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- Publisher Website: 10.1109/TMC.2020.2997077
- Scopus: eid_2-s2.0-85117186762
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Article: On Heterogeneous Sensing Capability for Distributed Rendezvous in Cognitive Radio Networks
Title | On Heterogeneous Sensing Capability for Distributed Rendezvous in Cognitive Radio Networks |
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Authors | |
Keywords | Cognitive Radio Network Rendezvous Heterogeneous Sensing Capability Distributed Algorithm |
Issue Date | 2021 |
Publisher | IEEE. The Journal's web site is located at https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=7755 |
Citation | IEEE Transactions on Mobile Computing, 2021, v. 20 n. 11, p. 3211-3226 How to Cite? |
Abstract | Cognitive radio networks have been proposed to solve the spectrum scarcity problem. One of their fundamental procedures is to construct a communication link on a common channel for the users, which is referred to as rendezvous. In reality, the capability to sense the spectrum may vary from user to user. We study distributed rendezvous for heterogeneous sensing capabilities in this paper. The licensed spectrum is divided into n channels and each user can sense a subset of the channels. Due to hardware differences, users may have different sensing capabilities. We study two scenarios: the fully available scenario where all channels are available in the capability set and the partially available scenario. Our idea is to utilize two 'pointers' to traverse the capability set, which sets our algorithms apart from the extant rendezvous algorithms. We propose the Traversing Pointer (TP) algorithm for the fully available scenario which works better than state-of-the-art result and is only O(loglogn) larger than the theoretical lower bound. For the partially available scenario, we propose the Moving Traversing Pointers (MTP) and Prime based Moving Traversing Pointers (P-MTP) algorithms that work more efficiently than previous best result. We also conduct extensive simulations and the results corroborate our analyses. |
Persistent Identifier | http://hdl.handle.net/10722/286496 |
ISSN | 2023 Impact Factor: 7.7 2023 SCImago Journal Rankings: 2.755 |
ISI Accession Number ID |
DC Field | Value | Language |
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dc.contributor.author | Gu, Z | - |
dc.contributor.author | Wang, Y | - |
dc.contributor.author | Shen, T | - |
dc.contributor.author | Lau, FCM | - |
dc.date.accessioned | 2020-08-31T07:04:41Z | - |
dc.date.available | 2020-08-31T07:04:41Z | - |
dc.date.issued | 2021 | - |
dc.identifier.citation | IEEE Transactions on Mobile Computing, 2021, v. 20 n. 11, p. 3211-3226 | - |
dc.identifier.issn | 1536-1233 | - |
dc.identifier.uri | http://hdl.handle.net/10722/286496 | - |
dc.description.abstract | Cognitive radio networks have been proposed to solve the spectrum scarcity problem. One of their fundamental procedures is to construct a communication link on a common channel for the users, which is referred to as rendezvous. In reality, the capability to sense the spectrum may vary from user to user. We study distributed rendezvous for heterogeneous sensing capabilities in this paper. The licensed spectrum is divided into n channels and each user can sense a subset of the channels. Due to hardware differences, users may have different sensing capabilities. We study two scenarios: the fully available scenario where all channels are available in the capability set and the partially available scenario. Our idea is to utilize two 'pointers' to traverse the capability set, which sets our algorithms apart from the extant rendezvous algorithms. We propose the Traversing Pointer (TP) algorithm for the fully available scenario which works better than state-of-the-art result and is only O(loglogn) larger than the theoretical lower bound. For the partially available scenario, we propose the Moving Traversing Pointers (MTP) and Prime based Moving Traversing Pointers (P-MTP) algorithms that work more efficiently than previous best result. We also conduct extensive simulations and the results corroborate our analyses. | - |
dc.language | eng | - |
dc.publisher | IEEE. The Journal's web site is located at https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=7755 | - |
dc.relation.ispartof | IEEE Transactions on Mobile Computing | - |
dc.subject | Cognitive Radio Network | - |
dc.subject | Rendezvous | - |
dc.subject | Heterogeneous Sensing Capability | - |
dc.subject | Distributed Algorithm | - |
dc.title | On Heterogeneous Sensing Capability for Distributed Rendezvous in Cognitive Radio Networks | - |
dc.type | Article | - |
dc.identifier.email | Wang, Y: amywang@hku.hk | - |
dc.identifier.email | Lau, FCM: fcmlau@cs.hku.hk | - |
dc.identifier.authority | Lau, FCM=rp00221 | - |
dc.description.nature | link_to_subscribed_fulltext | - |
dc.identifier.doi | 10.1109/TMC.2020.2997077 | - |
dc.identifier.scopus | eid_2-s2.0-85117186762 | - |
dc.identifier.hkuros | 313329 | - |
dc.identifier.volume | 20 | - |
dc.identifier.issue | 11 | - |
dc.identifier.spage | 3211 | - |
dc.identifier.epage | 3226 | - |
dc.identifier.isi | WOS:000702553000008 | - |
dc.publisher.place | United States | - |
dc.identifier.issnl | 1536-1233 | - |