Wireless Networking
Mobility data collected by LifeMap monitoring system at Yonsei University in Seoul.
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351 Views
The BLEBeacon dataset is a collection of Bluetooth Low Energy (BLE) advertisement packets/traces generated from BLE beacons carried by people following their daily routine inside a university building for a whole month. A network of Raspberry Pi 3 (RPi)-based edge devices were deployed inside a multi-floor facility continuously gathering BLE advertisement packets and storing them in a cloud-based environment.
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251 Views
This dataset includes real-world time-series statistics from network traffic on real commercial LTE networks in Greece. The purpose of this dataset is to capture the QoS/QoE of three COTS UEs interacting with three edge applications. Specifically, the following features are included: Throughput and Jitter for each UE-Application and Channel Quality Indicator (CQI) for each UE. The interactions were generated from a realistic network behavior in an office by developing multiple network traffic scenarios.
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3068 Views
Dataset of mobility traces collected by Pocket Mobility Trace Recorder devices at University of Milano.
This dataset contains mobility traces from 44 mobile devices at University of Milano. The data was collected in November 2008.
date/time of measurement start: 2008-11-13
date/time of measurement end: 2008-12-01
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112 Views
Traces of Bluetooth encounters, Facebook friendships and interests of a set of users collected through SocialBlueConn application at University of Calabria
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149 Views
The Berlin V2X dataset offers high-resolution GPS-located wireless measurements across diverse urban environments in the city of Berlin for both cellular and sidelink radio access technologies, acquired with up to 4 cars over 3 days. The data enables thus a variety of different ML studies towards vehicle-to-anything (V2X) communication.
The data includes information on:
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4449 Views
We have created a Deep Learning model for 5G and Network Slicing. (eMBB, URLLC, IoT).
I encourage developers and researchers working on the 4G/LTE, 5G, 6G and similar interest to use and provide feedback:
Our research can be found at
1. IEEE paper "DeepSlice: A Deep Learning Approach towards an Efficient and Reliable Network Slicing in 5G Networks" (https://ieeexplore.ieee.org/document/8993066)
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1886 Views
Dataset of RSS measurements of a Mica2 sensor network deployed at the University of Michigan.
This is a dataset of RSS measurements collected by Mica2 sensor nodes deployed inside and outside a lab room, with anomaly patterns occurring when students walked into and out of the lab. A web camera recorded the activity that could be matched with detected anomalies.
date/time of measurement start: 2006-04-21
date/time of measurement end: 2006-04-21
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136 Views
The measurement results provided here are part of work on PhD thesis connected with measurement results variability reduction (main focus was on GSM/UMTS system. but other technologies were measured at the same time). All measurements were of indoor type. The duration of collecting data samples was 24h per day, with 10 seconds sampling interval. At some places it took one, two or four weeks to complete the measurements. Equipment used is the dosimeter (or exposimeter) EME Spy 140 (manufactured by Satimo).
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102 Views
Detailed link quality information was collected over several days from the UCSB MeshNet for characterizing routing stability in wireless mesh networks.
last modified : 2007-02-15
release date : 2007-02-01
date/time of measurement start : 2006-04-01
date/time of measurement end : 2006-04-07
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324 Views