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Found 6 papers, 1 papers with code
Federated mmWave Beam Selection Utilizing LIDAR Data
Efficient link configuration in millimeter wave (mmWave) communication systems is a crucial yet challenging task due to the overhead imposed by beam selection.
Effective Communications: A Joint Learning and Communication Framework for Multi-Agent Reinforcement Learning over Noisy Channels
Specifically, we consider a multi-agent partially observable Markov decision process (MA-POMDP), in which the agents, in addition to interacting with the environment can also communicate with each other over a noisy communication channel.
Multi-agent Reinforcement Learning
reinforcement-learning
+1
DeepJSCC-Q: Channel Input Constrained Deep Joint Source-Channel Coding
Recent works have shown that the task of wireless transmission of images can be learned with the use of machine learning techniques.
DeepWiVe: Deep-Learning-Aided Wireless Video Transmission
We present DeepWiVe, the first-ever end-to-end joint source-channel coding (JSCC) video transmission scheme that leverages the power of deep neural networks (DNNs) to directly map video signals to channel symbols, combining video compression, channel coding, and modulation steps into a single neural transform.
DeepJSCC-Q: Constellation Constrained Deep Joint Source-Channel Coding
Recent works have shown that modern machine learning techniques can provide an alternative approach to the long-standing joint source-channel coding (JSCC) problem.
Generative Joint Source-Channel Coding for Semantic Image Transmission
In GenerativeJSCC, we carry out end-to-end training of an encoder and a StyleGAN-based decoder, and show that GenerativeJSCC significantly outperforms DeepJSCC both in terms of distortion and perceptual quality.
