Design of Smart Antenna for 5G Network Using Array Synthesis Methods and Leaky LMS Algorithm
5G antenna arrays are being designed to generate a dedicated stream of data for every single user. This results in more capacity and speed over the network along with the least possible latency rate. Depending upon the direction of the user demanding internet access, the beam can be steered in that...
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| Published in | Wireless personal communications Vol. 129; no. 4; pp. 2829 - 2841 |
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| Main Authors | , , |
| Format | Journal Article |
| Language | English |
| Published |
New York
Springer US
01.04.2023
Springer Nature B.V |
| Subjects | |
| Online Access | Get full text |
| ISSN | 0929-6212 1572-834X |
| DOI | 10.1007/s11277-023-10260-3 |
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| Abstract | 5G antenna arrays are being designed to generate a dedicated stream of data for every single user. This results in more capacity and speed over the network along with the least possible latency rate. Depending upon the direction of the user demanding internet access, the beam can be steered in that direction. Meanwhile, the occurrence of side lobes in such systems can be menacing. The smart antenna is a pivotal technology for modern cellular communication. It helps the user’s signal to determine the direction of arrival It also estimates antenna arrays using an adaptive signal processing algorithm that produces a radiation beam for communication. This work presents beamforming for uniform linear smart antenna array using leaky least mean square algorithm and side lobe level reduction using array synthesis methods like Tchebycheff and Taylor distribution. Multiple interferers are considered for the smart antenna. Here, one of the aims is to reduce side lobe levels nearer to the main beam which can enhance more efficient frequency reuse in a cellular network. Side lobe level is reduced up to about 16 dB that enacted for signal-to-noise ratio to 20 dB. |
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| AbstractList | 5G antenna arrays are being designed to generate a dedicated stream of data for every single user. This results in more capacity and speed over the network along with the least possible latency rate. Depending upon the direction of the user demanding internet access, the beam can be steered in that direction. Meanwhile, the occurrence of side lobes in such systems can be menacing. The smart antenna is a pivotal technology for modern cellular communication. It helps the user’s signal to determine the direction of arrival It also estimates antenna arrays using an adaptive signal processing algorithm that produces a radiation beam for communication. This work presents beamforming for uniform linear smart antenna array using leaky least mean square algorithm and side lobe level reduction using array synthesis methods like Tchebycheff and Taylor distribution. Multiple interferers are considered for the smart antenna. Here, one of the aims is to reduce side lobe levels nearer to the main beam which can enhance more efficient frequency reuse in a cellular network. Side lobe level is reduced up to about 16 dB that enacted for signal-to-noise ratio to 20 dB. 5G antenna arrays are being designed to generate a dedicated stream of data for every single user. This results in more capacity and speed over the network along with the least possible latency rate. Depending upon the direction of the user demanding internet access, the beam can be steered in that direction. Meanwhile, the occurrence of side lobes in such systems can be menacing. The smart antenna is a pivotal technology for modern cellular communication. It helps the user’s signal to determine the direction of arrival It also estimates antenna arrays using an adaptive signal processing algorithm that produces a radiation beam for communication. This work presents beamforming for uniform linear smart antenna array using leaky least mean square algorithm and side lobe level reduction using array synthesis methods like Tchebycheff and Taylor distribution. Multiple interferers are considered for the smart antenna. Here, one of the aims is to reduce side lobe levels nearer to the main beam which can enhance more efficient frequency reuse in a cellular network. Side lobe level is reduced up to about 16 dB that enacted for signal-to-noise ratio to 20 dB. |
| Author | Patro, B. S. Roy, Jibendu Sekhar Senapati, Anupama |
| Author_xml | – sequence: 1 givenname: Anupama orcidid: 0000-0002-6935-5710 surname: Senapati fullname: Senapati, Anupama email: senapati.anupama@gmail.com organization: School of Electronics Engineering, Kalinga Institute of Industrial Technology – sequence: 2 givenname: B. S. surname: Patro fullname: Patro, B. S. organization: School of Electronics Engineering, Kalinga Institute of Industrial Technology – sequence: 3 givenname: Jibendu Sekhar surname: Roy fullname: Roy, Jibendu Sekhar organization: School of Electronics Engineering, Kalinga Institute of Industrial Technology |
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| Cites_doi | 10.1109/MAP.2002.1039395 10.11648/j.ajea.20140203.11 10.1109/5.622504 10.1007/s11277-012-0879-9 10.1007/s11633-017-1087-6 10.1088/2631-8695/ac9114 10.1080/00207217.2014.905993 10.1007/s11277-021-09417-9 10.1002/0471722839 10.3390/sym13030480 10.1007/s11277-019-06764-6 10.1109/JSEN.2018.2848632 10.1109/74.848965 10.1109/EDCT.2018.8405082 10.1109/ICCSP.2015.7322822 10.1109/ACSSC.2004.1399103 10.1109/ICECTE.2016.7879566 10.1109/CERA.2017.8343312 |
| ContentType | Journal Article |
| Copyright | The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2023. |
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| Keywords | Side lobe level Tchebycheff distribution Beamforming Leaky least mean square Smart antenna Taylor distribution |
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| References_xml | – ident: CR22 – volume: 2014 start-page: 1 year: 2014 end-page: 10 ident: CR7 article-title: Adaptive beamforming based on complex quaternion processes publication-title: Mathematical Problems in Engineering, Hindawi – volume: 13 start-page: 44 year: 2014 end-page: 50 ident: CR5 article-title: Adaptive beamforming algorithms for smart antenna systems publication-title: WSEAS Transaction on Communications – ident: CR14 – volume: 44 start-page: 145 issue: 3 year: 2002 end-page: 154 ident: CR4 article-title: Smart-antenna systems for mobile communication network, part 1, overview and antenna design publication-title: IEEE Antennas and Propagation Magazine doi: 10.1109/MAP.2002.1039395 – year: 2005 ident: CR21 publication-title: Antenna theory–analysis and design – volume: 12 start-page: 716 issue: 3 year: 2017 end-page: 724 ident: CR12 article-title: Adaptive beamforming in smart antenna using tchebyscheff distribution and variants of least mean square algorithm 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| SubjectTerms | 5G mobile communication Adaptive algorithms Algorithms Antenna arrays Antenna design Antennas Arrays Beamforming Cellular communication Communications Engineering Computer Communication Networks Direction of arrival Engineering Frequency reuse Network latency Networks Noise levels Parameter estimation Radiation Sidelobe reduction Sidelobes Signal processing Signal to noise ratio Signal,Image and Speech Processing Synthesis |
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| Title | Design of Smart Antenna for 5G Network Using Array Synthesis Methods and Leaky LMS Algorithm |
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