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Meng's Projects

sumo icon sumo

Eclipse SUMO is an open source, highly portable, microscopic and continuous traffic simulation package designed to handle large networks. It allows for intermodal simulation including pedestrians and comes with a large set of tools for scenario creation.

sumo-matlab icon sumo-matlab

MATLAB code for interacting with Simulation of Urban MObility (SUMO)

sumo_drone_simulation icon sumo_drone_simulation

code for generate all SUMO files for a drone simulation, with height variable in a normal distribution

sumoscenariogenerator icon sumoscenariogenerator

SUMO Scenario Generator is a web application that generates and downloads the necessary files to start a basic road traffic simulation in SUMO. Visit the official Eclipse SUMO repository: https://github.com/eclipse/sumo - More info about SUMO: https://eclipse.org/sumo/ - SUMO Documentation: https://sumo.dlr.de/docs/

talkycars-thesis icon talkycars-thesis

A Distributed Platform Approach to Cooperative Perception based on Celluar-V2X Communication

team-mmse icon team-mmse

Simulation code for “ Team MMSE Precoding with Applications to Cell-free Massive MIMO” by Lorenzo Miretti, Emil Björnson, David Gesbert, To appear 2022

temporal_vbi icon temporal_vbi

MATLAB codes for "Fast variational Bayesian inference for temporally correlated sparse signal recovery"

teramimo icon teramimo

TeraMIMO: A channel simulator for wideband ultra-massive MIMO terahertz communications.

tfocs icon tfocs

A MATLAB toolbox for building first-order solvers for convex models.

traci4matlab icon traci4matlab

An implementation of the Traffic Control Interface for Matlab

transferlearning icon transferlearning

Transfer learning / domain adaptation / domain generalization / multi-task learning etc. Papers, codes, datasets, applications, tutorials.-迁移学习

tsks14_multiple_antenna_communications icon tsks14_multiple_antenna_communications

This repository contains the slides (in Powerpoint and PDF formats) for the course TSKS14 Multiple Antenna Communications, used 2020. Video recordings of all the slides (with voice over by Emil Björnson) can be found on YouTube.

tsp-dnn icon tsp-dnn

Training Deep Neural Networks for Wireless Resource Management

twin-td3 icon twin-td3

IEEE WCNC 2023: Deep Reinforcement Learning for Secrecy Energy-Efficient UAV Communication with Reconfigurable Intelligent Surfaces

two-timescale-dnn icon two-timescale-dnn

Two-Timescale End-to-End Learning for Channel Acquisition and Hybrid Precoding

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