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Found 13 papers, 2 papers with code
Effective Communication with Dynamic Feature Compression
The remote wireless control of industrial systems is one of the major use cases for 5G and beyond systems: in these cases, the massive amounts of sensory information that need to be shared over the wireless medium may overload even high-capacity connections.
Push- and Pull-based Effective Communication in Cyber-Physical Systems
In Cyber Physical Systems (CPSs), two groups of actors interact toward the maximization of system performance: the sensors, observing and disseminating the system state, and the actuators, performing physical decisions based on the received information.
Accurate Calibration of Power Measurements from Internal Power Sensors on NVIDIA Jetson Devices
Power efficiency is a crucial consideration for embedded systems design, particularly in the field of edge computing and IoT devices.
Fast Context Adaptation in Cost-Aware Continual Learning
This creates friction: on the one hand, the learning process needs resources to quickly convergence to an effective strategy; on the other hand, the learning process needs to be efficient, i. e., take as few resources as possible from the user's data plane, so as not to throttle users' QoS.
Multi-Agent Reinforcement Learning for Pragmatic Communication and Control
In this work, we propose a joint design that combines goal-oriented communication and networked control into a single optimization model, an extension of a multiagent POMDP which we call Cyber-Physical POMDP (CP-POMDP).
Multi-agent Reinforcement Learning
reinforcement-learning
+1
Semantic and Effective Communication for Remote Control Tasks with Dynamic Feature Compression
The coordination of robotic swarms and the remote wireless control of industrial systems are among the major use cases for 5G and beyond systems: in these cases, the massive amounts of sensory information that needs to be shared over the wireless medium can overload even high-capacity connections.
The Cost of Learning: Efficiency vs. Efficacy of Learning-Based RRM for 6G
This creates a friction between the need to speed up convergence towards an effective strategy, which requires the allocation of resources to transmit learning samples, and the need to maximize the amount of resources used for data plane communication, maximizing users' Quality of Service (QoS), which requires the learning process to be efficient, i. e., minimize its overhead.
Energy Consumption of Neural Networks on NVIDIA Edge Boards: an Empirical Model
At the intersection of these trends, we hence find the energetic characterization of machine learning at the edge, which is attracting increasing attention.
User Clustering for Rate Splitting using Machine Learning
Hierarchical Rate Splitting (HRS) schemes proposed in recent years have shown to provide significant improvements in exploiting spatial diversity in wireless networks and provide high throughput for all users while minimising interference among them.
Point Cloud Compression for Efficient Data Broadcasting: A Performance Comparison
The worldwide commercialization of fifth generation (5G) wireless networks and the exciting possibilities offered by connected and autonomous vehicles (CAVs) are pushing toward the deployment of heterogeneous sensors for tracking dynamic objects in the automotive environment.
Energy-Efficient Design for RIS-assisted UAVcommunications in beyond-5G Networks
The usage of Reconfigurable Intelligent Surfaces (RIS) in conjunction with Unmanned Ariel Vehicles (UAVs) is being investigated as a way to provide energy-efficient communication to ground users in dense urban areas.
Distributed Reinforcement Learning for Flexible and Efficient UAV Swarm Control
The proposed framework relies on the possibility for the UAVs to exchange some information through a communication channel, in order to achieve context-awareness and implicitly coordinate the swarm's actions.
Feature selection for gesture recognition in Internet-of-Things for healthcare
Internet of Things is rapidly spreading across several fields, including healthcare, posing relevant questions related to communication capabilities, energy efficiency and sensors unobtrusiveness.
