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Found 11 papers, 0 papers with code
Rendering Wireless Environments Useful for Gradient Estimators: A Zero-Order Stochastic Federated Learning Method
By utilizing a communication-efficient framework, we propose a novel zero-order (ZO) method with a one-point gradient estimator that harnesses the nature of the wireless communication channel without requiring the knowledge of the channel state coefficient.
Zero-Order One-Point Estimate with Distributed Stochastic Gradient-Tracking Technique
We analyze the convergence of this novel technique for smooth and convex objectives using stochastic approximation tools, and we prove that it converges almost surely to the optimum.
Real-Time Massive MIMO Channel Prediction: A Combination of Deep Learning and NeuralProphet
Channel state information (CSI) is of pivotal importance as it enables wireless systems to adapt transmission parameters more accurately, thus improving the system's overall performance.
Artificial Intelligence for 6G Networks: Technology Advancement and Standardization
With the deployment of 5G networks, standards organizations have started working on the design phase for sixth-generation (6G) networks.
A Novel Algorithm to Report CSI in MIMO-Based Wireless Networks
Besides, in the immobile radio channel, feedback can be eliminated, which brings the benefit of further reducing the OTA overhead.
Dealing with CSI Compression to Reduce Losses and Overhead: An Artificial Intelligence Approach
The proposed scheme enhances the CSI compression, which is done at the mobile terminal (MT), along with accurate recovery of estimated CSI at the BS.
Semantic Communications in Networked Systems: A Data Significance Perspective
We present our vision for a departure from the established way of architecting and assessing communication networks, by incorporating the semantics of information for communications and control in networked systems.
On the Global Optimality of Whittle's index policy for minimizing the age of information
This paper examines the average age minimization problem where only a fraction of the network users can transmit simultaneously over unreliable channels.
Information Theory Networking and Internet Architecture Information Theory
The Age of Incorrect Information: an Enabler of Semantics-Empowered Communication
Interestingly, we show that the AoII-optimal policy is also error-optimal for the adopted information source model.
Information Theory Information Theory
Distributed Power Control for Large Energy Harvesting Networks: A Multi-Agent Deep Reinforcement Learning Approach
In the proposed framework, we model the online power control problem as a discrete-time mean-field game (MFG), and analytically show that the MFG has a unique stationary solution.
Multi-agent Reinforcement Learning
reinforcement-learning
+1
Deep Learning Based Online Power Control for Large Energy Harvesting Networks
In this paper, we propose a deep learning based approach to design online power control policies for large EH networks, which are often intractable stochastic control problems.
