JOURNAL ARTICLE

Cooperative retransmissions using Markov decision process with reinforcement learning

Abstract

In cooperative retransmissions, nodes with better channel qualities help other nodes in retransmitting a failed packet to its intended destination. In this paper, we propose a cooperative retransmission scheme where each node makes local decision to cooperate or not to cooperate at what transmission power using a Markov decision process with reinforcement learning. With the reinforcement learning, the proposed scheme avoids solving an Markov decision process with a large number of states. Through simulations, we show that the proposed scheme is robust to collisions, is scalable with regard to the network size, and can provide significant cooperative diversity.

Keywords:
Markov decision process Retransmission Computer science Reinforcement learning Markov process Scalability Node (physics) Scheme (mathematics) Partially observable Markov decision process Process (computing) Computer network Network packet Markov chain Markov model Artificial intelligence Distributed computing Machine learning Engineering Mathematics

Metrics

6
Cited By
0.69
FWCI (Field Weighted Citation Impact)
19
Refs
0.79
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Cooperative Communication and Network Coding
Physical Sciences →  Computer Science →  Computer Networks and Communications
Advanced MIMO Systems Optimization
Physical Sciences →  Engineering →  Electrical and Electronic Engineering
Wireless Communication Security Techniques
Physical Sciences →  Engineering →  Electrical and Electronic Engineering
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