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Optimisation methods for performance of communication interaction based on cooperative vehicle infrastructure system

机译：基于协同车辆基础设施系统的通信交互性能优化方法

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Vehicular ad-hoc network (VANET) is the main information distribution way in VANET. In this paper, the traditional handshake mechanism of enhanced distributed channel access (EDCA) model protocol in IEEE 802.11p and the request to send/clear to send (RTS/CTS) control frame were optimised, then a more reasonable and adaptive back off algorithm based on contention window was proposed, and it's called A-EDCA, and then the competition mechanism of multi communication mode based on adaptive neural network was proposed. After finishing the nonlinear neural network modelling and least mean square (LMS) learning algorithm, variety of traffic scenarios were built to verify and evaluate competition mechanism in OPNET Modeller. The simulation results show that A-EDCA can reduce the likelihood of wireless channel conflict effectively and has significant performance in term of transmission delay and throughput. The proposed competition mechanism of multi communication mode can mainly forecast the optimal communication mode accurately.
机译：车辆ad-hoc网络（VANET）是VANET中的主要信息分布方式。在本文中，优化了IEEE 802.11p中增强分布式信道访问（EDCA）模型协议的传统握手机制和发送/清除发送（RTS / CTS）控制帧的请求，然后是更合理和自适应的反外算法提出了基于争用窗口，并提出了基于A-EDCA，然后提出了基于自适应神经网络的多通信模式的竞争机制。完成非线性神经网络建模和最小均方（LMS）学习算法后，建立各种流量方案，以验证和评估OPNET MODELLER中的竞争机制。仿真结果表明，A-EDCA可以有效地降低无线信道冲突的可能性，并且在传输延迟和吞吐量期间具有显着性能。多通信模式的提议竞争机制主要可以准确地预测最佳通信模式。

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