Wireless Networking
More than 85% of traffic utilization via mobile phones are consumed in the urban area, and most of the traffic is used for downloading. Improving the throughput in LTE for 1 user equipment (UE) in cities is an urgent problem. The collected data is intended to study a dependence of the KPI mobile base station and neighboring from installation extra technology. This study will support the development of methods for comparing traffic utilization of urban area and carry out recommendations for the Channel Quality Indicator (CQI) increases.
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505 Views
Dataset of radio characteristics of 802.15.4 mobile person-to-person communications.
The dataset contains results from a simple yet systematic set of benchmark experiments that offer a number of important insights into the radio characteristics of mobile 802.15.4 person-to-person communications.
date/time of measurement start: 2007-08-12
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261 Views
CenceMe is a sensing system based on standard and sensor-enabled mobile phones. CenceMe uses the output of the phones' sensors and external data (if such is available) to infer human presence and activity information. This dataset contains movements and inferred activities of participants using CenceMe on their mobile phones.
The CenceMeLite traces were collected from 2008-07-28 to 2008-08-11 by students and staff members at Dartmouth College.
last modified 2010-08-30
reason for most recent change the initial version
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212 Views
Bluetooth hci traces collected on smartphones (btsnoop)
This dataset consists of a collection of Bluetooth HCI traces captured on a smartphone while a smartphone and smart device communicated. 00_raw` contains the raw HCI traces (btsnoop files pulled from an Android smartphone) - each subfolder contains the traces captured during communication between a specific device and its companion smartphone app. `01_processed` contains CSV-formatted files, which are parsed versions of the raw Bluetooth traces. The first row of each file contains the column labels.
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332 Views
This is the dataset we collected for the article "Scalable Undersized Dataset RF Classification: Using Convolutional Multistage Training". 17 objects were collected in the laboratory and scanned using a 'cw radar' setup featuring 2x UWB antennas (1 transmit antenna, 1 receive antenna), inside anechoic chamber. There was no clutter added in the experiment.
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1384 Views
This dataset includes real-world Channel Quality Indicator (CQI) values from UEs connected to real commercial LTE networks in Greece. Channel Quality Indicator (CQI) is a metric posted by the UEs to the base station (BS). It is linked with the allocation of the UE’s modulation and coding schemes and ranges from 0 to 15 in values. This is from no to 64 QAM modulation, from zero to 0.93 code rate, from zero to 5.6 bits per symbol, from less than 1.25 to 20.31 SINR (dB) and from zero to 3840 Transport Block Size bits.
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1802 Views
To determine the effectiveness of any defense mechanism, there is a need for comprehensive real-time network data that solely references various attack scenarios based on older software versions or unprotected ports, and so on. This presented dataset has entire network data at the time of several cyber attacks to enable experimentation on challenges based on implementing defense mechanisms on a larger scale. For collecting the data, we captured the network traffic of configured virtual machines using Wireshark and tcpdump.
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2349 Views
室内环境设置为长、宽、高分别为21m、21m和3m。内部由九个房间组成，每个房间都有混凝土墙、天花板和地板，门窗分别由木板和玻璃制成。参考点和测试点的数量分别为324和361，用红色和黄色方块表示，房间内配备6个AP。
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149 Views
This paper investigates the finite-time formation control problem for high-order nonlinear multiagent systems (MASs) with consideration of obstacle avoidance, unmeasurable states and dead-zone input. A neural networks k-filter observer is designed to estimate the unmeasurable states and cope with the problem of dead-zone input. Also, by using a tangent type Lyapunov barrier function (LBF), the obstacle avoidance mission can be completed for MASs without dynamic mismatching.
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100 Views
Three synthetic and validated datasets correspond to three typical vehicular communication scenarios. Each subdataset comprises approximately 15000 to 28000 samples that are MAC observations in each CCHI of all vehicles in the network during the travel on the road segment of 2km. Each sample includes six most concerned features: number of successful received packets ls, number of failed transmission on the medium lc, number of error received packets le, number of packet transmitted by the given vehicle ltx, time step ti and estimated number of neighbor vehicles n.
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172 Views