Wireless Networking

The TiHAN-V2X Dataset was collected in Hyderabad, India, across various Vehicle-to-Everything (V2X) communication types, including Vehicle-to-Vehicle (V2V), Vehicle-to-Infrastructure (V2I), Infrastructure-to-Vehicle (I2V), and Vehicle-to-Cloud (V2C). The dataset offers comprehensive data for evaluating communication performance under different environmental and road conditions, including urban, rural, and highway scenarios.

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The Unified Multimodal Network Intrusion Detection System (UM-NIDS) dataset is a comprehensive, standardized dataset that integrates network flow data, packet payload information, and contextual features, making it highly suitable for machine learning-based intrusion detection models. This dataset addresses key limitations in existing NIDS datasets, such as inconsistent feature sets and the lack of payload or time-window-based contextual features.

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The dataset consists of uplink channel gains, downlink channel gains and uplink to downlink channel gains along with corresponding power allocations for uplink users and downlink users across all subcarriers. Additionally, it consists of NOMA decoding order for successful implementation of SIC at NOMA receiver. The number of UL users and DL users are considered as N=M=6, and subcarriers are S=9. Each column in the dataset is a sample for fading channel realization and it should be converted back to the matrix to compute sumrate.

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A modern Wi-Fi-enabled device (e.g., a smartphone) can spontaneously emit unencrypted and anonymized signals to the environment in search of an access point. This signal is called a probe request. Since it is freely available in the open air, one can build a sensor from a Wi-Fi adapter to capture the signal. Once captured, its signal strength can be measured in the form of a Received Signal Strength Indicator (RSSI).

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This dataset was developed in the context of the NANCY project and it is the output of the experiments involving streaming a virtual reality (VR) video in a 5G coverage expansion scenario. Additionally, iPerf3 experiments in both TCP and UDP modes were carried out. The coverage expansion scenario involves a main operator and a micro-operator which extends the main operator’s coverage and can also provide additional services.

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This dataset was developed in the context of the NANCY project and it is the output of the experiments involving cyberattacks against services that are running in a 5G coverage expansion scenario. The coverage expansion scenario involves a main operator and a micro-operator which extends the main operator’s coverage and can also provide additional services, such as Artificial Intelligence-based cyberattack detection.

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316 Views

This dataset contains LoRa physical layer signals collected from 60 LoRa devices and six SDRs (PLUTO-SDR, USRP B200 mini, USRP B210, USRP N210, RTL-SDR). It is intended for use by researchers in the development of a federated RFFI system, whereby the signals collected from different receivers and locations can be employed for evaluation purposes.

More details can be found at https://github.com/gxhen/federatedRFFI

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659 Views

We conducted a massive MIMO channel measurement and uplink multi-user data transmission experiment in an indoor setting on the Rice University campus. The original purpose of this dataset was to study the effect of placement of massive MIMO BS arrays on performance in two scenarios of co-located and separated (distributed) as well as the effect of phase coherence among the arrays during channel measurement and data transmission. Use the link to access the datasets.

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293 Views

This dataset has been measured from the User Equipment (UE) using an Automated Guided Vehicle (AGV). The collected metrics include the radio information measured by the modem, and the localization information obtained from the AGV's navigation system based on LiDAR technology.

The AGV is configured to follow a loop movement from the south to the north of the laboratory at 1 m/s speed. The BTS is a commercial cell publicly available on mmWave, but no external users were connected to mmWave during the experiments.

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This dataset presents real-world VPN encrypted traffic flows captured from five applications that belong to four service categories, which reflect typical usage patterns encountered by everyday users. 

Our methodology utilized a set of automatic scripts to simulate real-world user interactions for these applications, to achieve a low level of noise and irrelevant network traffic.

 

The dataset consists of flow data collected from four service categories:

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