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5gm-data

Datasets and code for machine learning in 5G mmWave MIMO systems involving mobility (5GMdata)

aloha-sim

Pure ALOHA scheme simulation in Python

aoi_rl

Reinforcement learning based scheduling algorithm for optimizing AoI in URLLC networks

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/

baselines

OpenAI Baselines: high-quality implementations of reinforcement learning algorithms

comms_rl

commscoder

Depicts autoencoders as end-to-end communication systems

decentralized_qlearning_resource_allocation_in_wns

deep-q-learning

Minimal Deep Q Learning (DQN & DDQN) implementations in Keras

deep-q-learning-based-downlink-power-allocation

A deep reinforcement learning based approach is used to allocate downlink power for multi-cell wireless system.

deep-reinforcement-learning-for-dynamic-spectrum-access

Using multi-agent Deep Q Learning with LSTM cells (DRQN) to train multiple users in cognitive radio to learn to share scarce resource (channels) equally without communication

deep-rl-keras

Keras Implementation of popular Deep RL Algorithms (A3C, DDQN, DDPG, Dueling DDQN)

deeprl-agents

A set of Deep Reinforcement Learning Agents implemented in Tensorflow.

deeprl_network

multi-agent deep reinforcement learning for networked system control.

deeprm

Resource Management with Deep Reinforcement Learning (HotNets '16)

dissecting-reinforcement-learning

Python code, PDFs and resources for the series of posts on Reinforcement Learning which I published on my personal blog

drl_multiuseraccess

duel_ddqn

Duel_DDQN (Dueling Network Architectures + Double DQN) using Keras

dynamicmultichannelrl

Contains Implementation of Paper " S Wang, H Liu, P H Gomes, and B Krishnamachari ; Deep Reinforcement Learning for Dynamic Multichannel Access in Wireless Networks"

end-to-end-learning-of-communications-systems-without-a-channel-model

Implementation of research paper: End-to-End Learning of Communications Systems Without a Channel Model

intro_to_ml_lecture_note

irsa

A Matlab implementation of the Irregular Repetition (Diversity) Slotted Aloha MAC layer

irsa_python

Implementation of Irregular Repetition Slotted ALOHA protocol.

itn-windmill-reading-group

Literature reading group / ITN WindMill / https://windmill-itn.eu/

majadoon.github.io

Github Pages template for academic personal websites, forked from mmistakes/minimal-mistakes

marlspectrumsharingv2x

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

meta-autoencoder

Code for the paper "Meta-Learning to Communicate: Fast End-to-End Training for Fading Channels"

ml-from-scratch

Machine Learning From Scratch. Bare bones NumPy implementations of machine learning models and algorithms with a focus on accessibility. Aims to cover everything from linear regression to deep learning.

ml_wirelesscomm

Machine Learning Applications in Wireless Communications - Project work

multichanneldqn-channelmodel