… channel estimation scheme can be extended to multi-user scenario by using mutually orthogonal
time or code … Additionally, in our deep learning experiments, we adopt Nant IRS = 16 × …

… the channel hardening makes the channel after MRC almost deterministic. The simulations
in [7] shows that coding … In order to work with deep neural networks, we now use the channel …

… The HCS 2 -Net 31 took random code of the coded aperture and snapshot measurement as
… task, sub-pixel convolution layer 75 , channel attention 69 from image super resolution task, …

… a new class of high-efficiency deep joint source-channel coding methods to achieve end-to-end …
Goldsmith, “Deep learning for joint sourcechannel coding of text,” in Proceedings of the …

… On the other hand, due to their sheer size, deep learning algorithms are hardly re-… of
deep-learning-based radio fingerprinting algorithms without retraining the underlying deep learning …

… In this paper, we propose a deep learning framework for the … Jin, and GY Li, “Deep
learning-based CSI feedback approach … Juang, “Power of deep learning for channel estimation …

… coding, channel coding, and modulation module, while the PHY receiver includes
synchronization, channel estimation, equalization, demodulation, channel … of deep learning based …

… to estimate the sub-6GHz channels and this channel is passed to the deep learning model
which predicts which mmWave beam should be used … Code files are available online at [39]. …

… channel is predicted in the relay node through our distinct deep learning model, the
modulation, coding rate, and sending rate are acquired from the modulation and coding scheme (…

… a unit in channel i of the output unit and a unit in channel j of … value of the input unit within
channel i at row j and column k. … is similar to increasing the code distance in coding principle. …