General · GitHub ·35 ★

Q-Learning-Based-Power-Control-Algorithm-for-D2D-Communication

D2D communication as a multi-agents system, and power control is achieved by maximizing system capacity while maintaining the requirement of quality of service(QoS) from cellular users.

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Details

Author
nikhil-feb
Category
General
Platform
GitHub
Framework
custom
Language
matlab
Stars
35
First indexed
2026-05-15
Last active
2019-07-26
Directory sync
2026-05-15
@nikhil-feb

Overview

D2D communication as a multi-agents system, and power control is achieved by maximizing system capacity while maintaining the requirement of quality of service(QoS) from cellular users.

Quick start

git

git clone https://github.com/nikhil-feb/Q-Learning-Based-Power-Control-Algorithm-for-D2D-Communication

Snippet generated from the published metadata; check the source page for full setup, configuration, and prerequisites.

Frequently asked questions

What is Q-Learning-Based-Power-Control-Algorithm-for-D2D-Communication?
D2D communication as a multi-agents system, and power control is achieved by maximizing system capacity while maintaining the requirement of quality of service(QoS) from cellular users.
How do I install Q-Learning-Based-Power-Control-Algorithm-for-D2D-Communication?
Use git: `git clone https://github.com/nikhil-feb/Q-Learning-Based-Power-Control-Algorithm-for-D2D-Communication`. Full setup details on the source page linked above.
Is Q-Learning-Based-Power-Control-Algorithm-for-D2D-Communication open source?
Q-Learning-Based-Power-Control-Algorithm-for-D2D-Communication is published on GitHub.
What are alternatives to Q-Learning-Based-Power-Control-Algorithm-for-D2D-Communication?
Comparable agents include langflow, skills, markitdown. Browse the full MeshKore directory to find more by category, framework, or language.

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Source & freshness

Profile data for Q-Learning-Based-Power-Control-Algorithm-for-D2D-Communication is sourced from GitHub, published by nikhil-feb.

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