Intelligent Communication
8 papers with code • 0 benchmarks • 5 datasets
Intelligently decide (i) the content of data to be shared/communicated and (ii) the direction in which the chosen data is transmitted.
Benchmarks
These leaderboards are used to track progress in Intelligent Communication
dichasus-cf0x
SPAVE-28G
Berlin V2X
iV2V and iV2I+
MVX
Most implemented papers
Scaling Language Models: Methods, Analysis & Insights from Training Gopher
Language modelling provides a step towards intelligent communication systems by harnessing large repositories of written human knowledge to better predict and understand the world.
A Generic Multi-modal Dynamic Gesture Recognition System using Machine Learning
The system was analyzed from an end-user perspective and was modelled to operate in three modes.
An Efficient Deep Learning Model for Automatic Modulation Recognition Based on Parameter Estimation and Transformation
Automatic modulation recognition (AMR) is a promising technology for intelligent communication receivers to detect signal modulation schemes.
Deep Reinforcement Learning for Time Allocation and Directional Transmission in Joint Radar-Communication
joleeson/Directional-JRC
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IEEE Wireless Communications and Networking Conference (WCNC) 2022
In addition, experimental results show that the trained deep reinforcement learning agents are robust to changes in the number of vehicles in the environment.
Multi-Agent Feedback Enabled Neural Networks for Intelligent Communications
liyang619/MAFENN_TRANS_2022
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The design of MAFENN framework and algorithm are dedicated to enhance the learning capability of the feedfoward DL networks or their variations with the simple data feedback.
Synthetic Traffic Generation with Wasserstein Generative Adversarial Networks
snaclab/SPATGAN
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IEEE Global Communications Conference 2022
Network traffic data are critical for network research.
EMC2-Net: Joint Equalization and Modulation Classification based on Constellation Network
hyun-ryu/emc2net
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Modulation classification (MC) is the first step performed at the receiver side unless the modulation type is explicitly indicated by the transmitter.
MVX-ViT: Multimodal Collaborative Perception for 6G V2X Network Management Decisions Using Vision Transformer.
Advancements in sixth-generation (6G) networks, coupled with the evolution of multimodal sensing in vehicle-to-everything (V2X) networks, have opened avenues for transformative research into multimodal-based artificial intelligence (AI) applications for wireless communication and network management.
