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This simulation platform is presented in An Open Platform for Simulating the Physical Layer of 6G Communication Systems with Multiple Intelligent Surfaces.In this paper, we develop an open simulation platform, aimed at modeling the physical-layer electromagnetic coupling and propagation between RIS pairs. We present the platform by initially design
Simulation code for the book “Optimal Resource Allocation in Coordinated Multi-Cell Systems” by Emil Björnson and Eduard Jorswieck, Foundations and Trends in Communications and Information Theory, vol. 9, no. 2-3, pp. 113-381, 2013
Simulation code for “Channel Estimation in Massive MIMO under Hardware Non-Linearities: Bayesian Methods versus Deep Learning,” by Özlem Tugfe Demir, Emil Björnson, IEEE Open Journal of the Communications Society, To appear.
A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in python using Scikit-Learn and TensorFlow.
A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.
Simulation code for “Intelligent Reflecting Surface vs. Decode-and-Forward: How Large Surfaces Are Needed to Beat Relaying?,” by Emil Björnson, Özgecan Özdogan, Erik G. Larsson, IEEE Wireless Communications Letters, vol. 9, no. 2, pp. 244-248, February 2020.
paper simulation "Intelligent Reflecting Surface Enhanced Wireless Network_Joint Active and Passive BeamformingDesign" Qingqing Wu and Rui Zhang
Notes, examples, and Python demos for the textbook "Machine Learning Refined" (published by Cambridge University Press).
Book PDF and simulation code for the monograph "Massive MIMO Networks: Spectral, Energy, and Hardware Efficiency" by Emil Björnson, Jakob Hoydis and Luca Sanguinetti, published in Foundations and Trends in Signal Processing, 2017.
Simulation code for “A Framework for Training-Based Estimation in Arbitrarily Correlated Rician MIMO Channels with Rician Disturbance” by Emil Björnson and Björn Ottersten, IEEE Transactions on Signal Processing, vol. 58, no. 3, pp. 1807-1820, March 2010.
Tri Nhu Do, Georges Kaddoum, Thanh Luan Nguyen, Daniel Benevides da Costa, and Zygmunt J. Haas, “Multi-RIS-aided Wireless Systems: Statistical Characterization and Performance Analysis,” IEEE Transactions on Communications, Sep. 2021.
Simulation code for “Optimal Multiuser Transmit Beamforming: A Difficult Problem with a Simple Solution Structure” by Emil Björnson, Mats Bengtsson, and Björn Ottersten, IEEE Signal Processing Magazine, vol. 31, no. 4, pp. 142-148, July 2014.
Simulation code for "Achievable Rate Optimization for MIMO Systems with Reconfigurable Intelligent Surfaces" by N. S. Perović, L.-N. Tran, M. Di Renzo, and M. F. Flanagan, IEEE Trans. Wireless Commun., vol. 20, no. 6, pp. 3865-3882, Jun. 2021.
scikit-learn: machine learning in Python
This repository contains the description of the IEEE Signal Processing Cup 2021. Everyone is welcome to join this cup!
paper simultaion "Sum-Rate Maximization for Linearly Precoded Downlink Multiuser MISO Systems With Partial CSIT A Rate-Splitting Approach code"
A declarative, efficient, and flexible JavaScript library for building user interfaces.
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TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.