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  4. Vol 8, Issue 1, 2024

Wireless Communication Base Station Location Selection and Network Optimization Based on Neural Network Algorithm

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DOI: 10.23977/cpcs.2024.080105 | Downloads: 7 | Views: 95

Author(s)

Yi Yao 1

Affiliation(s)

1 Department of Information Science and Engineering, Hunan University of Humanities, Science and Technology, Loudi, Hunan, 417000, China

Corresponding Author

Yi Yao

ABSTRACT

Base station location selection and network optimization are critical to improving the performance of wireless communication networks in terms of latency reduction. To this end, the article proposes leveraging a convolutional neural network (CNN) to improve the accuracy of base station location selection and network latency reduction. The CNN method, based on a three-dimensional representation including signal strength data set, network topology data set, and transmission path data set, is used to select base station location and optimize the multihop relay network for latency reduction. The article presents a following method: location selection and network optimization for the wireless communication network. First, it collects the experimental data set of base station location selection and network optimization, and then uses the training data to train the CNN model to extract features. Once the training is done, the article further optimizes the network parameters and configurations, and ultimately obtains the optimal base station location and network configuration while minimizing network latency. As a result, simulation results indicate that the CNN model has remarkable performance in base station location selection, as well as in network optimization. In summary, the feature extraction and processing ability of CNN are powerful, enabling it to effectively capture factors leading to delay, hence improving the performance of base station location selection and network optimization. The article also demonstrates that the CNN model can be adjusted according to different environments and scenario settings through dynamic tuning.

KEYWORDS

Wireless Communication Base Station Location Selection; Network Optimization; Neural Network Algorithms; Convolutional Neural Network

CITE THIS PAPER

Yi Yao, Wireless Communication Base Station Location Selection and Network Optimization Based on Neural Network Algorithm. Computing, Performance and Communication Systems (2024) Vol. 8: 31-38. DOI: http://dx.doi.org/10.23977/cpcs.2024.080105.

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