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Found 18 papers, 1 papers with code
The Roles of Generative Artificial Intelligence in Internet of Electric Vehicles
With the advancements of generative artificial intelligence (GenAI) models, their capabilities are expanding significantly beyond content generation and the models are increasingly being used across diverse applications.
Online Optimization for Learning to Communicate over Time-Correlated Channels
To provide theoretical guarantees for learning-based communication systems, some recent works analyze generalization bounds for devised methods based on the assumption of Independently and Identically Distributed (I. I. D.)
Dynamic Cooperative MAC Optimization in RSU-Enhanced VANETs: A Distributed Approach
We propose the RSU Probing and Cooperative Access (RPCA) strategy, a two-stage approach based on dynamic inter-vehicle distances from the RSU.
Goal-Oriented Communication, Estimation, and Control over Bidirectional Wireless Links
This status information, such as dynamic plant state and Markov Process-based context information, is then received/estimated by the controller for remote control.
V2X Cooperative Perception for Autonomous Driving: Recent Advances and Challenges
Achieving fully autonomous driving with heightened safety and efficiency depends on vehicle-to-everything (V2X) cooperative perception (CP), which allows vehicles to share perception data, thereby enhancing situational awareness and overcoming the limitations of the sensing ability of individual vehicles.
Integrated Monostatic and Bistatic mmWave Sensing
Millimeter-wave (mmWave) signals provide attractive opportunities for sensing due to their inherent geometrical connections to physical propagation channels.
Semantic Information Marketing in The Metaverse: A Learning-Based Contract Theory Framework
Furthermore, the proposed learning-based iterative contract framework has limited access to the private information of the participants, which is to the best of our knowledge, the first of its kind in addressing the problem of adverse selection in incentive mechanisms.
Deep Learning-Based Channel Estimation for Double-RIS Aided Massive MIMO System
Reconfigurable Intelligent Surface (RIS) is considered as an energy-efficient solution for future wireless communication networks due to its fast and low-cost configuration.
AirFi: Empowering WiFi-based Passive Human Gesture Recognition to Unseen Environment via Domain Generalization
The AirFi is a novel domain generalization framework that learns the critical part of CSI regardless of different environments and generalizes the model to unseen scenarios, which does not require collecting any data for adaptation to the new environment.
SenseFi: A Library and Benchmark on Deep-Learning-Empowered WiFi Human Sensing
WiFi sensing has been evolving rapidly in recent years.
Optimization for Master-UAV-powered Auxiliary-Aerial-IRS-assisted IoT Networks: An Option-based Multi-agent Hierarchical Deep Reinforcement Learning Approach
This paper investigates a master unmanned aerial vehicle (MUAV)-powered Internet of Things (IoT) network, in which we propose using a rechargeable auxiliary UAV (AUAV) equipped with an intelligent reflecting surface (IRS) to enhance the communication signals from the MUAV and also leverage the MUAV as a recharging power source.
Toward UL-DL Rate Balancing: Joint Resource Allocation and Hybrid-Mode Multiple Access for UAV-BS Assisted Communication Systems
To the best of our knowledge, this is the first work to explicitly investigate joint UL-DL optimization for UAV assisted systems under heterogeneous requirements.
Adapting to Dynamic LEO-B5G Systems: Meta-Critic Learning Based Efficient Resource Scheduling
Low earth orbit (LEO) satellite-assisted communications have been considered as one of key elements in beyond 5G systems to provide wide coverage and cost-efficient data services.
Economics of Semantic Communication System in Wireless Powered Internet of Things
The semantic communication system enables wireless devices to communicate effectively with the semantic meaning of the data.
A Comprehensive Survey of 6G Wireless Communications
First, we give an overview of 6G from perspectives of technologies, security and privacy, and applications.
Privacy-Preserving Federated Learning for UAV-Enabled Networks: Learning-Based Joint Scheduling and Resource Management
However, due to the privacy concerns of devices and limited computation or communication resource of UAVs, it is impractical to send raw data of devices to UAV servers for model training.
Energy Minimization in UAV-Aided Networks: Actor-Critic Learning for Constrained Scheduling Optimization
The conventional RL/DRL, e. g., deep Q-learning, however, is limited in dealing with two main issues in constrained combinatorial optimization, i. e., exponentially increasing action space and infeasible actions.
Federated Orchestration for Network Slicing of Bandwidth and Computational Resource
Motivated by the observation that coordination synchronization may result in high coordination delay that can be intolerable when the network is large in scale, we propose a novel asynchronized ADMM algorithm.
Signal Processing Networking and Internet Architecture
