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- Title
基于 BP 和 RBF 神经网络的 C-V2X 无线资源管理.
- Authors
冯毅; 葛宁; 张陶冶
- Abstract
In order to improve the effectiveness of Cellular Vehicle-to-Everything(C-V2X) resource reuse and reduce the interference between terminals,the authors propose a scheme to improve radio resource management by predicting the traffic flow through neural networks. The traffic flow in the road side unit (RSU) coverage area is obtained through V2X messages between on board unit(OBU) and RSU. Back Propagation(BP) neural network and Radial Basis Function(RBF) neural network are used for short-time traffic flow prediction respectively. RSUs perform adaptive clustering according to the prediction results. The resource pools are multiplexed between clusters and divided within the clusters. OBUs within RSU coverage select transmitting resources in the divided resource pool,thus reducing interference between terminals and ensuring more resources for vehicles in hotspot areas. Simulation results show that the packet reception ratio of the proposed scheme improves by 14% compared with the scheme in the specification and 10% compared with the typical literature scheme in a traffic congestion scenario, ensuring the reliability of communication.
- Subjects
RADIO resource management
- Publication
Telecommunication Engineering, 2023, Vol 63, Issue 11, p1651
- ISSN
1001-893X
- Publication type
Article
- DOI
10.20079/j.issn.1001-893x.220418002