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http://hdl.handle.net/10603/592103
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DC Field | Value | Language |
---|---|---|
dc.coverage.spatial | Investigation of various antenna design techniques and received signal strength prediction using machine learning for multiband 5G Application | |
dc.date.accessioned | 2024-09-27T08:50:32Z | - |
dc.date.available | 2024-09-27T08:50:32Z | - |
dc.identifier.uri | http://hdl.handle.net/10603/592103 | - |
dc.description.abstract | The massive growth of mobile data evolution and numerous terminal devices requires a highly efficient mobile data network which affords superior communication. Shortage of available global bandwidth has led to allotment of 200 MHz band to service providers. These demands shift in spectrum up to several GHz for improvisation of quality of service (QoS) and reduced latency etc., using next generation mobile technology. newlineThe objective of this research work is to design suitable multiband antennas supporting frequency band from 2G (2nd Generation) to 5G (5th Generation) for meeting the demands of the current and upcoming 5G wireless technologies, which require incorporation of transceiver antennas for multiple wireless standards such as 2G, 3G, 4G, 5G, WiFi, Wimax, Bluetooth, etc., in a single computing device. This scenario has created a demand for wideband and multiband antennas for multi-standard wireless systems. Various countries have suggested and are working at 5G frequency ranging from 600 MHz to 71 GHz. The lower frequency spectrum is named as sub 6 GHz (Up to 6GHz) band while the higher frequency is known as mm wave spectrum (Above 6GHz). newline newline | |
dc.format.extent | xxii,133p. | |
dc.language | English | |
dc.relation | p.124-132 | |
dc.rights | university | |
dc.title | Investigation of various antenna design techniques and received signal strength prediction using machine learning for multiband 5G Application | |
dc.title.alternative | ||
dc.creator.researcher | Benisha, M | |
dc.subject.keyword | Computer Science | |
dc.subject.keyword | Computer Science Information Systems | |
dc.subject.keyword | Engineering and Technology | |
dc.subject.keyword | GHz for improvisation | |
dc.subject.keyword | global bandwidth | |
dc.subject.keyword | mobile data evolution | |
dc.description.note | ||
dc.contributor.guide | Thulasi Bai, V | |
dc.publisher.place | Chennai | |
dc.publisher.university | Anna University | |
dc.publisher.institution | Faculty of Information and Communication Engineering | |
dc.date.registered | ||
dc.date.completed | 2024 | |
dc.date.awarded | 2024 | |
dc.format.dimensions | 21cm. | |
dc.format.accompanyingmaterial | None | |
dc.source.university | University | |
dc.type.degree | Ph.D. | |
Appears in Departments: | Faculty of Information and Communication Engineering |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
01_title.pdf | Attached File | 87.1 kB | Adobe PDF | View/Open |
02_prelim pages.pdf | 2.67 MB | Adobe PDF | View/Open | |
03_content.pdf | 782.93 kB | Adobe PDF | View/Open | |
04_abstract.pdf | 1.12 MB | Adobe PDF | View/Open | |
05_chapter1.pdf | 3.04 MB | Adobe PDF | View/Open | |
06_chapter2.pdf | 4.11 MB | Adobe PDF | View/Open | |
07_chapter3.pdf | 1.84 MB | Adobe PDF | View/Open | |
08_chapter4.pdf | 1.12 MB | Adobe PDF | View/Open | |
09_chapter5.pdf | 3.24 MB | Adobe PDF | View/Open | |
10_chapter6.pdf | 4 MB | Adobe PDF | View/Open | |
11_chapter7.pdf | 3.24 MB | Adobe PDF | View/Open | |
12_annexures.pdf | 4.53 MB | Adobe PDF | View/Open | |
80_recommendation.pdf | 2.11 MB | Adobe PDF | View/Open |
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