Reinforcement Learning for Routing in Cognitive Radio Ad Hoc Networks

Joint Authors

Mohamad, Hafizal
Yau, Kok-Lim Alvin
Al-Rawi, Hasan A. A.
Ramli, Nordin
Hashim, Wahidah

Source

The Scientific World Journal

Issue

Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-22, 22 p.

Publisher

Hindawi Publishing Corporation

Publication Date

2014-07-16

Country of Publication

Egypt

No. of Pages

22

Main Subjects

Medicine
Information Technology and Computer Science

Abstract EN

Cognitive radio (CR) enables unlicensed users (or secondary users, SUs) to sense for and exploit underutilized licensed spectrum owned by the licensed users (or primary users, PUs).

Reinforcement learning (RL) is an artificial intelligence approach that enables a node to observe, learn, and make appropriate decisions on action selection in order to maximize network performance.

Routing enables a source node to search for a least-cost route to its destination node.

While there have been increasing efforts to enhance the traditional RL approach for routing in wireless networks, this research area remains largely unexplored in the domain of routing in CR networks.

This paper applies RL in routing and investigates the effects of various features of RL (i.e., reward function, exploitation, and exploration, as well as learning rate) through simulation.

New approaches and recommendations are proposed to enhance the features in order to improve the network performance brought about by RL to routing.

Simulation results show that the RL parameters of the reward function, exploitation, and exploration, as well as learning rate, must be well regulated, and the new approaches proposed in this paper improves SUs’ network performance without significantly jeopardizing PUs’ network performance, specifically SUs’ interference to PUs.

American Psychological Association (APA)

Al-Rawi, Hasan A. A.& Yau, Kok-Lim Alvin& Mohamad, Hafizal& Ramli, Nordin& Hashim, Wahidah. 2014. Reinforcement Learning for Routing in Cognitive Radio Ad Hoc Networks. The Scientific World Journal،Vol. 2014, no. 2014, pp.1-22.
https://search.emarefa.net/detail/BIM-1051756

Modern Language Association (MLA)

Al-Rawi, Hasan A. A.…[et al.]. Reinforcement Learning for Routing in Cognitive Radio Ad Hoc Networks. The Scientific World Journal No. 2014 (2014), pp.1-22.
https://search.emarefa.net/detail/BIM-1051756

American Medical Association (AMA)

Al-Rawi, Hasan A. A.& Yau, Kok-Lim Alvin& Mohamad, Hafizal& Ramli, Nordin& Hashim, Wahidah. Reinforcement Learning for Routing in Cognitive Radio Ad Hoc Networks. The Scientific World Journal. 2014. Vol. 2014, no. 2014, pp.1-22.
https://search.emarefa.net/detail/BIM-1051756

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references

Record ID

BIM-1051756