10 citations · 29 across the 18 of their papers we have counts for
25 papers
Variational Bayesian Tensor Decomposition With Discrete Mixture Prior for Unsourced Random Access
Ala Baccar, Alexis Decurninge, Alberto Rech +3
Tensor-based modulation (TBM) schemes are a promising approach for unsourced random access (URA), where user separation relies on decomposing the received signal tensor via the can…
Tensor-based Random Access for Ambient IoT Contention Resolution
Alberto Rech, Alexis Decurninge, Ala Baccar +1
Ambient Internet of Things (A-IoT) deployments impose stringent hardware constraints, including low-order modulations and simple transceiver architectures. We propose a tensor-base…
Statistical Limits in Random Tensors with Multiple Correlated Spikes
Yang Qi, Alexis Decurninge
We use tools from random matrix theory to study the multi-spiked tensor model, i.e., a rank- deformation of a symmetric random Gaussian tensor. In particular, thanks to the natu…
An Introduction to Complex Random Tensors
Divyanshu Pandey, Alexis Decurninge, Harry Leib
This work considers the notion of random tensors and reviews some fundamental concepts in statistics when applied to a tensor based data or signal. In several engineering fields su…
On the Accuracy of Hotelling-Type Asymmetric Tensor Deflation: A Random Tensor Analysis
Mohamed El Amine Seddik, Maxime Guillaud, Alexis Decurninge +1
This work introduces an asymptotic study of Hotelling-type tensor deflation in the presence of noise, in the regime of large tensor dimensions. Specifically, we consider a low-rank…
Unsourced Random Access With Tensor-Based and Coherent Modulations
Alberto Rech, Alexis Decurninge, Luis G. Ordóñez
Unsourced random access (URA) is a particular form of grant-free uncoordinated random access wherein the users' identities are not associated to specific waveforms at the physical…