2 citations · 6 across the 6 of their papers we have counts for
10 papers
Size Generalization for Resource Allocation with Graph Neural Networks
Wu Jiajun, Sun Chengjian, Yang Chenyang
Size generalization is important for learning wireless policies, which are often with dynamic sizes, say caused by time-varying number of users. Recent works of learning to optimiz…
Privacy Leakage in Proactive VR Streaming: Modeling and Tradeoff
Xing Wei, Chenyang Yang, Chengjian Sun
Proactive tile-based virtual reality (VR) video streaming employs the viewpoint of a user to predict the tiles to be requested, renders and delivers the predicted tiles before play…
A Tutorial on Ultra-Reliable and Low-Latency Communications in 6G: Integrating Domain Knowledge into Deep Learning
Changyang She, Chengjian Sun, Zhouyou Gu +4
As one of the key communication scenarios in the 5th and also the 6th generation (6G) of mobile communication networks, ultra-reliable and low-latency communications (URLLC) will b…
Unsupervised Deep Learning for Optimizing Wireless Systems with Instantaneous and Statistic Constraints
Chengjian Sun, Changyang She, Chenyang Yang
Deep neural networks (DNNs) have been introduced for designing wireless policies by approximating the mappings from environmental parameters to solutions of optimization problems.…
Optimizing Wireless Systems Using Unsupervised and Reinforced-Unsupervised Deep Learning
Dong Liu, Chengjian Sun, Chenyang Yang +1
Resource allocation and transceivers in wireless networks are usually designed by solving optimization problems subject to specific constraints, which can be formulated as variable…
Proactive Optimization with Machine Learning: Femto-caching with Future Content Popularity
Jiajun Wu, Chengjian Sun, Chenyang Yang
Optimizing resource allocation with predicted information has shown promising gain in boosting network performance and improving user experience. Earlier research efforts focus on…