A network topology control method in cognitive vehicle networking

Abstract

The invention discloses a network topology control method in a cognitive vehicle networking, which mainly solves the problems of network topology splitting and mutual interference of cognitive vehicles caused by any channel being occupied in the prior art. The implementation process of the method is as follows: 1. Each vehicle node in the network first uses the directional information transmission mechanism in the present invention to obtain one-hop neighbor information; 2. Based on the one-hop neighbor information, each vehicle node uses the two-hop neighbor information in the present invention. The hop neighbor discrimination mechanism obtains a local two-hop topology map; 3. Each vehicle node constructs a local generated subgraph that can ensure the connectivity of the topology structure according to the link weight proposed in the present invention; 4. All vehicle nodes in the network are based on the optimized The locally generated subgraph of the channel is requested and used to avoid interference in the network. The method of the invention can ensure the network connectivity after any channel in the network in the cognitive vehicle networking is occupied, and improve the fault tolerance and robustness of the network topology structure.

Description

technical field [0001] The invention belongs to the field of wireless communication, and in particular relates to a method for constructing a network topology structure, which can be used for cognitive vehicle networking. Background technique [0002] The robustness of the network topology is an important factor affecting the end-to-end transmission performance of the cognitive vehicle networking. How to build a network topology with high fault tolerance is a key research issue in the deployment of the cognitive vehicle networking. When the primary user in the network occupies a certain channel, the cognitive vehicles in the cognitive vehicle networking must back out of the channel, and these vehicles will lose the ability to transmit and relay data in the network. In this case, the topological structure of the cognitive vehicle networking is very likely to be fragmented, which will cause the network to lose its connectivity characteristics and affect the end-to-end transmis...

AI Technical Summary

Problems solved by technology

However, the algorithm proposed in this article is limited to guarantee the channel connectivity characteristics of the static network topology, and cannot be directly applied to the cognitive vehicle networking environment where the vehicle has mobility.

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