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Realization method for Q learning based vehicle-mounted network media access control (MAC) protocol

An implementation method and a technology of an in-vehicle network, applied in the field of the in-vehicle network MAC protocol, can solve problems such as collision, channel access fairness is not effectively improved, traffic flow is not scalable, etc., to improve fairness and data packet reception rate. and packet transmission delay improvement, packet reception rate and end-to-end transmission delay improvement effect

Active Publication Date: 2016-02-03
NANJING NANYOU INST OF INFORMATION TECHNOVATION CO LTD
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  • Summary
  • Abstract
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  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] However, the above existing technologies are all improved on the basis of the BEB algorithm. Generally speaking, when the data collides and needs to be avoided, the CW value is multiplied. After the data is successfully sent, the CW will be restored to 15. If there are multiple nodes At the same time, the data is successfully sent, the CW value is restored to 15, and a collision occurs when the data is sent again.
The network load is less considered, and it is not suitable for networks with different load levels, that is, it is not scalable for traffic flows of different densities, and the fairness of channel access has not been effectively improved.

Method used

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  • Realization method for Q learning based vehicle-mounted network media access control (MAC) protocol
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  • Realization method for Q learning based vehicle-mounted network media access control (MAC) protocol

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Embodiment Construction

[0021] The invention will be described in further detail below in conjunction with the accompanying drawings.

[0022] The QL-MAC algorithm includes the following:

[0023] The QL-MAC method solves the problem of collision rate and delay by dynamically adjusting the competition window. It uses the Q-Learning algorithm to learn the best competition window. Since the exchange of beacon messages between adjacent nodes can obtain the location information of neighboring nodes, Therefore, assuming that each node knows the location information of its one-hop neighbor node, after the node successfully sends the data frame, the environment will give the node a positive reward, and if the transmission fails, it will give a negative reward. When the network load is low, use Nodes use the learned best CW to choose to access the channel with a smaller CW to avoid delay increase, and when the network load is high, use a larger CW to access the channel to reduce collisions. The QL-MAC algor...

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Abstract

The invention discloses a realization method for a Q learning based vehicle-mounted network media access control (MAC) protocol. According to the method, a vehicle node uses a Q learning algorithm to constantly interact with the environment through repeated trial and error in a VANETs environment, and dynamically adjusts a competitive window (CW) according to a feedback signal (reward value) given by the VANETs environment, thereby always accessing the channel via the best CW (the best CW is selected when the reward value obtained from surrounding environment is maximum). Through adoption of the method, the data frame collision rate and transmission delay are lowered, and fairness of the node in channel accessing is improved.

Description

technical field [0001] The invention relates to an implementation method of a vehicle-mounted network MAC protocol based on Q learning in a vehicle-mounted self-organizing network communication protocol, and belongs to the technical field of the Internet of Things. Background technique [0002] In recent years, with the rapid development of the transportation industry, the number of cars has increased dramatically. While the wide range of automobiles brings convenience to people's daily travel, various problems such as safety and traffic congestion have also occurred. In the 1980s, the University of California first proposed the concept of Intelligent Transportation System (ITS) to improve transportation efficiency, alleviate traffic congestion, and reduce traffic accidents. Today, with the rapid development of intelligent transportation systems and wireless communication technologies, the Internet of Vehicles has emerged as the times require. It is another symbol of future...

Claims

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Application Information

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IPC IPC(8): H04L1/12H04W28/08H04W74/08H04L29/08
CPCH04L1/12H04L67/12H04W74/085H04W28/082
Inventor 赵海涛杜艾芊刘南杰朱洪波
Owner NANJING NANYOU INST OF INFORMATION TECHNOVATION CO LTD
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