Academic Journal
Comparative analysis and optimization of path loss models for small cell wireless communication systems
| Title: | Comparative analysis and optimization of path loss models for small cell wireless communication systems |
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| Authors: | Chilakala Sudhamani, Mardeni Roslee, Lee Loo Chuan, Athar Waseem, Anwar Faizd Osman, Mohamad Huzaimy Jusoh, Yasir Ullah |
| Source: | Cogent Engineering, Vol 11, Iss 1 (2024) |
| Publisher Information: | Taylor & Francis Group, 2024. |
| Publication Year: | 2024 |
| Collection: | LCC:Engineering (General). Civil engineering (General) |
| Subject Terms: | 5G, urban micro-environment, path loss model, error statistics, optimization, genetic algorithm, Engineering (General). Civil engineering (General), TA1-2040 |
| More Details: | Nowadays, a precise assessment of path loss is essential to the efficient design and functioning of wireless communication networks. This research explores path loss evaluation and comparison using models designed for urban-micro scenarios. The article also looks into how these path loss models might be optimized using a genetic algorithm to more accurately simulate actual propagation paths. Analytic path loss measurements are determined by thorough analysis to closely match optimal values for every model, and error statistics are used to evaluate model performance in a comprehensive manner. The root mean square error of the study reveals that the 5th Generation Channel Model (5GCM) open square demonstrates the most favorable performance, exhibiting the lowest mean square error of 2.33 dB and standard deviation of 2.33 dB values. Operators of 5 G small cell networks have the opportunity to greatly improve service quality by utilizing this optimization technique, especially at millimeter wave frequencies. Such developments have the potential to completely transform the user experience in urban micro-environments in addition to optimizing wireless communication infrastructure. |
| Document Type: | article |
| File Description: | electronic resource |
| Language: | English |
| ISSN: | 23311916 2331-1916 |
| Relation: | https://doaj.org/toc/2331-1916 |
| DOI: | 10.1080/23311916.2024.2402894 |
| Access URL: | https://doaj.org/article/5720105a2e204066ab35a1697b8af120 |
| Accession Number: | edsdoj.5720105a2e204066ab35a1697b8af120 |
| Database: | Directory of Open Access Journals |
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| ISSN: | 23311916 |
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| DOI: | 10.1080/23311916.2024.2402894 |
| Published in: | Cogent Engineering |
| Language: | English |