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Name: 娄毅 (Yi Lou)

Type: User

Company: Harbin Institute of Technology

Bio: 娄毅目前工作于哈尔滨工业大学（威海）。 Since 2022, Yi Lou has been an Associate Professor at Harbin Institute of Technology Weihai.

Location: Weihai

Blog: http://homepage.hit.edu.cn/louyi

娄毅 (Yi Lou)'s Projects

massive-mimo-book-chapter

Simulation code for the book chapter “Massive MIMO Communications” by Trinh van Chien and Emil Björnson, 5G Mobile Communications, Springer, 2017

massive-mimo-hardware-impairments

Simulation code for “Massive MIMO Systems with Non-Ideal Hardware: Energy Efficiency, Estimation, and Capacity Limits” by Emil Björnson, Jakob Hoydis, Marios Kountouris, Mérouane Debbah, IEEE Transactions on Information Theory, vol. 60, no. 11, pp. 7112-7139, November 2014.

massive-mimo-myths

Simulation code for “Massive MIMO: Ten Myths and One Critical Question” by Emil Björnson, Erik G. Larsson, Thomas L. Marzetta, IEEE Communications Magazine, vol. 54, no. 2, pp. 114-123, February 2016

massive-mimo-rician-channels

This code computes the spectral efficiency in the downlink of a Massive MIMO systems over Uncorrelated Rician Fading Channels. In particular, it generates Figs. 4 and 5 of a manuscript that is currently under review for publication on IEEE Transactions on Communications (submitted May 2018). The manuscript will be made available soon on arxiv.

massive-mimo-small-cells

Simulation code for “Massive MIMO and Small Cells: Improving Energy Efficiency by Optimal Soft-Cell Coordination” by Emil Björnson, Marios Kountouris, Mérouane Debbah, Proceedings of International Conference on Telecommunications (ICT), Casablanca, Morocco, May 2013.

massivemimobook

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.

math_model

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mathcompile

Compile Wolfram Language functions into C++ code and binary

mathematica

Mathematica Packages

mathematica-coding

Some interesting projects implemented with Mathematica

mathematica-mcmc

Mathematica Markov chain Monte Carlo

mathematica-tools

One-off tools and packages

mathematicaforprediction

Mathematica implementations of machine learning algorithms used for prediction and personalization.

mathgr

A package for GR calculation

mathpix

Mathpix API in Mathematica

mathworks-excellence-in-innovation

Capstone and senior design projects for undergraduate and graduate students to gain practical experience and insight into technology trends and industry directions.

mathworks_tools

Scripts and tools created by ADI to be used with MATLAB and Simulink with ADI products

matlab-code-twc-aug2017

Matlab code of the paper: N. T. Do, D. B. da Costa, T. Q. Duong, V. N. Q. Bao, and B. An, “Exploiting direct links in multiuser multirelay SWIPT cooperative networks with opportunistic scheduling,” IEEE Transactions on Wireless Communications, vol. 16, no. 8, pp. 5410–5427, Aug. 2017

matlab-octave

This repository contains algorithms written in MATLAB/Octave. Developing algorithms in the MATLAB environment empowers you to explore and refine ideas, and enables you test and verify your algorithm.

matlab_daqmx_examples

DAQmx Examples using MATLAB

max-ee-multislope-path-loss

This is a code package is related to the follow scientific article: Andrea Pizzo, Daniel Verenzuela, Luca Sanguinetti and Emil Björnson, "Network Deployment for Maximal Energy Efficiency in Uplink with Multislope Path Loss," IEEE Transactions on Green Communications and Networking, Submitted to. The package contains a simulation environment, based on Matlab, that reproduces all the numerical results and figures in the article. We encourage you to also perform reproducible research!

maximal-ee

Simulation code for “Deploying Dense Networks for Maximal Energy Efficiency: Small Cells Meet Massive MIMO” by Emil Björnson, Luca Sanguinetti, Marios Kountouris, To appear in IEEE Journal on Selected Areas in Communications

maximal-se

Simulation code for “Massive MIMO for Maximal Spectral Efficiency: How Many Users and Pilots Should Be Allocated?” by Emil Björnson, Erik G. Larsson, Mérouane Debbah, IEEE Transactions on Wireless Communications, vol. 15, no. 2, pp. 1293-1308, 2016.

mfoxh

Multivariate Fox H-function C/Matlab MEX

mh-tracker

Track-Oriented Multiple Hypothesis Tracker

mht

Multiple Hypothesis Tracking

mht-1

Python implementation of the Multiple Hypothesis Tracking algorithm

mimo-channel-estimation

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.

mimo-ofdm

MATLAB code simulating different MIMO-OFDM schemes

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