Abstract
Cognitive wireless mesh networks have great flexibility to improve the spectrum utilization by opportunistically accessing the authorized frequency bands, within which the secondary users (SUs) should not violate the quality of service (QoS) requirement of the primary users (PUs) while transmitting. In this paper, we consider inter-cluster connection among neighboring clusters under the framework of cognitive wireless mesh networks. Corresponding to the neighboring clusters, all nodes operate in half-duplex mode; hence exchanging control message usually needs four time slots by traditional scheme, which leads to a loss in networking and spectral efficiency especially at the gateway node. A novel scheme based on network coding is proposed, which needs only two time slots. Our simulation experiments reveal the following findings: the performances of traditional inter-cluster connection and network coding based inter-cluster connection are comparable. Next, how to choose optimal signal amplification factor at the gateway node according to the wireless environment is discussed. And we present an intelligent policy based on reinforcement learning to solve the problem. Theoretical analysis and numerical results both show the policy can achieve optimal throughput for the SUs in the long run.
Original language | English |
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Title of host publication | 2009 IEEE 20th Personal, Indoor and Mobile Radio Communications Symposium, PIMRC 2009 |
Publisher | IEEE Institute of Electrical and Electronic Engineers |
ISBN (Print) | 978-1-4244-5123-4 |
DOIs | |
Publication status | Published - 1 Dec 2009 |
MoE publication type | Not Eligible |
Event | 20th IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC 2009 - Tokyo, Japan Duration: 13 Sept 2009 → 16 Sept 2009 |
Conference
Conference | 20th IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC 2009 |
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Abbreviated title | PIMRC 2009 |
Country/Territory | Japan |
City | Tokyo |
Period | 13/09/09 → 16/09/09 |
Keywords
- Cluster
- CogMesh
- Cognitive radio
- Cognitive wireless mesh networks
- Network coding
- Reinforcement learning
- Relaying