期刊
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
卷 68, 期 8, 页码 8075-8090出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TVT.2019.2924669
关键词
Integrated terrestrial-satellite network; multigroup precoding; power allocation; clustering algorithm; convex optimization
资金
- New Strategic Industries Development Projects of Shenzhen City [JCYJ20170816151922176]
- National Nature Science Foundation of China [91638205, 91538203, 61621091, 91738101]
- Nantong Science and Technology Bureau [GY22016058]
The integrated terrestrial-satellite network (ITSN) combines cellular networks and satellite networks to provide services for the ever-increasing users, where the coexistence of the two systems can not only highlight their advantages but also bring serious interference. Confronted with the target of maximizing the network capacity and ensuring the quality-of-service (QoS) for large number of users, we propose a framework-involved joint optimization of the multigroup precoding and resource allocation in the ITSN. In the multigroup precoding, we ameliorate the interference by optimizing the user access scheme, where the users with weak correlation on channel state information are distributed into the same group, such that all the users are divided into multiple groups and served at different time slots. To realize this multigroup precoding, first, we propose the multilevel clustering based grouping approach to obtain the groups in each cell or satellite. Second, we match those groups at different time slots to minimize intra-system interference and inter-system interference according to the proposed shortest path pairing algorithm and satellite users precoding method, respectively. In the resource allocation, we first transform the complicated non-convex problem into multiple convex subproblems, and then propose the collaborative power allocation method to optimize the power control for the whole network. Our simulation results show that the joint multigroup precoding and the resource allocation method is superior to the existing algorithms in terms of system capacity and QoS, which can significantly improve the performance of the ITSN.
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