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Dayo Oladejo's Projects

covid-ct icon covid-ct

COVID-CT-Dataset: A CT Scan Dataset about COVID-19

dataset icon dataset

医学影像数据集列表 『An Index for Medical Imaging Datasets』

deep_learning_wireless_networks icon deep_learning_wireless_networks

Final year project (BEng Electronic Engineering with Management): Applications of Deep Learning in Resource Allocation in Wireless Networks

deepslice icon deepslice

DeepSlice: A Deep Learning Approach towards an Efficient and Reliable Network Slicing in 5G Networks

economicsimulator icon economicsimulator

Simulator for studying network providers interaction under the ChoiceNet concepts

end2end_gan icon end2end_gan

Conditional GAN based End-to-End Communication System

gadmm icon gadmm

GADMM: fast and communication efficient framework for distributed machine learning

gnnpapers icon gnnpapers

Must-read papers on graph neural networks (GNN)

irs-modeling icon irs-modeling

Simulation code for “Intelligent Reflecting Surfaces: Physics, Propagation, and Pathloss Modeling,” by Özgecan Özdogan, Emil Björnson, Erik G. Larsson, IEEE Wireless Communications Letters, To appear.

irs-relaying icon irs-relaying

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.

ln-game-theory icon ln-game-theory

Matlab code for the figures and the examples used in G. Bacci, L. Sanguinetti, and M. Luise, "Understanding game theory via wireless power control,' submitted to IEEE Signal Process. Mag., Oct. 2014.

marlspectrumsharingv2x icon marlspectrumsharingv2x

Spectrum sharing in vehicular networks based on multi-agent reinforcement learning, IEEE Journal on Selected Areas in Communications

max-ee-multislope-path-loss icon 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!

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