Communications
Supplementary material for the paper: 'Adaptive Block Compressive Imaging: towards a real-time and low complexity implementation'
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2D geometrically shaped constellations that are simultaneously robust to both residual phase noise and AWGN (GS-RPN) for 8, 16, 32 and 64-ary formats. The presented formats are optimised at the generalised mutual information (GMI) threshold of 0.96m bits/symbol, where m is the number of bits per symbol. Additionally, we added AWGN-only constellations (GS-AWGN) to serve as a reference.
Note: This is a supplementary dataset for a journal submission.
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This MATLAB dataset (.mat) contains the collected real measurement data from a total of 470 access points (APs) deployed in the Linnanmaa campus of the University of Oulu, Finland. The measurements include IDs, dates of data collection, number of users, received traffic data, transmitted traffic data and location names of each AP. Each observation of traffic data and number of users provide the data value at every 10-minute interval between December 18, 2018 and February 12, 2019. Please cite this as: S. P. Sone & Janne Lehtomäki & Zaheer Khan.
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Including the symbol under demodulation in data-aided reference/pilot recovery process, dominates the contribution of all the received sybmols. Therefore, excluding the contribution of the symbol under detection allows other symbols to equally contributeto the reference estimation.
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Learning To Simulate Asymmetric Encryption With Adversarial Neural Networks
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Digital signature is an encryption mechanism used to verify the authenticity and integrity of message, which has higher complexity and security than traditional handwritten signature. However, the two main challenges of digital signature are security and computing speed. It then imposes a problem - how to quickly verify and sign digital signatures under the premise of ensuring security.
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Drive test measurements of deployed LTE base stations located at and around the campus of The Technical Unversity of Denmark. Metrics of signal quality are obtained using TSMW equipment with a vehicle driving around the area. In addition to the radio measurements, a GNSS receiver is utilized for additional localization metrics. Approximate altitude information is provided by the GNSS.
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Visible Light Positioning is an indoor localization technology that uses wireless transmission of visible light signals to obtain a location estimate of a mobile receiver.
This dataset can be used to validate supervised machine learning approaches in the context of Received Signal Strength Based Visible Light Positioning.
The set is acquired in an experimental setup that consists of 4 LED transmitter beacons and a photodiode as receiving element that can move in 2D.
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This RSSI Dataset is a comprehensive set of Received Signal Strength Indicator (RSSI) readings gathered from three different types of scenarios. Three wireless technologies were used which consisted of:
- Zigbee (IEEE 802.15.4),
- Bluetooth Low Energy (BLE), and
- WiFi (IEEE 802.11n 2.4GHz band).
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Encoding and decoding tables for 6b8b encoder/decoder for sefl-syncrhonized improved RMII protocol. Proposed encoder/decoder garantee that 2-bit TXD/RXD will change each data transmission cycle, making it possible for RMII interface to work without REF_CLK, TX_EN and CRS_DV lines.
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