Optimization of Base Station Placement in 4G LTE Broadband Networks Using Adaptive Variable Length Genetic Algorithm

Nwelih, Emmanuel; Isabona, Joseph; Imoize, Agbotiname Lucky

doi:10.1007/s42979-022-01533-y

SN COMPUT. SCI.

2022

DOI: 10.1007/s42979-022-01533-y

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Optimization of Base Station Placement in 4G LTE Broadband Networks Using Adaptive Variable Length Genetic Algorithm

Emmanuel Nwelih

Joseph Isabona

Agbotiname Lucky Imoize

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Cited by 2 publications

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“…Rodriguez et al [23] analyzed the effect of vehicles' average utilization on the siting in a study on facility location and equipment emplacement led by. Nwelih et al [24] introduced a weighted fitness function that combines coverage, capacity, and transmit power parameters in this field. However, in most of the articles, only the influence of the selection of coordinates for a single type of BS was considered, neglecting the complexity of the practical situation where multiple types of BSs work in combination [25,26].…”

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confidence: 99%

Network Site Optimization and Clustering Study Based on Simulated Annealing Algorithm

Yang,

Wen,

Yan

2023

IEEE Access

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Nowadays, communication networks are becoming increasingly complex. This paper aims to demonstrate an effective method to achieve the intelligent planning for network base stations (BSs). The various parameters such as BS coordinates (x, y), the collaboration of multiple types of BS, and the density of BS construction are taken as design parameters for BS placement. We construct the objective function using the lowest total cost and the total minimum workload of BS to 90%. To solve the problem of siting planning with large data volume and mixed placement of multiple BS, we propose a new practical three-step model for BS siting planning: ( Ⅰ) roughly selecting the alternative coordinates for the BS using the DBSCAN algorithm; (Ⅱ) correcting and further refining the alternative BS coordinates using the K-means algorithm; (Ⅲ) determining the optimal BS construction solution to meet the requirements using simulated annealing algorithm (SAA). The real data of a 2500×2500 area have been used for the simulation test. The simulation result shows that BS placement covers 90.03% of the workload, confirming that the proposed method can handle site planning for large orders of magnitude of data and use a mix of BS to achieve the best economics for the demand. This paper provides basic support for future research on network site optimization. INDEX TERMS DBSCAN algorithm, K-means algorithm, simulated annealing algorithm, base station(BS) planning I. INTRODUCTIONMobile communication technology is proliferating, and the scale of operation is getting bigger, bringing more complex communication networks. With the development of 5G, communication bandwidth is getting bigger. However, the area that BSs can cover is getting smaller, making the number of BSs needed to cover the same area more. In addition, the types of BSs and antennas have also become more varied. Various BSs make the planning of communication networks, especially the problem of station site selection, more complicated. Rational BS placement plays a key role in the massive data exchange and communication within cities, which can reduce government overhead, coordinate the development of communication quality across regions and improve environmental quality. Besides within cities, optimal BS placement is also important: BS location planning at sea [1] can improve the accuracy of landing point, calculation speed of positioning and positioning accuracy of high-speed targets at sea[2]； Most of the BSs were in ruin during rescue and relief in

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confidence: 99%

Network Site Optimization and Clustering Study Based on Simulated Annealing Algorithm

Yang,

Wen,

Yan

2023

IEEE Access

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LTE Cell Planning for Resource Allocation in Emergency Communication

Debnath,

Arif,

Sen

et al. 2024

Wireless Pers Commun

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Optimization of Base Station Placement in 4G LTE Broadband Networks Using Adaptive Variable Length Genetic Algorithm

Cited by 2 publications

References 51 publications

Network Site Optimization and Clustering Study Based on Simulated Annealing Algorithm

Network Site Optimization and Clustering Study Based on Simulated Annealing Algorithm

LTE Cell Planning for Resource Allocation in Emergency Communication

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