963 citations · 3.4k across the 52 of their papers we have counts for
7 papers · 1 filter
Bayesian Optimization for Radio Resource Management: Open Loop Power Control
Lorenzo Maggi, Alvaro Valcarce Rial, Jakob Hoydis
We provide the reader with an accessible yet rigorous introduction to Bayesian optimisation with Gaussian processes (BOGP) for the purpose of solving a wide variety of radio resour…
Toward a 6G AI-Native Air Interface
Jakob Hoydis, Fayçal Ait Aoudia, Alvaro Valcarce +1
Each generation of cellular communication systems is marked by a defining disruptive technology of its time, such as orthogonal frequency division multiplexing (OFDM) for 4G or Mas…
Machine Learning for MU-MIMO Receive Processing in OFDM Systems
Mathieu Goutay, Fayçal Ait Aoudia, Jakob Hoydis +1
Machine learning (ML) starts to be widely used to enhance the performance of multi-user multiple-input multiple-output (MU-MIMO) receivers. However, it is still unclear if such met…
End-to-end Learning for OFDM: From Neural Receivers to Pilotless Communication
Fayçal Ait Aoudia, Jakob Hoydis
Previous studies have demonstrated that end-to-end learning enables significant shaping gains over additive white Gaussian noise (AWGN) channels. However, its benefits have not yet…
Towards Joint Learning of Optimal MAC Signaling and Wireless Channel Access
Alvaro Valcarce, Jakob Hoydis
Communication protocols are the languages used by network nodes. Before a user equipment (UE) can exchange data with a base station (BS), it must first negotiate the conditions and…
Joint Learning of Probabilistic and Geometric Shaping for Coded Modulation Systems
Fayçal Ait Aoudia, Jakob Hoydis
We introduce a trainable coded modulation scheme that enables joint optimization of the bit-wise mutual information (BMI) through probabilistic shaping, geometric shaping, bit labe…
Deep HyperNetwork-Based MIMO Detection
Mathieu Goutay, Fayçal Ait Aoudia, Jakob Hoydis
Optimal symbol detection for multiple-input multiple-output (MIMO) systems is known to be an NP-hard problem. Conventional heuristic algorithms are either too complex to be practic…