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Found 6 papers, 2 papers with code
A Low-Complexity Machine Learning Design for mmWave Beam Prediction
The 3rd Generation Partnership Project (3GPP) is currently studying machine learning (ML) for the fifth generation (5G)-Advanced New Radio (NR) air interface, where spatial and temporal-domain beam prediction are important use cases.
Berlin V2X: A Machine Learning Dataset from Multiple Vehicles and Radio Access Technologies
The evolution of wireless communications into 6G and beyond is expected to rely on new machine learning (ML)-based capabilities.
Toward an AI-enabled Connected Industry: AGV Communication and Sensor Measurement Datasets
This paper presents two wireless measurement campaigns in industrial testbeds: industrial Vehicle-to-vehicle (iV2V) and industrial Vehicle-to-infrastructure plus Sensor (iV2I+), together with detailed information about the two captured datasets.
A Comprehensive Survey of Spectrum Sharing Schemes from a Standardization and Implementation Perspective
As the services and requirements of next-generation wireless networks become increasingly diversified, it is estimated that the current frequency bands of mobile network operators (MNOs) will be unable to cope with the immensity of anticipated demands.
AoI-Aware Resource Allocation for Platoon-Based C-V2X Networks via Multi-Agent Multi-Task Reinforcement Learning
Hence, we exploit a distributed resource allocation framework based on multi-agent reinforcement learning (MARL), where each platoon leader (PL) acts as an agent and interacts with the environment to learn its optimal policy.
A Unified Framework for Joint Energy and AoI Optimization via Deep Reinforcement Learning for NOMA MEC-based Networks
To further improve the system capacity, non-orthogonal multiple access (NOMA) is proposed as a candidate for multiple access schemes for future cellular networks.
Signal Processing
