Pinned Repositories
AutoEncoder-Based-Communication-System
Tensorflow Implementation and result of Auto-encoder Based Communication System From Research Paper : "An Introduction to Deep Learning for the Physical Layer" http://ieeexplore.ieee.org/document/8054694/
book-resource-allocation
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
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.
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.
multiobjective
Simulation code for “Multi-Objective Signal Processing Optimization: The Way to Balance Conflicting Metrics in 5G Systems” by Emil Björnson, Eduard Jorswieck, Mérouane Debbah, and Björn Ottersten, IEEE Signal Processing Magazine, vol. 31, no. 6, pp. 14-23, November 2014.
new-look-at-relaying
Simulation code for “A New Look at Dual-Hop Relaying: Performance Limits with Hardware Impairments” by Emil Björnson, Michail Matthaiou, Mérouane Debbah, IEEE Transactions on Communications, vol. 61, no. 11, pp. 4512-4525, November 2013.
python-ml-case-studies
Source code for 'Python Machine Learning Case Studies' by Danish Haroon
RIS-Codes-Collection
RIS-Codes-Collection: A Complete Collection contains the Codes for RIS(IRS) Researches.
sotawhat
Returns latest research results by crawling arxiv papers and summarizing abstracts. Helps you stay afloat with so many new papers everyday.
stanford-tensorflow-tutorials
This repository contains code examples for the Stanford's course: TensorFlow for Deep Learning Research.
binhddt's Repositories
binhddt/RIS-Codes-Collection
RIS-Codes-Collection: A Complete Collection contains the Codes for RIS(IRS) Researches.
binhddt/sotawhat
Returns latest research results by crawling arxiv papers and summarizing abstracts. Helps you stay afloat with so many new papers everyday.
binhddt/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.
binhddt/python-ml-case-studies
Source code for 'Python Machine Learning Case Studies' by Danish Haroon
binhddt/stanford-tensorflow-tutorials
This repository contains code examples for the Stanford's course: TensorFlow for Deep Learning Research.
binhddt/AutoEncoder-Based-Communication-System
Tensorflow Implementation and result of Auto-encoder Based Communication System From Research Paper : "An Introduction to Deep Learning for the Physical Layer" http://ieeexplore.ieee.org/document/8054694/
binhddt/new-look-at-relaying
Simulation code for “A New Look at Dual-Hop Relaying: Performance Limits with Hardware Impairments” by Emil Björnson, Michail Matthaiou, Mérouane Debbah, IEEE Transactions on Communications, vol. 61, no. 11, pp. 4512-4525, November 2013.
binhddt/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.
binhddt/multiobjective
Simulation code for “Multi-Objective Signal Processing Optimization: The Way to Balance Conflicting Metrics in 5G Systems” by Emil Björnson, Eduard Jorswieck, Mérouane Debbah, and Björn Ottersten, IEEE Signal Processing Magazine, vol. 31, no. 6, pp. 14-23, November 2014.
binhddt/book-resource-allocation
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