1 citations · 1 across the 11 of their papers we have counts for
18 papers · 1 filter
Low-Complexity Maximum Likelihood Detection for Type-Based Over-the-Air Computation
Marc Martinez-Gost, Miguel Ángel Lagunas, Ana Pérez-Neira
Type-based multiple access (TBMA) is a digital over-the-air computation (OAC) scheme that exploits symbol collisions over the wireless multiple-access channel to construct a histog…
Efficient DCT-Based Estimation and Compensation of Nonlinear Channels for OFDM Systems
Marc Martinez-Gost, Ana Pérez-Neira, Miguel Ángel Lagunas
This paper proposes a maximum-likelihood (ML) framework for estimating nonlinear frequency-selective channels in orthogonal frequency-division multiplexing (OFDM) communication sys…
Exponential Noise Robustness of Type-Based Multiple Access for Over-the-Air Computation
Marc Martinez-Gost, Ana Pérez-Neira, Miguel Ángel Lagunas
This paper studies the robustness of type-based multiple access (TBMA) in over-the-air computation (AirComp) under nonparametric estimation, where no prior knowledge of the data di…
The DCT Neuron for Estimation and Compensation of Amplitude Distortions in OFDM Systems
Marc Martinez-Gost, Ana Pérez-Neira, Miguel Ángel Lagunas
We present a receiver-side framework for identifying amplitude distortions in frequency-selective OFDM channels. The core novelty is the use of the DCT Neuron, a compact adaptive p…
The DCT Model as a Novel Regression Framework within a Lagrangian Formulation
Marc Martinez-Gost, Ana I. Perez Neira, Miguel Angel Lagunas
This paper introduces a unified regression framework based on the Lagrange formalism, demonstrating how polynomial and logistic regression can all be formulated within a common var…
Before AI Takes Over: Rethinking Nonlinear Signal Processing in Communications
Ana Pérez-Neira, Marc Martinez-Gost, Miguel Ángel Lagunas
There is an urgent reflection on traditional nonlinear signal processing methods in communications before Artificial Intelligence (AI) dominates the field. It implies a need to rea…