# DQN-PowerControl

**Repository Path**: goudi520/DQN-PowerControl

## Basic Information

- **Project Name**: DQN-PowerControl
- **Description**: No description available
- **Primary Language**: Unknown
- **License**: Not specified
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2020-09-15
- **Last Updated**: 2020-12-19

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

注：本代码是从Jun Fang教授的主页下载

**DQN-power-control** is the code for applying deep reinforcement learning for spectrum sharing in cognitive radios, available at http://www.junfang-uestc.net/codes/DQN-power-control.rar.

The code has been tested on Ubuntu 14.04 + tensorflow 1.0.0 + Python 2.7.

Reference:  Xingjian Li, Jun Fang, Wen Cheng, Huiping Duan, Zhi Chen, and Hongbin Li, "Intelligent Power Control for Spectrum Sharing in Cognitive Radios: A Deep Reinforcement Learning Approach," was accepted by IEEE Access, May 2018.

Written by: Wen Cheng

Email: JunFang@uestc.edu.cn


Get Start:

cd ./code

python main.py


Optional parameters (main.py):

noise - The estimation error of RSS

num_sensor - The number of sensors

policy - Power update policy of PU, suppose to be 1 or 2