6 citations · 8 across the 6 of their papers we have counts for
6 papers
Deterministic Smoothed MAP Detection for High-Dimensional MIMO Systems
Vitor Tucci Ramos, Stephane Senecal, Sheng Yang
We propose a deterministic smoothed maximum a posteriori (SMAP) framework for high-dimensional multiple-input multiple-output (MIMO) detection. The discrete constellation prior is…
From RAN Control to Agentic Intelligence: Architecture and Vision for Energy Efficient AI-RAN
Sabrine Aroua, Alexis I. Aravanis, Ilias Chatzistefanidis +7
Future 6G networks will rely on highly distributed, AI-native Radio Access Networks (RANs), where communication and AI workloads share a common infrastructure. This evolution, comb…
Forward Event-Chain Monte Carlo: Fast sampling by randomness control in irreversible Markov chains
Manon Michel, Alain Durmus, Stéphane Sénécal
Irreversible and rejection-free Monte Carlo methods, recently developed in Physics under the name Event-Chain and known in Statistics as Piecewise Deterministic Monte Carlo (PDMC),…
Analytical Performance Model for Poisson Wireless Networks with Pathloss and Shadowing Propagation
Jean-Marc Kelif, Stephane Senecal, Marceau Coupechoux +1
The SINR (signal to interference plus noise ratio) is a key factor for wireless networks analysis. Indeed, the SINR distribution allows the derivation of performance and quality of…
A Fluid Approach for Poisson Wireless Networks
Jean-Marc Kelif, Stephane Senecal, Constant Bridon +1
Among the different models of networks usually considered, the hexagonal network model is the most popular. However, it requires extensive numerical computations. The Poisson netwo…
The association problem in wireless networks: a Policy Gradient Reinforcement Learning approach
Richard Combes, Ilham El Bouloumi, Stephane Senecal +1
The purpose of this paper is to develop a self-optimized association algorithm based on PGRL (Policy Gradient Reinforcement Learning), which is both scalable, stable and robust. Th…