6G Vision, Value, Use Cases and Technologies From European 6G Flagship Project Hexa-X
While 5G is being deployed and the economy and society begin to reap the associated benefits, the research and development community starts […]
Minimizing Average On-Demand AoI in an IoT Network with Energy Harvesting Sensors
Delivering timely status information of a random process has become increasingly important for time-sensitive applications, e.g., vehicle tracking and environment monitoring. We […]
On the UWB WBAN Radio Channel Research
In this paper, radio signal propagation characteristics for ultra wideband (UWB) signal is discussed in a wireless body area network (WBAN) context. […]
ETSI SmartBAN in Medical IoT
In this paper, we are briefly discussing on the ETSI SmartBAN standard and its utilization in medical Internet of Things (mIoT) applications. […]
Massive Machine-Type Communication and Satellite Integration for Remote Areas
Despite immense progress along different tracks, wireless connectivity for machine applications in remote areas is still very challenging. To address this vital […]
LPWAN Coverage Assessment Planning without Explicit Knowledge of Base Station Locations
An assessment of radio network coverage, usually in the form of a measurement campaign, is essential for multi-base-station (multi-BS) network deployment and […]
Understanding UAV-Based WPCN-Aided Capabilities for Offshore Monitoring Applications
Despite the immense progress in recent years, efficient solutions for monitoring remote areas are still missing today. This is especially notable in […]
Hiding in the Crowd
To cope with the lack of on-device machine learning samples, this article presents a distributed data augmentation algorithm, coined federated data augmentation […]
Accuracy Assessment and Cross-Validation of LPWAN Propagation Models in Urban Scenarios
With the proliferation of machine-to-machine (M2M) communication in the course of the last decade, the importance of low-power wide-area network (LPWAN) technologies […]
Proxy Experience Replay
Traditional distributed deep reinforcement learning (RL) commonly relies on exchanging the experience replay memory (RM) of each agent. Since the RM contains […]