Cross layer protocol architecture for spectrum‐based routing in cognitive radio networks
Abstract New cell phone services and apps consume more spectrum. Wireless spectrum allows services and apps to communicate with one another. Wi‐Fi quality is improved via smart spectrum usage and new CRT services. The use of spectrum is beneficial. Cross‐layer architecture improves the energy effici...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2024-01-01
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| Series: | IET Networks |
| Subjects: | |
| Online Access: | https://doi.org/10.1049/ntw2.12101 |
| _version_ | 1797353945271631872 |
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| author | R. Sri Uma Suseela Korlapati Satyanarayana Murthy Hima Bindu Valiveti Mohammad Akhtaruzzaman |
| author_facet | R. Sri Uma Suseela Korlapati Satyanarayana Murthy Hima Bindu Valiveti Mohammad Akhtaruzzaman |
| author_sort | R. Sri Uma Suseela |
| collection | DOAJ |
| description | Abstract New cell phone services and apps consume more spectrum. Wireless spectrum allows services and apps to communicate with one another. Wi‐Fi quality is improved via smart spectrum usage and new CRT services. The use of spectrum is beneficial. Cross‐layer architecture improves the energy efficiency of wireless networks. System performance is improved by connecting protocol layers. Cross‐layer configuration does not introduce layer functionality into a network. By protecting networks, cross‐layer design increases communication. C‐LNRD uses self‐determined time slots to promote communication. Agents that collect information. At each level, the monitoring agent monitors traffic, time, and topology. Each layer of agents has its own database. Data is received by the network, MAC, and physical layers. Based on its measurements, each node grants trust. Routes were altered. PR ATTACK does not have RTS, CTS, or RREQ to reduce false positives. Spectrum allocation is improved via cognitive radio and learning technologies. Adaptive Cognitive Radio Networks are created using AI, GA, Fuzzy Logic, and Game Theory (ACRN). DSA creates high‐bandwidth MCRNs. This research looks at MCRNs in order to optimise spectrum usage, throughput, routing delay, and overhead. Multihop, the proposed approach by CRN takes into account spectrum awareness, quality route establishment, and route maintenance in the event that a connection fails due to spectrum or a node transfer. New strategies improve the cross‐layer network protocols of MCRN. Learners gain from spectrum models. Sensors and routers are linked by layers. The proposed routing improves both performance and spectrum use. |
| first_indexed | 2024-03-08T13:38:16Z |
| format | Article |
| id | doaj.art-5afd04b379ed42e99f2610f121407de5 |
| institution | Directory Open Access Journal |
| issn | 2047-4954 2047-4962 |
| language | English |
| last_indexed | 2024-03-08T13:38:16Z |
| publishDate | 2024-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | IET Networks |
| spelling | doaj.art-5afd04b379ed42e99f2610f121407de52024-01-16T13:54:07ZengWileyIET Networks2047-49542047-49622024-01-01131586510.1049/ntw2.12101Cross layer protocol architecture for spectrum‐based routing in cognitive radio networksR. Sri Uma Suseela0Korlapati Satyanarayana Murthy1Hima Bindu Valiveti2Mohammad Akhtaruzzaman3Department of ECE KLEF Vijayawada Andhra Pradesh IndiaDepartment of ECE KLEF Vijayawada Andhra Pradesh IndiaDepartment of ECE GRIET Hyderabad Telangana IndiaDepartment of CSE Asian University of Bangladesh Dhaka BangladeshAbstract New cell phone services and apps consume more spectrum. Wireless spectrum allows services and apps to communicate with one another. Wi‐Fi quality is improved via smart spectrum usage and new CRT services. The use of spectrum is beneficial. Cross‐layer architecture improves the energy efficiency of wireless networks. System performance is improved by connecting protocol layers. Cross‐layer configuration does not introduce layer functionality into a network. By protecting networks, cross‐layer design increases communication. C‐LNRD uses self‐determined time slots to promote communication. Agents that collect information. At each level, the monitoring agent monitors traffic, time, and topology. Each layer of agents has its own database. Data is received by the network, MAC, and physical layers. Based on its measurements, each node grants trust. Routes were altered. PR ATTACK does not have RTS, CTS, or RREQ to reduce false positives. Spectrum allocation is improved via cognitive radio and learning technologies. Adaptive Cognitive Radio Networks are created using AI, GA, Fuzzy Logic, and Game Theory (ACRN). DSA creates high‐bandwidth MCRNs. This research looks at MCRNs in order to optimise spectrum usage, throughput, routing delay, and overhead. Multihop, the proposed approach by CRN takes into account spectrum awareness, quality route establishment, and route maintenance in the event that a connection fails due to spectrum or a node transfer. New strategies improve the cross‐layer network protocols of MCRN. Learners gain from spectrum models. Sensors and routers are linked by layers. The proposed routing improves both performance and spectrum use.https://doi.org/10.1049/ntw2.121015G mobile communicationcognitive radiosoftware radio |
| spellingShingle | R. Sri Uma Suseela Korlapati Satyanarayana Murthy Hima Bindu Valiveti Mohammad Akhtaruzzaman Cross layer protocol architecture for spectrum‐based routing in cognitive radio networks IET Networks 5G mobile communication cognitive radio software radio |
| title | Cross layer protocol architecture for spectrum‐based routing in cognitive radio networks |
| title_full | Cross layer protocol architecture for spectrum‐based routing in cognitive radio networks |
| title_fullStr | Cross layer protocol architecture for spectrum‐based routing in cognitive radio networks |
| title_full_unstemmed | Cross layer protocol architecture for spectrum‐based routing in cognitive radio networks |
| title_short | Cross layer protocol architecture for spectrum‐based routing in cognitive radio networks |
| title_sort | cross layer protocol architecture for spectrum based routing in cognitive radio networks |
| topic | 5G mobile communication cognitive radio software radio |
| url | https://doi.org/10.1049/ntw2.12101 |
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