Effect of reinforcement learning on routing of cognitive radio ad-hoc networks
Today's network control systems have very limited ability to adapt the changes in network. The addition of reinforcement learning (RL) based network management agents can improve Quality of Service (QoS) by reconfiguring the network layer protocol parameters in response to observed network perf...
| Main Authors: | Safdar, T., Hasbulah, H.B., Rehan, M. |
|---|---|
| Format: | Conference or Workshop Item |
| Institution: | Universiti Teknologi Petronas |
| Record Id / ISBN-0: | utp-eprints.30906 / |
| Published: |
Institute of Electrical and Electronics Engineers Inc.
2016
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| Online Access: |
https://www.scopus.com/inward/record.uri?eid=2-s2.0-84995665385&doi=10.1109%2fISMSC.2015.7594025&partnerID=40&md5=9bbe3b49b2bca53a82af02651d52f1d2 http://eprints.utp.edu.my/30906/ |
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