A vehicle networking fairness transmission method based on convex optimization and reinforcement learning

By improving the ACK and DATA frame structures to detect hidden nodes and optimizing transmission power, and combining convex optimization and reinforcement learning, the problem of unfair transmission between hidden nodes and fast and slow vehicles in vehicle-to-everything (V2X) networks is solved, thereby improving throughput and transmission reliability.

CN122120731BActive Publication Date: 2026-07-24IANGSU COLLEGE OF ENG & TECH
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
IANGSU COLLEGE OF ENG & TECH
Filing Date
2026-04-29
Publication Date
2026-07-24

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Abstract

The application provides a vehicle networking fairness transmission method based on convex optimization and reinforcement learning, and belongs to the technical field of vehicle networking and data transmission. The technical scheme is as follows: S1: an improved confirmation ACK frame and a data DATA frame are designed to realize hidden node detection; S2: mathematical modeling of the transmission fairness problem; S3: fairness transmission based on convex optimization and reinforcement learning. The application effectively discovers hidden nodes, alleviates transmission conflicts caused by hidden nodes by improving the transmission power and the 'continuation' field of the data frame DATA, and finally improves the throughput; the reinforcement learning and convex optimization method are used to jointly optimize the transmission strategy, solve the minimization problem of the difference between the transmission data amounts of fast and slow vehicles, and improve the data fairness of vehicle networking transmission.
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Citation Information

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