105 citations · 382 across the 25 of their papers we have counts for
12 papers · 1 filter
Trainable Communication Systems: Concepts and Prototype
Sebastian Cammerer, Fayçal Ait Aoudia, Sebastian Dörner +3
We consider a trainable point-to-point communication system, where both transmitter and receiver are implemented as neural networks (NNs), and demonstrate that training on the bit-…
Learning to Communicate and Energize: Modulation, Coding and Multiple Access Designs for Wireless Information-Power Transmission
Morteza Varasteh, Jakob Hoydis, Bruno Clerckx
The explosion of the number of low-power devices in the next decades calls for a re-thinking of wireless network design, namely, unifying wireless transmission of information and p…
Learning Modulation Design for SWIPT with Nonlinear Energy Harvester: Large and Small Signal Power Regimes
Morteza Varasteh, Jakob Hoydis, Bruno Clerckx
Nonlinear energy harvesters (EH) behave differently depending on the range of their input power. In the literature, different models have been proposed mainly for relatively small…
"Machine LLRning": Learning to Softly Demodulate
Ori Shental, Jakob Hoydis
Soft demodulation, or demapping, of received symbols back into their conveyed soft bits, or bit log-likelihood ratios (LLRs), is at the very heart of any modern receiver. In this p…
Adaptive Neural Signal Detection for Massive MIMO
Mehrdad Khani, Mohammad Alizadeh, Jakob Hoydis +1
Symbol detection for Massive Multiple-Input Multiple-Output (MIMO) is a challenging problem for which traditional algorithms are either impractical or suffer from performance limit…
Joint Learning of Geometric and Probabilistic Constellation Shaping
Maximilian Stark, Fayçal Ait Aoudia, Jakob Hoydis
The choice of constellations largely affects the performance of communication systems. When designing constellations, both the locations and probability of occurrence of the points…