80 citations
- Université Paris-SaclayFR4 papers
- CentraleSupélecFR2 papers
- Laboratoire Traitement et Communication de l’InformationFR2 papers
- Living Independently Now CenterUS2 papers
- Nokia (Germany)DE2 papers
- Télécom ParisFR2 papers
- 3S Photonics (France)FR1 paper
- Centre National de la Recherche ScientifiqueFR1 paper
- Hôpital Xavier ArnozanFR1 paper
- Informa (Sweden)SE1 paper
- Institute of Informatics and TelematicsIT1 paper
- King Abdullah University of Science and TechnologySA1 paper
7 papers · 1 filter
Massive MIMO CSI Feedback using Channel Prediction: How to Avoid Machine Learning at UE?
Muhammad Karam Shehzad, Luca Rose, Mohamad Assaad
In the literature, machine learning (ML) has been implemented at the base station (BS) and user equipment (UE) to improve the precision of downlink channel state information (CSI).…
Trimming the Fat from OFDM: Pilot- and CP-less Communication with End-to-end Learning
Fayçal Ait Aoudia, Jakob Hoydis
Orthogonal frequency division multiplexing (OFDM) is one of the dominant waveforms in wireless communication systems due to its efficient implementation. However, it suffers from a…
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…
Probabilistic Shaping and Non-Binary Codes
Joseph J. Boutros, Fanny Jardel, Cyril Méasson
We generalize probabilistic amplitude shaping (PAS) with binary codes to the case of non-binary codes defined over prime finite fields. Firstly, we introduce probabilistic shaping…
On Deep Learning-Based Channel Decoding
Tobias Gruber, Sebastian Cammerer, Jakob Hoydis +1
We revisit the idea of using deep neural networks for one-shot decoding of random and structured codes, such as polar codes. Although it is possible to achieve maximum a posteriori…
Pilot Contamination is Not a Fundamental Asymptotic Limitation in Massive MIMO
Emil Björnson, Jakob Hoydis, Luca Sanguinetti
Massive MIMO (multiple-input multiple-output) provides great improvements in spectral efficiency over legacy cellular networks, by coherent combining of the signals over a large an…