Communications

This dataset has been used to evaluate different consistent hashing algorithms for non-peer-to-peer contexts. Further information can be found at https://github.com/SUPSI-DTI-ISIN/java-consistent-hashing-algorithms

This article presents the details of the Cardinal RF (CardRF) dataset. CardRF is acquired to foster research in RF- based UAV detection and identification or RF fingerprinting. RF signals were collected from UAV controllers, UAV, Bluetooth, and Wi-Fi devices. Signals are collected at both visual line-of-sight and beyond-line-of-sight. The assumptions and procedure for the data acquisition are presented. A detailed explanation of how the data can be utilized is discussed. CardRF is over 65 GB in storage memory.

5G-NR is beginning to be widely deployed in the mmWave frequencies in urban areas in the US and around the world. Due to the directional nature of mmWave signal propagation, improving performance of such deployments heavily relies on beam management and deployment configurations.

This data provides realized gain values for a handset operating at 28 GHz, with 3 4x1 linear antenna arrays placed around the handset along the right edge, bottom edge and back face of the handset. Beam steering was carried out at each of these antenna arrays and results for the handset with and without the hand phantom are included to show the effect that the introduction of the hand phantom has on the realized gain of the handset.