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  • Open Access

    ARTICLE

    A Base Station Deployment Algorithm for Wireless Positioning Considering Dynamic Obstacles

    Aiguo Li1, Yunfei Jia2,*

    CMC-Computers, Materials & Continua, Vol.82, No.3, pp. 4573-4591, 2025, DOI:10.32604/cmc.2025.059184 - 06 March 2025

    Abstract In the context of security systems, adequate signal coverage is paramount for the communication between security personnel and the accurate positioning of personnel. Most studies focus on optimizing base station deployment under the assumption of static obstacles, aiming to maximize the perception coverage of wireless RF (Radio Frequency) signals and reduce positioning blind spots. However, in practical security systems, obstacles are subject to change, necessitating the consideration of base station deployment in dynamic environments. Nevertheless, research in this area still needs to be conducted. This paper proposes a Dynamic Indoor Environment Beacon Deployment Algorithm (DIE-BDA)… More >

  • Open Access

    ARTICLE

    Evolutionary Particle Swarm Optimization Algorithm Based on Collective Prediction for Deployment of Base Stations

    Jiaying Shen1, Donglin Zhu1, Yujia Liu2, Leyi Wang1, Jialing Hu1, Zhaolong Ouyang1, Changjun Zhou1, Taiyong Li3,*

    CMC-Computers, Materials & Continua, Vol.82, No.1, pp. 345-369, 2025, DOI:10.32604/cmc.2024.060335 - 03 January 2025

    Abstract The wireless signals emitted by base stations serve as a vital link connecting people in today’s society and have been occupying an increasingly important role in real life. The development of the Internet of Things (IoT) relies on the support of base stations, which provide a solid foundation for achieving a more intelligent way of living. In a specific area, achieving higher signal coverage with fewer base stations has become an urgent problem. Therefore, this article focuses on the effective coverage area of base station signals and proposes a novel Evolutionary Particle Swarm Optimization (EPSO)… More >

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