Communications

In this paper, the security-aware robust resource allocation in energy harvesting cognitive radio networks is considered with cooperation between two transmitters while there are uncertainties in channel gains and battery energy value. To be specific, the primary access point harvests energy from the green resource and uses time switching protocol to send the energy and data towards the secondary access point (SAP).

The dataset corresponds the measurement that was implemented on the control accuracy of a mixed reality application for digital twin based crane. 

Some 6G use cases include augmented reality and high-fidelity holograms, with this information flowing through the network. Hence, it is expected that 6G systems can feed machine learning algorithms with such context information to optimize communication performance. This paper focuses on the simulation of 6G MIMO systems that rely on a 3-D representation of the environment as captured by cameras and eventually other sensors. We present new and improved Raymobtime datasets, which consist of paired MIMO channels and multimodal data.

The presented data contain recordings of underwater acoustic transmissions collected from a field experiment whose goal was to characterize self-interference for in-band full-duplex underwater acoustic communications. The experiment was conducted in the Lake of Tuscaloosa in July 2019. A single transmission-receiving line was deployed off a boat that was moored in the center of the lake. The transmission-receiving line had one acoustic transmitter and eight hydrophone receivers.