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Jayanthiladevi, A.
- Handoff in 5g Ultra Dense Networks Using Fixed Sphere Precoding
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Authors
Affiliations
1 College of Computer Science and Information Science, Srinivas University, IN
1 College of Computer Science and Information Science, Srinivas University, IN
Source
ICTACT Journal on Communication Technology, Vol 13, No 2 (2022), Pagination: 2689-2693Abstract
It is anticipated that the millimetrewave, often known as mm-wave, technology that will be used in 5G networks will greatly enhance network capacity. The mm-wave signals, on the other hand, are prone to obstructions than the ones at lower bands; this demonstrates the impact that route loss has on the network coverage. Because of the fractal nature of cellular coverage and the different path loss exponents that apply to different directions, it has been suggested that a route loss model in a multi-directional manner for 5G UDN networks. This is due to the fact that different directions have path loss exponents. In addition, the proposed loss model is applied to the 5G ultra-dense network in order to calculate the coverage probability, association probability, and handoff probability (UDN). According to the numerical findings of this research, in 5G UDN, the influence of anisotropic path loss increases the association probability with long link distance. It has also come to light that the performance of the handoff suffers tremendously as a consequence of the anisotropic propagation environment. A new difficulty has arisen for 5G UDN as a consequence of the substantial handoff overhead that has been produced.Keywords
Fractal Characteristics, Multi-Directional Path Loss, Cellular Coverage Ultra-Dense NetworkReferences
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- Detection of Cyber Attack on Internet of Vehicle Commuters
Abstract Views :104 |
PDF Views:0
Authors
Affiliations
1 Institute of Computer Science and Information Science, Srinivas University, India., IN
2 Department of Mathematics and Computer Science, University of Africa, Nigeria., NG
1 Institute of Computer Science and Information Science, Srinivas University, India., IN
2 Department of Mathematics and Computer Science, University of Africa, Nigeria., NG
Source
ICTACT Journal on Communication Technology, Vol 14, No 1 (2023), Pagination: 2876-2881Abstract
The Internet of Vehicles (IoV) is a massive interactive network that can be extended into the realm of smart transportation by utilizing IoV at scale because it is capable of attaining unified management. It is well known that the gathered contents not only contain personal information, but also certain critical data, such as a vehicle running parameter, which is strongly related to traffic safety. This study explains how a network intrusion detection system (IDS) based on artificial intelligence can be deployed over various datasets. The simulation is carried out in an extensive way and the results show that the proposed method achieves a higher rate of accuracy in detecting the instances than the other existing methods.Keywords
Internet of Vehicles, Intrusion Detection System, Traffic System, Vehicle Commuters.References
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