has been successfully evaluated

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The dataset is the experimental output of a 5G New Radio (NR) coverage expansion use case in the context of the NANCY project (https://nancy-project.eu/). Two experimental scenarios were carried out, namely a) a scenario where a user equipment (UE) is directly connected to a Base Station (BS) through a 5G NR link, and b) a scenario where an intermediate node is employed, which acts as a relay between the base station and the UE. To this end, two 5G BSs were deployed, using Ettus Research USRP B210 devices.

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449 Views

The Army Cyber Institute (ACI) Internet of Things (IoT) Network Traffic Dataset 2023 (ACI-IoT-2023) is a novel dataset tailored for machine learning (ML) applications in the realm of IoT network security. This effort focuses on delivering a distinctive and realistic dataset designed to train and evaluate ML models for IoT network environments. By addressing a gap in existing resources, this dataset aims to propel advancements in ML-based solutions, ultimately fortifying the security of IoT operations.

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1877 Views

This Dataset provides input data for the development of the B-RAN and attacks models for the NANCY framework,to model training and model inference functions. The data collected plays the role of ML algorithm-specific data preparation. The dataset contains time-series, collected transmitting a video content through the Italtel "VTU - video streaming and transcoding application", that can convert audio and video streams from one format to another, at multiple encodings schemes, changing resolution, bitrate, and video parameters.

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177 Views

The dataset Provides S-parameter measurements of an AI enhanced wireless power transfer system using two ISO/ICE 14443-1 Coils with series capacitance compensation at 13.56 MHz under three configurations of vertical and horizontal misalignment, inter-coil distance, and azimuthal tilt. The structure and components of the system is shown in the Image attached to the Dataset This measured data validates the implementation of the system at the three coil configurations discussed in the publication.

 

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121 Views

Location awareness is vital in next generation (xG) wireless networks to enable different use cases, including location-based services (LBSs) and efficient network management. However, achieving the service level requirements specified by the 3rd Generation Partnership Project (3GPP) is challenging.

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830 Views
Recent advances in Wi-Fi sensing have ushered in a plethora of pervasive applications in home surveillance, remote healthcare, road safety, and home entertainment, among others. Most of the existing works are limited to the activity classification of a single human subject at a given time. Conversely, a more realistic scenario is to achieve simultaneous, multi-subject activity classification. The first key challenge in that context is that the number of classes grows exponentially with the number of subjects and activities.
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