Spectrum optimization in cognitive satellite networks with graph coloring method
Cognitive satellite networks can enhance spectrum efficiency by enabling satellite networks to dynamically share idle spectrum with terrestrial networks. However, when taking into consideration the inter-cell or internet interferences in various application circumstances, dynamic spectrum optimizati...
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sg-ntu-dr.10356-1443992020-11-03T06:47:56Z Spectrum optimization in cognitive satellite networks with graph coloring method Wang, Li Lam, Kwok-Yan Zhang, Jiangxin Li, Feng School of Computer Science and Engineering Research Techno Plaza Engineering::Computer science and engineering Cognitive Satellite Networks Spectrum Optimization Cognitive satellite networks can enhance spectrum efficiency by enabling satellite networks to dynamically share idle spectrum with terrestrial networks. However, when taking into consideration the inter-cell or internet interferences in various application circumstances, dynamic spectrum optimization in cognitive satellite networks remains challenging due to the diversified QoS demands of secondary terrestrial users. To address this issue, this paper proposes an efficient spectrum allocation algorithm which is based on graph coloring technique and combined with analytic hierarchy process so as to meet the requirements of dynamic spectrum allocation to secondary terrestrial users with diversified QoS demands and yet without causing severe inference to primary satellite users. In this paper, we combine graph coloring algorithm and analytic hierarchy process so as to assign the heterogeneous spectrum bands to secondary users in an orderly manner. The method of graph coloring is applied to control obvious interference caused by the secondary users. We also provide numerical results to evaluate the impacts of different parameter settings on the performances of the proposed solution. National Research Foundation (NRF) Accepted version This research is supported by the National Research Foundation, Prime Ministers Office, Singapore under its Strategic Capability Research Centres Funding Initiative. This work is also supported by the National Natural Science Foundation of China under Grant 51404211. 2020-11-03T06:44:30Z 2020-11-03T06:44:30Z 2019 Journal Article Wang, L., Lam, K.-Y., Zhang, J., & Li, F. (2019). Spectrum optimization in cognitive satellite networks with graph coloring method. Wireless Networks. doi:10.1007/s11276-019-02138-9 1022-0038 https://hdl.handle.net/10356/144399 10.1007/s11276-019-02138-9 en Strategic Centre for Research in Privacy-Preserving Technologies & Systems Wireless Networks © 2019 Springer. This is a post-peer-review, pre-copyedit version of an article published in Wireless Networks. The final authenticated version is available online at: http://dx.doi.org/10.1007/s11276-019-02138-9 application/pdf |
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Engineering::Computer science and engineering Cognitive Satellite Networks Spectrum Optimization Wang, Li Lam, Kwok-Yan Zhang, Jiangxin Li, Feng Spectrum optimization in cognitive satellite networks with graph coloring method |
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Cognitive satellite networks can enhance spectrum efficiency by enabling satellite networks to dynamically share idle spectrum with terrestrial networks. However, when taking into consideration the inter-cell or internet interferences in various application circumstances, dynamic spectrum optimization in cognitive satellite networks remains challenging due to the diversified QoS demands of secondary terrestrial users. To address this issue, this paper proposes an efficient spectrum allocation algorithm which is based on graph coloring technique and combined with analytic hierarchy process so as to meet the requirements of dynamic spectrum allocation to secondary terrestrial users with diversified QoS demands
and yet without causing severe inference to primary satellite users. In this paper, we combine graph coloring algorithm and analytic hierarchy process so as to assign the heterogeneous spectrum bands to secondary users in an orderly manner. The method of graph coloring is applied to control obvious interference caused by the secondary users. We also provide numerical results to evaluate the impacts of different parameter settings on the performances of the proposed solution. |
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School of Computer Science and Engineering |
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School of Computer Science and Engineering Wang, Li Lam, Kwok-Yan Zhang, Jiangxin Li, Feng |
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Article |
author |
Wang, Li Lam, Kwok-Yan Zhang, Jiangxin Li, Feng |
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Wang, Li |
title |
Spectrum optimization in cognitive satellite networks with graph coloring method |
title_short |
Spectrum optimization in cognitive satellite networks with graph coloring method |
title_full |
Spectrum optimization in cognitive satellite networks with graph coloring method |
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Spectrum optimization in cognitive satellite networks with graph coloring method |
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Spectrum optimization in cognitive satellite networks with graph coloring method |
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spectrum optimization in cognitive satellite networks with graph coloring method |
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2020 |
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https://hdl.handle.net/10356/144399 |
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