Communications

The frequency domain measurement of the scattering parameter, S21, of the wireless channel was carried out using the ZVB14 Vector Network Analyzer (VNA) from Rhode and Schwartz. The measurement system consists of the VNA, low loss RF cables, and omnidirectional antennas at the transmitter and receiver ends. The transmitter and receiver heights were fixed at 1.5 m. A program script was written for the VNA to measure 10 consecutive sweeps: each sweep contains 601 frequency sample points with spacing of 0.167 MHz to cover a 100 MHz band centered at 2.4 GHz.
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For reproducibility purposes, a large test bench of fiber links is simulated to test the Baseband Subcarrier Sweep framework and associated monitoring techniques. The test bench comprises three sets of 1000 fiber links each containing one, two, or three faults.
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This dataset includes the Channels Switch Sequences of 300 IPTV viewers in Guangzhou, P.R. China, in Augest, 2014. There are 4 columns in the file, which represent viewer ID, the current channel number, the next channel number, the date of the month, respectively. The first column, the ID code of a viewer, ranks in descent with the times the viewer watched tv channels. The more times a viewer watches tv channels, the bigger the ID is. In a day, the rows are time series and generated step by step as the real watching tv behavior.
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This dataset includes the Channels Switch Sequences of 300 IPTV viewers in Guangzhou, P.R. China, in Augest, 2014.
There are 4 columns in the file, which represent viewer ID, the current channel number, th next channel number, the date of the month, respectively.
The first column, the ID code of a viewter, ranks with the times the viewer watched tv channels. The more times a viewer watches tv channels, the bigger
the ID is. In a day, the rows are time series and generated step by step as the real watching tv behavior.
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The system obtained interference information from the measurement signal, solved the problem of phase wrapping, and got the accurate coordinates of target. The tags and tag-free items including shrimp chips, cola and instant noodles were taken as target respectively in experiment.
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The software industry is a very flexible phenomenon. Adding network concepts to this industry means we have countless actors with different roles on a single ground. Its players include software developers, customers, users, and software components. The purpose of this article is to create a better way to communicate between these actors.We can imagine software engineering different and more effective than the current situation.
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RSSI-Dataset
The RSSI-Dataset provides a comprehensive set of Received Signal Strength Indication (RSSI) readings from within two indoor office buildings. Four wireless technologies were used:
- Zigbee (IEEE 802.15.4),
- WiFi (IEEE 802. 11),
- Bluetooth Low Energy (BLE) and
- Long Range Area-Wide Network (LoRaWAN).
For experimentation Arduinos Raspberry Pi, XBees, Gimbal beacons Series 10 and Dragino LoRa Shield were also used.
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Expansion of wireless body area networks (WBANs) applications such as health-care, m-banking, and others has lead to vulnerability of privacy and personal data. An effective and unobtrusive natural method of authentication is therefore a necessity in such applications. Accelerometer-based gait recognition has become an attractive solution, however, continuous sampling of accelerometer data reduces the battery life of wearables. This paper investigates the usage of received signal strength indicator (RSSI) as a source of gait recognition.
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