Wireless Networking
The capabilities of the millimeter wave (mmWave) spectrum to fulfill the ultra high data rate demands of V2X (Vehicle-to-Everything) communications necessitates the need for accurate channel modeling to facilitate the efficient development of next-generation network and device design strategies. Ergo, this work describes the design of a novel fully autonomous robotic beam-steering platform, equipped with a custom broadband sliding correlator channel sounder, for 28GHz V2X propagation modeling activities on the NSF POWDER experimental testbed.
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299 Views
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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697 Views
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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84 Views
The accuracy of temperature & humidity prediction directly affects indoor environmental control, and current predictions mainly focus on time modeling, lacking spatiotemporal modeling based prediction for distributed sensors installed in buildings. Therefore, this article proposes an indoor temperature and humidity prediction method based on spatiotemporal modeling and transfer learning of informer. A IOT platform is designed with 8 temperature & humidity integrated sensors in a public building.
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48 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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64 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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173 Views
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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727 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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5764 Views
Abstract—This paper proposes an enhanced scheme for a traditional phase-locked loop (PLL) frequency synthesizer based on the integration of self-injected locking and in-loop mixing (SIL-MIX) techniques. This approach significantly reduces the overall phase noise of the conventional PLL frequency synthesizer. Additionally, the integration of a programmable phase shifter on the system provides a novel perspective for the on-board implementation of frequency synthesizers.
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24 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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254 Views