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5gnr-hetnet_model

This work demonstrates the performance feasibility of a Heterogeneous cellular Network (HetNet) setup depicting a 5G dense urban microcellular deployment scenario with a Wireless Backhaul.

ai

使用深度强化学习解决视觉跟踪和视觉导航问题

b2dqn

basic_reinforcement_learning

An introduction series to Reinforcement Learning (RL) with comprehensive step-by-step tutorials.

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

breast-tumour-maligancy-classification

Breast tumor malignancy classification using machine learning

bsca

Matlab code for block successive convex approximation algorithms

classicpowerallocation

This is a classic power allocation in a sparse femtocell network based on dual lagrange problem.

commag_code

Simulation code and additional documents for Communication Magazine

convex-optimization

A convex optimization course https://see.stanford.edu/Course/EE364A completed homework assignments

dca

Dynamic channel allocation in cellular networks by reinforcement learning

decentralized_qlearning_resource_allocation_in_wns

deep-ee-opt

Source code for "Deep Learning for Optimal Energy-Efficient Power Control in Wireless Interference Networks" by Bho Matthiesen, Alessio Zappone, Eduard A. Jorswieck, and Merouane Debbah, submitted to IEEE Journal on Selected Areas in Communication.

deep-learning-power-allocation-in-massive-mimo

This is the code package related to the follow scientific article: Luca Sanguinetti, Alessio Zappone, Merouane Debbah 'Deep-Learning-Power-Allocation-in-Massive-MIMO' presented at the Asilomar Conference on Signals, Systems, and Computers, 2018. http://www.asilomarsscconf.org

deep-learning-v2-pytorch

Projects and exercises for the latest Deep Learning ND program https://www.udacity.com/course/deep-learning-nanodegree--nd101

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-5g-networks

Code for my publication: Deep Reinforcement Learning for 5G Networks: Joint Beamforming, Power Control, and Interference Coordination. Paper accepted for publication to IEEE Transactions on Communications.

deep-rl-keras

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

deeprl_segmentation

Project for Berkeley Deep RL course: using deep reinforcement learning for segmentation of medical images

deeprlvehicularlocalization

Decentralized Scheduling for Cooperative Localization with Deep Reinforcement Learning

dl-massive-mimo

DL tackling Massive-MIMO problems

double-deep-q-learning-for-resource-allocation

Reproduce results of the research article "Deep Reinforcement Learning Based Resource Allocation for V2V Communications"

dqn_of_dwa_matlab

learning the weight of each paras in DWA(Dynamic Window Approach) by using DQN(Deep Q-Learning)

drl-code-pytorch

Concise pytorch implements of DRL algorithms, including REINFORCE, A2C, DQN, PPO(discrete and continuous), DDPG, TD3, SAC.

drl_for_ddbc

Simulation codes for the manuscript "Deep Reinforcement Learning for Distributed Dynamic MISO Downlink-Beamforming Coordination" submitted to IEEE Transactions on Communications

drone_rl

Solving Beamforming problem using reinforcement learning between Base station and UAV

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"

ee-cr

Source code for "Energy Efficiency in MIMO Underlay and Overlay Device-to-Device Communications and Cognitive Radio Systems," by Alessio Zappone, Bho Matthiesen, and Eduard Jorswieck, IEEE Transactions on Signal Processing, vol. 65, no. 4, pp. 1026-1041 Feb. 2017.

energy_efficiency_optimization_for_mimo_interference_networks

Solving energy efficiency optimization problem for MIMO interference wireless network using iterative semi-definite programming with WMMSE (SDP-WMMSE) algorithm and successive convex approximation (SCA) algorithm

fairness-and-sum-rate-maximization-via-joint-subcarrier-and-power-allocation-in-uplink-scma-transmis

Code for the joint power and subcarrier allocation algorithm for sum rate and fairness maximization in SCMA uplink transmission (link to the paper https://ieeexplore.ieee.org/document/8836645)