Enhancement of In-Building small cells network planning design


Khor, Fang Cheng (2023) Enhancement of In-Building small cells network planning design. Masters thesis, Multimedia University.

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Official URL: http://erep.mmu.edu.my/


In recent years, mobile networks have seen significant advancements, resulting in faster, more reliable, and more efficient networks. However, indoor mobile network coverage and capacity still pose major challenges for network operators, especially with the exponential growth of in-building mobile data traffic. This is due to the lack of a systematic design methodology for commercial in-building mobile networks and the absence of solutions for designing and optimizing the deployment cost of in-building small cell networks for sub-6GHz mobile networks. To address these challenges, this work proposes an Enhanced In-Building Small Cells Network Planning Algorithm (ESCNP) that optimizes the in-building mobile network for all indoor mobile network users while reducing construction costs and maximizing profit. The ESCNP algorithm consists of two modules, i.e. the small cells deployment module, and the circuit routes and splitters planning module. The proposed algorithm is tested at the Sarawak General Hospital and five commercial frequency spectrums, i.e. 900 MHz, 1800 MHz, 2100 MHz, 2300 MHz, and 2600MHzareevaluated. To evaluate the effectiveness of the proposed algorithm, the simulation network planning was carried out for various commercial frequency spectrums, and the Reference Signal Received Power (RSRP) strength values were used. The proposed ESCNP successfully provided 100% good network coverage with a 27.64%cost savings compared to the design without ESCNP for sub-6GHz in-building mobile networks. Overall, this work presents a novel ESCNP algorithm that provides a low-cost and high-efficiency in-building mobile network for all indoor mobile network users, and the proposed algorithm can significantly improve the cost-effectiveness of in-building mobile networks and provide good in-building network coverage.

Item Type: Thesis (Masters)
Additional Information: Call No.: QA9.58 .K46 2023
Uncontrolled Keywords: Algorithms
Subjects: Q Science > QA Mathematics
Divisions: Faculty of Engineering (FOE)
Depositing User: Ms Nurul Iqtiani Ahmad
Date Deposited: 27 Nov 2023 04:46
Last Modified: 27 Nov 2023 04:46
URII: http://shdl.mmu.edu.my/id/eprint/11852


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