A Study on Nonlinearity in Mixers Using a Time-Varying Volterra-Based Distortion Contribution Analysis Tool
To optimize the linearity of mixers, one needs to recognize the origins and mixing mechanisms of dominant nonlinearities. This article presents a […]
An overview of approaches for reducing uncertainties in hydrological forecasting: Progress and challenges
Uncertainty plays a key role in hydrological modeling and forecasting, which can have tremendous environmental, economic, and social impacts. Therefore, it is […]
Intelligible Protocol Learning for Resource Allocation in 6G O-RAN Slicing
An adaptive standardized protocol is essential for addressing inter-slice resource contention and conflict in network slicing. Traditional protocol standardization is a cumbersome […]
Communication-Efficient Federated Deep Reinforcement Learning based Cooperative Edge Caching in Fog Radio Access Networks
In this paper, the cooperative edge caching problem is studied in fog radio access networks (F-RANs). Given the non-deterministic polynomial hard (NP-hard) […]
Robust EV Scheduling in Charging Stations Under Uncertain Demands and Deadlines
To enable widespread use of electric vehicles (EVs), large-scale public charging stations with fast chargers are being planned in places such as […]
A Multi-Task Oriented Semantic Communication Framework for Autonomous Vehicles
Task-oriented semantic communication is an emerging technology that transmits only the relevant semantics of a message instead of the whole message to […]
Switch-Based Hybrid Beamforming Transceiver Design for Wideband Communications With Beam Squint
Hybrid beamforming (HBF) transceiver architectures based on frequency-independent phase shifters (PSs) are sensitive to phases and physical directions, resulting in limited capability […]
SHIELD – Secure Aggregation against Poisoning in Hierarchical Federated Learning
Federated Learning (FL) is a privacy-preserving distributed Machine Learning (ML) technique. Hierarchical FL is a novel variant of FL applicable to networks […]
Progressively global–local fusion with explicit guidance for accurate and robust 3d hand pose reconstruction
Parametric and non-parametric methods are two commonly used strategies in current 3D hand pose reconstruction. Parametric methods predict low-dimensional parameters to fit […]
Separating Intrinsic and Extrinsic Responses of Whisker Sensors Using Accelerometer
Rodents and Felidae whiskers are highly sensitive, detecting extrinsic inputs like airflow or contact and intrinsic inputs such as base vibrations or […]