Study of Optimal Base Station Deployment for UAM Operations in an Urban Environment Based on a Genetic Algorithm
In this paper, we propose a method for determining the optimal base station deployment to establish a stable communication environment for urban air mobility (UAM) operation in urban areas. To realistically model the UAM operating environment, we utilize DEM files that include data on terrain and bu...
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2025-01-01
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| author | Minsang Yoon Jiseok Park Bosung Park Taekyeong Jin Hosung Choo |
| author_facet | Minsang Yoon Jiseok Park Bosung Park Taekyeong Jin Hosung Choo |
| author_sort | Minsang Yoon |
| collection | DOAJ |
| description | In this paper, we propose a method for determining the optimal base station deployment to establish a stable communication environment for urban air mobility (UAM) operation in urban areas. To realistically model the UAM operating environment, we utilize DEM files that include data on terrain and buildings. Furthermore, the radiation patterns of the BS’s antenna are generated according to the 3GPP-standard, and the receiver antenna patterns are obtained through analysis of the UAM’s mounted antenna. The proposed method uses binary chromosomes to determine the locations of BSs and the orientations of the antennas. A genetic algorithm is then used to determine the optimal deployment of the base stations. When applying the proposed method to optimize BS deployment in the UAM corridor (area of approximately 5.4 km<inline-formula> <tex-math notation="LaTeX">${}^{\mathbf {2}}$ </tex-math></inline-formula>), the optimization process resulted in the deployment of two base stations at 3.5 GHz, achieving an average received power of −61.36 dBm across the corridor. At 5.4 GHz, three base stations are deployed, with an average received power of −63.74 dBm. To validate the reliability of the simulation, measurements are conducted in a real urban environment, comparing the results from measurement, theory, and simulation. The received power values obtained from measurement, theory, and simulation are −110.21 dBm, −110.82 dBm, and −110.38 dBm, respectively. These results demonstrate that the proposed BS deployment method can be used to establish a stable communication environment in a real UAM corridor. |
| format | Article |
| id | doaj-art-cb4f3a4cee684d13abfbd4c19db4089d |
| institution | Kabale University |
| issn | 2169-3536 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | IEEE |
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| spelling | doaj-art-cb4f3a4cee684d13abfbd4c19db4089d2025-08-20T03:56:49ZengIEEEIEEE Access2169-35362025-01-011312757012757910.1109/ACCESS.2025.359006911083567Study of Optimal Base Station Deployment for UAM Operations in an Urban Environment Based on a Genetic AlgorithmMinsang Yoon0https://orcid.org/0009-0008-6654-9772Jiseok Park1https://orcid.org/0009-0004-6406-182XBosung Park2https://orcid.org/0009-0003-9900-7260Taekyeong Jin3https://orcid.org/0009-0003-8712-5366Hosung Choo4https://orcid.org/0000-0002-8409-6964Department of Electronic and Electrical Engineering, Hongik University, Seoul, South KoreaDepartment of Electronic and Electrical Engineering, Hongik University, Seoul, South KoreaDepartment of Electronic and Electrical Engineering, Hongik University, Seoul, South KoreaDepartment of Electronic and Electrical Engineering, Hongik University, Seoul, South KoreaDepartment of Electronic and Electrical Engineering, Hongik University, Seoul, South KoreaIn this paper, we propose a method for determining the optimal base station deployment to establish a stable communication environment for urban air mobility (UAM) operation in urban areas. To realistically model the UAM operating environment, we utilize DEM files that include data on terrain and buildings. Furthermore, the radiation patterns of the BS’s antenna are generated according to the 3GPP-standard, and the receiver antenna patterns are obtained through analysis of the UAM’s mounted antenna. The proposed method uses binary chromosomes to determine the locations of BSs and the orientations of the antennas. A genetic algorithm is then used to determine the optimal deployment of the base stations. When applying the proposed method to optimize BS deployment in the UAM corridor (area of approximately 5.4 km<inline-formula> <tex-math notation="LaTeX">${}^{\mathbf {2}}$ </tex-math></inline-formula>), the optimization process resulted in the deployment of two base stations at 3.5 GHz, achieving an average received power of −61.36 dBm across the corridor. At 5.4 GHz, three base stations are deployed, with an average received power of −63.74 dBm. To validate the reliability of the simulation, measurements are conducted in a real urban environment, comparing the results from measurement, theory, and simulation. The received power values obtained from measurement, theory, and simulation are −110.21 dBm, −110.82 dBm, and −110.38 dBm, respectively. These results demonstrate that the proposed BS deployment method can be used to establish a stable communication environment in a real UAM corridor.https://ieeexplore.ieee.org/document/11083567/Urban air mobilitybase station deploymentgenetic algorithmelectromagnetic wave propagationray-tracing |
| spellingShingle | Minsang Yoon Jiseok Park Bosung Park Taekyeong Jin Hosung Choo Study of Optimal Base Station Deployment for UAM Operations in an Urban Environment Based on a Genetic Algorithm IEEE Access Urban air mobility base station deployment genetic algorithm electromagnetic wave propagation ray-tracing |
| title | Study of Optimal Base Station Deployment for UAM Operations in an Urban Environment Based on a Genetic Algorithm |
| title_full | Study of Optimal Base Station Deployment for UAM Operations in an Urban Environment Based on a Genetic Algorithm |
| title_fullStr | Study of Optimal Base Station Deployment for UAM Operations in an Urban Environment Based on a Genetic Algorithm |
| title_full_unstemmed | Study of Optimal Base Station Deployment for UAM Operations in an Urban Environment Based on a Genetic Algorithm |
| title_short | Study of Optimal Base Station Deployment for UAM Operations in an Urban Environment Based on a Genetic Algorithm |
| title_sort | study of optimal base station deployment for uam operations in an urban environment based on a genetic algorithm |
| topic | Urban air mobility base station deployment genetic algorithm electromagnetic wave propagation ray-tracing |
| url | https://ieeexplore.ieee.org/document/11083567/ |
| work_keys_str_mv | AT minsangyoon studyofoptimalbasestationdeploymentforuamoperationsinanurbanenvironmentbasedonageneticalgorithm AT jiseokpark studyofoptimalbasestationdeploymentforuamoperationsinanurbanenvironmentbasedonageneticalgorithm AT bosungpark studyofoptimalbasestationdeploymentforuamoperationsinanurbanenvironmentbasedonageneticalgorithm AT taekyeongjin studyofoptimalbasestationdeploymentforuamoperationsinanurbanenvironmentbasedonageneticalgorithm AT hosungchoo studyofoptimalbasestationdeploymentforuamoperationsinanurbanenvironmentbasedonageneticalgorithm |