Channel Estimation for One-Bit Multiuser Massive MIMO Using Conditional GAN

Linear and Nonlinear precoding in downlink Multi-user Massive MIMO systems

DL tackling Massive-MIMO problems

Matlab Simulation for T. K. Vu, M. Bennis, S. Samarakoon, M. Debbah and M. Latva-aho, "Joint In-Band Backhauling and Interference Mitigation in 5G Heterogeneous Networks," European Wireless 2016; 22th European Wireless Conference, Oulu, Finland, 2016, pp. 1-6. URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7499273&isnumber=7499250

Simulation for "On the total energy efficiency of cell-free massive MIMO" by H. Q. Ngo, L.-N. Tran, T. Q. Duong, M. Matthaiou, E. G. Larsson, IEEE Trans. Green Commun. and Network., vol. 2, no. 1, pp. 25-39, Mar. 2018.

This repository contains the Matlab code used to generate the results in the paper “Enhancement of a state-of-the-art RL-based detection algorithm for Massive MIMO radars” https://ieeexplore.ieee.org/abstract/document/9760145

Codes for reproducing the numerical results reported in both: "Randomized Kaczmarz Algorithm for Massive MIMO Systems with Channel Estimation and Spatial Correlation" by Victor Croisfelt Rodrigues, José Carlos Marinello Filho, and Taufik Abrão. Wiley International Journal of Communication Systems, 2019. "Kaczmarz Precoding and Detection for Mass…

Machine Learning-Based CSI Feedback With Variable Length in FDD Massive MIMO

We have proposed a novel pilot decontamination scheme which combines the two existing schemes: SPRS and WGC-PD scheme.

6G and Security repository for telecommunications and AI research. We will share our implementations and publications in 5G and beyond technology, 6G, Security, Machine learning on 6G, Massive MIMO, THz communication and communication networks.

Allows to reproduce the figures and the appendix of the paper "Correctly Modeling TX and RX Chain in (Distributed) Massive MIMO - New Fundamental Insights on Coherency"

Partial implementaition of the paper "Sohrabi, Foad, & Yu, Wei (2016). Hybrid Digital and Analog Beamforming Design for Large-Scale Antenna Arrays" in python.

Codes for reproducing the numerical results reported in "Exponential Spatial Correlation with Large-Scale Fading Variations in Massive MIMO Channel Estimation" by Victor Croisfelt Rodrigues, José Carlos Marinello Filho, and Taufik Abrão. Transactions on Emerging Telecommunications Technologies. 2019;e3563.

Codes for reproducing the numerical results reported in: "Accelerated Randomized Methods for Receiver Design in Extra-Large Scale MIMO Arrays" by Victor Croisfelt, Abolfazl Amiri, Taufik Abrão, Elisabeth de Carvalho and Petar Popovski.

Codes for reproducing the numerical results reported in: "An Orchestration Framework for Open System Models of Reconfigurable Intelligent Surfaces" by V. Croisfelt, F. Devoti, F. Saggese, V. Sciancalepore, X. Costa-Pérez, and P. Popovski.

Codes for reproducing the numerical results reported in: "Decentralized Design of Fast Iterative Receiver for Massive MIMO with Spatial Non-Stationarities" by V. Croisfelt, T. Abrao, A. Amiri, E. de Carvalho, and P. Popovski.

The PULP Ara is a 64-bit Vector Unit, compatible with the RISC-V Vector Extension Version 1.0, working as a coprocessor to CORE-V's CVA6 core

Pesquisas envolvendo simulações de sistemas 5G, aprendizado federado, beamforming inteligente, algoritmos multiagentes e cooperativos, mobilidade em redes cell-free com MIMO Massivas, superfícies refletoras inteligentes configuráveis e tecnologias 6G.