Joint Downlink Power and Time-Slot Allocation for Distributed Satellite Cluster Network Based on Pareto Optimization
In this paper, we design a novel architecture of distributed satellite cluster network (DSCN). In order to achieve a good trade-off between the energy consumption and the total capacity, we investigate the joint downlink power and time-slot allocation problem, taking into account the limitation of r...
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| Format: | Article |
| Language: | English |
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IEEE
2017-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/8086140/ |
| _version_ | 1818369787382726656 |
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| author | Xudong Zhong Hao Yin Yuanzhi He Yuzhen Huang |
| author_facet | Xudong Zhong Hao Yin Yuanzhi He Yuzhen Huang |
| author_sort | Xudong Zhong |
| collection | DOAJ |
| description | In this paper, we design a novel architecture of distributed satellite cluster network (DSCN). In order to achieve a good trade-off between the energy consumption and the total capacity, we investigate the joint downlink power and time-slot allocation problem, taking into account the limitation of resource, collaborative coverage of multi-satellite, and dynamism, which is proved to be a Pareto optimization and NP-hard problem. Different from the existing 1-D multi-objective optimization algorithm (1D-MOA) based on meta-heuristics, such as immune clonal algorithm (ICA), we propose an improved 2-D dynamic immune clonal algorithm (TDICA) to search the solution space for approaching the Pareto front. From simulation results, several important concluding remarks are obtained as follows: 1) the proposed TDICA can obtain more non-dominated solutions in each iteration with better accuracy than existing algorithms; 2) with inter-satellite resource optimization, the total capacity can be improved; 3) compared with 1D-MOAs, the 2D-MOA can save more energy and achieve higher total capacity; d) MOAs can be transferred into multiple single-objective optimization algorithms (SOAs) under certain conditions. |
| first_indexed | 2024-12-13T23:29:23Z |
| format | Article |
| id | doaj.art-1200710608db448f8cb88dee1a9d5406 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-13T23:29:23Z |
| publishDate | 2017-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-1200710608db448f8cb88dee1a9d54062022-12-21T23:27:27ZengIEEEIEEE Access2169-35362017-01-015250812509610.1109/ACCESS.2017.27670618086140Joint Downlink Power and Time-Slot Allocation for Distributed Satellite Cluster Network Based on Pareto OptimizationXudong Zhong0https://orcid.org/0000-0003-1847-3677Hao Yin1Yuanzhi He2Yuzhen Huang3https://orcid.org/0000-0002-9536-7918College of Communications Engineering, Army Engineering University of PLA, Nanjing, ChinaInstitute of Electronic System Engineering, Beijing, ChinaInstitute of Electronic System Engineering, Beijing, ChinaCollege of Communications Engineering, Army Engineering University of PLA, Nanjing, ChinaIn this paper, we design a novel architecture of distributed satellite cluster network (DSCN). In order to achieve a good trade-off between the energy consumption and the total capacity, we investigate the joint downlink power and time-slot allocation problem, taking into account the limitation of resource, collaborative coverage of multi-satellite, and dynamism, which is proved to be a Pareto optimization and NP-hard problem. Different from the existing 1-D multi-objective optimization algorithm (1D-MOA) based on meta-heuristics, such as immune clonal algorithm (ICA), we propose an improved 2-D dynamic immune clonal algorithm (TDICA) to search the solution space for approaching the Pareto front. From simulation results, several important concluding remarks are obtained as follows: 1) the proposed TDICA can obtain more non-dominated solutions in each iteration with better accuracy than existing algorithms; 2) with inter-satellite resource optimization, the total capacity can be improved; 3) compared with 1D-MOAs, the 2D-MOA can save more energy and achieve higher total capacity; d) MOAs can be transferred into multiple single-objective optimization algorithms (SOAs) under certain conditions.https://ieeexplore.ieee.org/document/8086140/Distributed satellite cluster network (DSCN)resource allocationmulti-objective optimization algorithm (MOA)Pareto optimization |
| spellingShingle | Xudong Zhong Hao Yin Yuanzhi He Yuzhen Huang Joint Downlink Power and Time-Slot Allocation for Distributed Satellite Cluster Network Based on Pareto Optimization IEEE Access Distributed satellite cluster network (DSCN) resource allocation multi-objective optimization algorithm (MOA) Pareto optimization |
| title | Joint Downlink Power and Time-Slot Allocation for Distributed Satellite Cluster Network Based on Pareto Optimization |
| title_full | Joint Downlink Power and Time-Slot Allocation for Distributed Satellite Cluster Network Based on Pareto Optimization |
| title_fullStr | Joint Downlink Power and Time-Slot Allocation for Distributed Satellite Cluster Network Based on Pareto Optimization |
| title_full_unstemmed | Joint Downlink Power and Time-Slot Allocation for Distributed Satellite Cluster Network Based on Pareto Optimization |
| title_short | Joint Downlink Power and Time-Slot Allocation for Distributed Satellite Cluster Network Based on Pareto Optimization |
| title_sort | joint downlink power and time slot allocation for distributed satellite cluster network based on pareto optimization |
| topic | Distributed satellite cluster network (DSCN) resource allocation multi-objective optimization algorithm (MOA) Pareto optimization |
| url | https://ieeexplore.ieee.org/document/8086140/ |
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