Cooperative Transmission Mechanism Based on Revenue Learning for Vehicular Networks
نویسندگان
چکیده
With the rapid development of science and technology improvement people’s living standards, vehicles have gradually become main means travel. The increase in has also brought about an increasing incidence car accidents. In order to reduce traffic accidents, many researchers proposed use vehicular networks quickly transmit information. As long as these can receive information from other or buildings nearby a timely manner, they avoid networks, traditional double connection technique, through interference coordination scheduling strategy based on graph theory, ensure fairness obtain suitable neighborhood resistance with limited computing resources. However, when base station transmits data user, network user may be state suspended communication. Thus, resource utilization above is not sufficient, resulting waste To solve this issue, paper presents study earnings learning multi-point collaborative transmission mechanism, which users communicate surrounding transmission. We Q-learning algorithm reinforcement process enable learn each make cooperative decisions different environments. learning, agent makes decision changes environment. Then, environment feeds back benefit related so that learns optimal decision. Simulation results demonstrate superiority our approach revenue machine model compared benchmark schemes.
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ژورنال
عنوان ژورنال: Applied sciences
سال: 2022
ISSN: ['2076-3417']
DOI: https://doi.org/10.3390/app122412651