# DRL_for_DDBC

**Repository Path**: goudi520/DRL_for_DDBC

## Basic Information

- **Project Name**: DRL_for_DDBC
- **Description**: Simulation codes for the manuscript "Deep Reinforcement Learning for Distributed Dynamic MISO Downlink-Beamforming Coordination" submitted to IEEE Transactions on Communications
- **Primary Language**: Unknown
- **License**: Not specified
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2020-11-11
- **Last Updated**: 2020-12-19

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

### Simulation codes and results for the manuscript "Deep Reinforcement Learning for Distributed Dynamic MISO Downlink-Beamforming Coordination", which has been accepted for publication in IEEE Transactions on Communications.
---
#### What in the three folders

The simulation codes are in the folder `./code`, the data and figures of simulation results is in folder `./data_and_plots`, and a demo simulation program with detailed annotations in the folder `./DRL_for_DDBC`. All the simulation programs in `./code` are based on the demo simulation program with some altered simulation parameters.
#### Requirements to run the simulation programs and plot the figures
The simulation programs require Python3 with installed packages such as Keras, Tesorflow, Numpy, Scipy and etc. The figures are plot by MATLAB. 

#### Structure of the demo simulation program
`./DRL_for_DDBC/codebook/codebook.mat` the file for saving the codebook matrix used in current simulation program.

`./DRL_for_DDBC/data` the folder to save the simulation results of the four schemes.

`./DRL_for_DDBC/rates` the folder to save the achievable rate of each cell within the simulation process

`./DRL_for_DDBC/base_station.py` the simulator of the base station

`./DRL_for_DDBC/cellular_network.py` the simulator of the cellular network

`./DRL_for_DDBC/channel.py` the simulator of the channels

`./DRL_for_DDBC/config.py` the file to save the configuration of the current simulation program

`./DRL_for_DDBC/data_process.py` the python script to plot the simulation results of the current simulation program

`./DRL_for_DDBC/dqn_for_singleagent.py` the DQN agent at each BS

`./DRL_for_DDBC/drl.py` the DTDE DRL-based scheme

`./DRL_for_DDBC/export_locations.py` export the locations of BSs and UEs as `.mat` files

`./DRL_for_DDBC/fp_algorithm.py` the ideal FP approach

`./DRL_for_DDBC/functions.py` some extra functions requied in the simulation

`./DRL_for_DDBC/greedy.py` the greedy scheme

`./DRL_for_DDBC/neural_network.py` the file to save the configurations of the neural network in DQN

`./DRL_for_DDBC/random_choose.py` the random scheme

`./DRL_for_DDBC/user_equipment.py` the simulator of the user equipments

In each file above, there are detailed annotations to help you understand the simulation program.
#### How to use
After running the simulation programs, the simulation results will be saved as json files such as `XXXX.json` in the corresponding folder `data`. Then you can rename and copy the results, i.e., the json files, to the corresponding folder in `./data_and_plots`. Run the script `json2mat.py` to transform the json files to `.mat` files. Finally run the MATLAB script file in the same folder to plot the figure.