An Optimal Algorithm for Feature Activation Based on Cell Value Scoring in the Field of Wireless Communication
Research Article
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An Optimal Algorithm for Feature Activation Based on Cell Value Scoring in the Field of Wireless Communication

Zhuoran Ji 1*
1 School of Electronic Engineering, Beijing University of Posts and Telecommunications, Beijing, China, 100084
*Corresponding author: 2023210522@bupt.cn
Published on 3 September 2025
Journal Cover
ACE Vol.183
ISSN (Print): 2755-273X
ISSN (Online): 2755-2721
ISBN (Print): 978-1-80590-341-3
ISBN (Online): 978-1-80590-342-0
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Abstract

With the increasingly strict assessment of regional mobile operators’ wireless indicator by the wireless communication group, and the need for corresponding licenses and activation fees for the advanced feature algorithms provided by the vendor, regional mobile operators are in urgent need of optimizing a cost - controllable and scenario - based rapid deployment plan for the above - mentioned advanced feature algorithms due to cost control. This paper uses the methods of data analysis and comparative experiments to analyze and study the Key Performance Index (KPI) data of cells provided by regional mobile operators, and proposes an optimal algorithm for feature activation based on cell value scoring. This algorithm aims to solve the problem of how to select cells for deployment when mobile operators deploy specific feature algorithms. The algorithm can balance operating costs and network performance, and help mobile operators make optimal deployment decisions based on data. Based on the experimental KPI data, this algorithm can achieve an approximately optimal effect in terms of improving the Low-Speed network performance, and has a lower time complexity compared with the traditional combination algorithm.

Keywords:

Wireless Communication, Wireless Indicators, Cell Value Scoring, Performance Gain

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Ji,Z. (2025). An Optimal Algorithm for Feature Activation Based on Cell Value Scoring in the Field of Wireless Communication. Applied and Computational Engineering,183,1-6.

References

[1]. Zhu Lilei. Research on 5G User Perception Optimization Speed Improvement and Application. Data Communications. 2021, (02), 11 - 16.

[2]. Fan Zhongyang, Tang Bing, Zhang Xiaodong, Zhao Xin. Research and Practice on 5G User Perceived Speed Improvement. communications Management and Technology. 2021, (01), 46 - 48.

[3]. Chen Yue, Chen Yu, Xu Weihua, Zhang Zhenyi, Guo Hua. Research on the Method of Improving User Perceived Speed in High - value Residential Areas. Information Recording Materials. 2022, 23(03), 196 - 199.

[4]. Qiang Jun. Summary of Optimization Experience for 5G Low - speed Cells. Data Communications. 2025, (02), 37 - 39.

[5]. Hao Yue, Tian Yuqi, Li Xin, Liu Jianhua, Chen Zhuo & Deng Wei. Performance Analysis and Improvement Scheme of MU - MIMO. 5G Network Innovation Seminar (2020), 267-271.

[6]. Jiang Xiaoyu. Test Progress and Performance Analysis of Massive MIMO. Communications World. 2018, (22), 33.

[7]. Xie Liang. Research on LTE Positioning Service System and the Method of Obtaining the Network Identification of the Cell Where the User is Located. Information and Communications Technology and Policy. 2011, (11), 27-30.

[8]. 3GPP TS 28.552-f60: "5G performance measurements (Release 15)". 2019, P11

[9]. Tae Yoon Park, Jong Won Han &   Een Kee Hong.UE throughput guaranteed small cell on/off algorithm with machine learning. Journal of Communications and Networks, 2020, 22(3), 223-229.

[10]. Al Janaby Ali Othman. 5G Downlink Throughput Enhancement by Beams Consolidating at Vacant Traffic. Journal of Communications Software and Systems, 2019, 15(4), 311-316.

Cite this article

Ji,Z. (2025). An Optimal Algorithm for Feature Activation Based on Cell Value Scoring in the Field of Wireless Communication. Applied and Computational Engineering,183,1-6.

Data availability

The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.

About volume

Volume title: Proceedings of CONF-MLA 2025 Symposium: Applied Artificial Intelligence Research

ISBN: 978-1-80590-341-3(Print) / 978-1-80590-342-0(Online)
Editor: Hisham AbouGrad
Conference website: https://2025.confmla.org/
Conference date: 3 September 2025
Series: Applied and Computational Engineering
Volume number: Vol.183
ISSN: 2755-2721(Print) / 2755-273X(Online)