4 citations · 8 across the 7 of their papers we have counts for
9 papers
Reliable Extraction of Semantic Information and Rate of Innovation Estimation for Graph Signals
Mert Kalfa, Sadik Yagiz Yetim, Arda Atalik +6
Semantic signal processing and communications are poised to play a central part in developing the next generation of sensor devices and networks. A crucial component of a semantic…
On the Rate-Distortion-Perception Function
Jun Chen, Lei Yu, Jia Wang +3
Rate-distortion-perception theory generalizes Shannon's rate-distortion theory by introducing a constraint on the perceptual quality of the output. The perception constraint comple…
Distributed Learning for Time-varying Networks: A Scalable Design
Jian Wang, Yourui Huangfu, Rong Li +2
The wireless network is undergoing a trend from "onnection of things" to "connection of intelligence". With data spread over the communication networks and computing capability enh…
Smart Scheduling based on Deep Reinforcement Learning for Cellular Networks
Jian Wang, Chen Xu, Rong Li +2
To improve the system performance towards the Shannon limit, advanced radio resource management mechanisms play a fundamental role. In particular, scheduling should receive much at…
Buffer-aware Wireless Scheduling based on Deep Reinforcement Learning
Chen Xu, Jian Wang, Tianhang Yu +5
In this paper, the downlink packet scheduling problem for cellular networks is modeled, which jointly optimizes throughput, fairness and packet drop rate. Two genie-aided heuristic…
Realistic Channel Models Pre-training
Yourui Huangfu, Jian Wang, Chen Xu +5
In this paper, we propose a neural-network-based realistic channel model with both the similar accuracy as deterministic channel models and uniformity as stochastic channel models.…