Wireless Networking
Wireless Intelligence Channel (WIC) is a realistic channel data set, which is designed for deep learning research work in MIMO as well as other applications. The WIC data set is obtained directly through commercial BSs and a device capable of data acquisition that is similar to a commercial terminal. The scene selection and parameter configuration involved in the experiment are based on the characteristics of realistic scenarios and the existing configurations in commercial BSs, without assumptions and restrictions on the ideal experimental conditions.
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Here we provide the dataset containing the power measurements obtained with our RIS prototype, which were carried out in the anechoic chamber of TU Darmstadt.
The use of data here contained is intended only for research purposes.
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The dataset was collected by performing uplink/downlink throughput measurements in Munich, Germany. The user side device was a vehicle with roof-mounted antenna (approx. 1.5 m height), and on the network side was a base station antenna mounted at the top of a building (height of the antenna with respect to the ground: 21 m). The measurements were collected at the center frequency of 3.41 GHz, with 40 MHz of bandwidth, with antenna gain of 15.5dBi (5dBi) at the base station (vehicle) side. The maximum throughput in the uplink was 40 Mbps.
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200 hours of accelerometer information recorded over 25 days from 5 participants.
To help us better understand the properties of various energy sources and their impact on energy harvesting adaptive algorithms, we collected acceleration traces from different participants.
release date: 2014-05-13
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Dataset of radiant light energy measurements.
This dataset includes radiant light energy measurements from a study by Columbia University's EnHANTs (Energy Harvesting Active Networked Tags) project.
date/time of measurement start: 2009-08-14
date/time of measurement end: 2010-11-23
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Sensor network dataset for enhancing CSMA MAC protocol.
This dataset contains packet transmission traces collected from an experimental wireless sensor network testbed, where E(Enhanced)-CSMA MAC protocol is implemented using TinyOS on Mica2 motes.
date/time of measurement start: 2006-03-26
date/time of measurement end: 2006-04-08
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In this paper, we develop a hierarchical aerial computing framework composed of high altitude platform (HAP) and unmanned aerial vehicles (UAVs) to compute the fully offloaded tasks of terrestrial mobile users which are connected through an uplink non-orthogonal multiple access (UL-NOMA).
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