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Intelligent Optimization Algorithm for Green IoV Networks Based on SSA

delete2025-02-01
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PRE
AI
H
Hao Yin
Y
Yaohui Lyu *
L
Lingwei Xu
T
T. Aaron Gulliver
DOI:10.1109/TVT.2023.3347744delete
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摘要

摘要

En 中文
The rapid development of the Internet of Vehicles (IoV) has been enabled by sixth-generation (6G) mobile communication and artificial intelligence technologies. However, with the explosive growth of vehicle Big Data. However, Big Data transmission consumes a significant amount of energy. Green IoV networks have received increasing attention. Power consumption optimization plays an important role in green IoV networks. Using decode-and-forward (DF) relaying, we investigate the intelligent power allocation optimization of green cooperative IoV networks. Based on the characteristics of mobile channels, we employ outage probability (OP) criterion to analyze communication performance of green cooperative connected IoV networks from a mathematical perspective. Novel OP mathematical expressions are obtained. Using the obtained OP results, we investigate the problem of OP performance minimization via power allocation optimization. The complex non-convex problem of power allocation is formulated, as well as the optimization function. Based on the sparrow search algorithm (SSA), an intelligent optimization algorithm is proposed to solve the above complex problem. The proposed SSA approach is compared to the state-of-the-art intelligence algorithms, and our proposed algorithm can achieve a shorter running time and a good OP performance, thereby enhancing the system's efficiency.
Keyword:
Resource management
Optimization
Green products
6G mobile communication
Power demand
Heuristic algorithms
Energy consumption
Green cooperative connected IoV networks
performance analysis
power allocation optimization
sparrow search algorithm

期刊

IEEE Transactions on Vehicular Technology 封面图
IEEE Transactions on Vehicular Technology
IF:
7.1
论文数:
1.8W
被引数:
6.6W

机构

U
University of Victoria
学者数:
1.0W
论文数: 1.0W
被引数: 1.5W
O
ocean university of china
学者数:
3.1W
论文数: 2.0W
被引数: 21
G
guangxi minzu university
学者数:
3.4K
论文数: 2.2K
被引数: 59
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