A Survey of the Applications of Evolutionary Computation in Satellite Domain
- Authors
- Sun, Yu; Cao, Zhenyu; Song, Shilun; Jin, Hu
- Issue Date
- Oct-2023
- Publisher
- IEEE Computer Society
- Keywords
- Evolutionary Computation; Satellite
- Citation
- 2023 14th International Conference on Information and Communication Technology Convergence (ICTC), pp 1622 - 1627
- Pages
- 6
- Indexed
- SCOPUS
- Journal Title
- 2023 14th International Conference on Information and Communication Technology Convergence (ICTC)
- Start Page
- 1622
- End Page
- 1627
- URI
- https://scholarworks.bwise.kr/erica/handle/2021.sw.erica/118527
- DOI
- 10.1109/ICTC58733.2023.10392367
- ISSN
- 2162-1233
- Abstract
- Due to the swift progress of transmission technologies, the challenges faced by satellite systems are continually escalating. These challenges encompass not only the heightened complexity in system design, operation, and optimization but also multi-objective trade-offs in power consumption, bandwidth, coverage areas, and so on. Additionally, as satellites form a crucial nexus of global communication, the demand for efficient satellite network design and management is also growing exponentially. While conventional algorithms frequently struggle when dealing with high-dimensional, nonlinear, and multi-constraint problems, evolutionary computation becomes a feasible tool due to its robust global search capabilities, multi-objective optimization techniques, and adaptability to complex systems. This survey explores the various applications of evolutionary computation in the satellite domain, especially focusing on resource allocation, path optimization, signal processing, and network design and management. © 2023 IEEE.
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