4 citations · 5 across the 10 of their papers we have counts for
5 papers · 1 filter
On the Error-Reducing Properties of Superposition Codes
Kirill Andreev, Pavel Rybin, Alexey Frolov
Next-generation wireless communication systems impose much stricter requirements for transmission rate, latency, and reliability. The peak data rate of 6G networks should be no les…
Information Bottleneck Analysis of Deep Neural Networks via Lossy Compression
Ivan Butakov, Alexander Tolmachev, Sofia Malanchuk +3
The Information Bottleneck (IB) principle offers an information-theoretic framework for analyzing the training process of deep neural networks (DNNs). Its essence lies in tracking…
Soft-Output Deep Neural Network-Based Decoding
Dmitry Artemasov, Kirill Andreev, Pavel Rybin +1
Deep neural network (DNN)-based channel decoding is widely considered in the literature. The existing solutions are investigated for the case of hard output, i.e. when the decoder…
Energy Efficiency of Unsourced Random Access over the Binary-Input Gaussian Channel
Anton Glebov, Pavel Rybin, Kirill Andreev +1
We investigate the fundamental limits of the unsourced random access over the binary-input Gaussian channel. By fundamental limits, we mean the minimal energy per bit required to a…
Unsourced Random Access with the MIMO Receiver: Projection Decoding Analysis
Kirill Andreev, Daria Ustinova, Alexey Frolov
We consider unsourced random access with MIMO receiver - a crucial communication scenario for future 5G/6G wireless networks. We perform a projection-based decoder analysis and der…