Design and analysis of SWIPT with safety constraints
Simultaneous wireless information and power transfer (SWIPT) has long been proposed as
a key solution for charging and communicating with low-cost and low-power devices …
a key solution for charging and communicating with low-cost and low-power devices …
Probabilistic Constrained Optimization for Predictive Video Streaming by Deep Learning
This paper optimizes predictive power allocation to minimize the average transmit power for
video streaming subject to the constraint on stalling time, one of the most important factors …
video streaming subject to the constraint on stalling time, one of the most important factors …
Towards fidelity of graph data augmentation via equivariance
Graph data augmentation is widely used in machine learning, and when serving the
underlying model, it is necessary to ensure that the feature–graph–label tuples are …
underlying model, it is necessary to ensure that the feature–graph–label tuples are …
Deep Learning-based Joint Channel Prediction and Multibeam Precoding for LEO Satellite Internet of Things
Low earth orbit (LEO) satellite internet of things (IoT) is a promising way achieving global
Internet of Everything, and thus has been widely recognized as an important component of …
Internet of Everything, and thus has been widely recognized as an important component of …
A Data and Model-Driven Deep Learning Approach to Robust Downlink Beamforming Optimization
This paper investigates the optimization of the long-standing probabilistically robust transmit
beamforming problem with channel uncertainties in the multiuser multiple-input single …
beamforming problem with channel uncertainties in the multiuser multiple-input single …