Communications

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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564 Views

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).
The scenarios took place in three rooms with different sizes and inteference levels. For the experimentation, the equipment utilized consisted of Raspberry Pi 3 Model Bs, Gimbal Series 10 Beacons, and Series 2 Xbees with Arduino Uno microcontrollers.
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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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This work develops a novel power control framework for energy-efficient powercontrol in wireless networks. The proposed method is a new branch-and-boundprocedure based on problem-specific bounds for energy-efficiency maximizationthat allow for faster convergence. This enables to find the global solution forall of the most common energy-efficient power control problems with acomplexity that, although still exponential in the number of variables, is muchlower than other available global optimization frameworks.

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This file contains the experimental results for the research paper "Optimization-Based Offloading and Routing Strategies for Sensor-Enabled Video Surveillance Networks". Just open the excel file! then you can view the data.

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This dataset is associated with the paper entitled "DeepWiPHY: Deep Learning-based Receiver Design and Dataset for IEEE 802.11ax Systems", accepted by IEEE Transactions on Wireless Communications. It has synthetic and real-word IEEE 802.11ax OFDM symbols. The synthetic dataset has around 110 million OFDM symbols and the real-world dataset has more than 14 million OFDM symbols. Our comprehensive synthetic dataset has specifically considered typical indoor channel models and RF impairments. The real-world dataset was collected under a wide range of signal-to-noise ratio (SNR) levels and at va

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1850 Views

This is source code for the paper "Analog Self-Interference Cancellation Using Auxiliary Transmitter Considering IQ Imbalance and Amplifier Nonlinearity" submitted to IEEE Transactions on Wireless Communications.

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