HybridDeepRx: Deep Learning Receiver for High-EVM Signals

no code implementations • 30 Jun 2021 • Jaakko Pihlajasalo, Dani Korpi, Mikko Honkala, Janne M. J. Huttunen, Taneli Riihonen, Jukka Talvitie, Alberto Brihuega, Mikko A. Uusitalo, Mikko Valkama

In this paper, we propose a machine learning (ML) based physical layer receiver solution for demodulating OFDM signals that are subject to a high level of nonlinear distortion.

Vocal Bursts Intensity Prediction

Gradient-Adaptive Spline-Interpolated LUT Methods for Low-Complexity Digital Predistortion

no code implementations • 4 Jul 2019 • Pablo Pascual Campo, Alberto Brihuega, Lauri Anttila, Matias Turunen, Dani Korpi, Markus Allén, Mikko Valkama

The results show that the linearization capabilities of the proposed methods are very close to that of the ordinary MP DPD, particularly with the proposed SMP approach, while having substantially lower processing complexity.

Digital Predistortion for Multiuser Hybrid MIMO at mmWaves

no code implementations • 22 Mar 2019 • Alberto Brihuega, Lauri Anttila, Mahmoud Abdelaziz, Fredrik Tufvesson, Mikko Valkama

Efficient mitigation of power amplifier (PA) nonlinear distortion in multi-user hybrid precoding based broadband mmWave systems is an open research problem.