Indoor Visible Light Positioning Based on Improved Particle Swarm Optimization Method With Min-Max Algorithm
In this paper, an improved particle swarm optimization (IPSO) algorithm is proposed to solve the problem of premature convergence and redundant particles of the original PSO used in visible light positioning (VLP) systems. In the proposed IPSO algorithm, an adaptive particle initialization method ba...
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
IEEE
2022-01-01
|
| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/9982447/ |
| _version_ | 1811291195089879040 |
|---|---|
| author | Zhenyu Wang Zhonghua Liang Xunuo Li Hui Li |
| author_facet | Zhenyu Wang Zhonghua Liang Xunuo Li Hui Li |
| author_sort | Zhenyu Wang |
| collection | DOAJ |
| description | In this paper, an improved particle swarm optimization (IPSO) algorithm is proposed to solve the problem of premature convergence and redundant particles of the original PSO used in visible light positioning (VLP) systems. In the proposed IPSO algorithm, an adaptive particle initialization method based on Min-Max algorithm is used to adjust the number of particles and ensure that there are always particles near the target node (TN). Moreover, a nonlinear decreasing strategy of inertia weight is designed to ensure the stability of particle velocity during the iterative process. Simulation results show that, compared with the original PSO algorithm, the averaged positioning accuracy of the proposed IPSO-Min-Max algorithm is enhanced significantly at the expense of limited time consumption. What’s more, we also find that for the proposed IPSO-Min-Max algorithm the increase of particle generation spacing will reduce the positioning delay but with the penalty in positioning accuracy. Therefore, it is necessary to select an appropriate particle spacing value according to specific requirements. |
| first_indexed | 2024-04-13T04:24:44Z |
| format | Article |
| id | doaj.art-339f4d5f958c4e29aebd29c08fbd944c |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-04-13T04:24:44Z |
| publishDate | 2022-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-339f4d5f958c4e29aebd29c08fbd944c2022-12-22T03:02:33ZengIEEEIEEE Access2169-35362022-01-011013006813007710.1109/ACCESS.2022.32285439982447Indoor Visible Light Positioning Based on Improved Particle Swarm Optimization Method With Min-Max AlgorithmZhenyu Wang0https://orcid.org/0000-0002-3130-802XZhonghua Liang1https://orcid.org/0000-0002-7200-6685Xunuo Li2Hui Li3Department of Communication Engineering, School of Information Engineering, Chang’an University, Xi’an, ChinaDepartment of Communication Engineering, School of Information Engineering, Chang’an University, Xi’an, ChinaDepartment of Communication Engineering, School of Information Engineering, Chang’an University, Xi’an, ChinaDepartment of Communication Engineering, School of Information Engineering, Chang’an University, Xi’an, ChinaIn this paper, an improved particle swarm optimization (IPSO) algorithm is proposed to solve the problem of premature convergence and redundant particles of the original PSO used in visible light positioning (VLP) systems. In the proposed IPSO algorithm, an adaptive particle initialization method based on Min-Max algorithm is used to adjust the number of particles and ensure that there are always particles near the target node (TN). Moreover, a nonlinear decreasing strategy of inertia weight is designed to ensure the stability of particle velocity during the iterative process. Simulation results show that, compared with the original PSO algorithm, the averaged positioning accuracy of the proposed IPSO-Min-Max algorithm is enhanced significantly at the expense of limited time consumption. What’s more, we also find that for the proposed IPSO-Min-Max algorithm the increase of particle generation spacing will reduce the positioning delay but with the penalty in positioning accuracy. Therefore, it is necessary to select an appropriate particle spacing value according to specific requirements.https://ieeexplore.ieee.org/document/9982447/Visible light positioning (VLP)particle swarm optimization (PSO)received signal strength (RSS)Min-Max algorithm |
| spellingShingle | Zhenyu Wang Zhonghua Liang Xunuo Li Hui Li Indoor Visible Light Positioning Based on Improved Particle Swarm Optimization Method With Min-Max Algorithm IEEE Access Visible light positioning (VLP) particle swarm optimization (PSO) received signal strength (RSS) Min-Max algorithm |
| title | Indoor Visible Light Positioning Based on Improved Particle Swarm Optimization Method With Min-Max Algorithm |
| title_full | Indoor Visible Light Positioning Based on Improved Particle Swarm Optimization Method With Min-Max Algorithm |
| title_fullStr | Indoor Visible Light Positioning Based on Improved Particle Swarm Optimization Method With Min-Max Algorithm |
| title_full_unstemmed | Indoor Visible Light Positioning Based on Improved Particle Swarm Optimization Method With Min-Max Algorithm |
| title_short | Indoor Visible Light Positioning Based on Improved Particle Swarm Optimization Method With Min-Max Algorithm |
| title_sort | indoor visible light positioning based on improved particle swarm optimization method with min max algorithm |
| topic | Visible light positioning (VLP) particle swarm optimization (PSO) received signal strength (RSS) Min-Max algorithm |
| url | https://ieeexplore.ieee.org/document/9982447/ |
| work_keys_str_mv | AT zhenyuwang indoorvisiblelightpositioningbasedonimprovedparticleswarmoptimizationmethodwithminmaxalgorithm AT zhonghualiang indoorvisiblelightpositioningbasedonimprovedparticleswarmoptimizationmethodwithminmaxalgorithm AT xunuoli indoorvisiblelightpositioningbasedonimprovedparticleswarmoptimizationmethodwithminmaxalgorithm AT huili indoorvisiblelightpositioningbasedonimprovedparticleswarmoptimizationmethodwithminmaxalgorithm |