Routing method of self-adapting self-organized network in cognitive network

A cognitive network and self-organizing network technology, applied in the field of wireless communication, can solve the problems of lack of perception of various performances of network status, lack of consideration of network service quality, etc., and achieve the effects of improving efficiency, balancing load, and reducing survival time

Inactive Publication Date: 2010-05-26
XIDIAN UNIV
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AI Technical Summary

Problems solved by technology

[0005] The improved AODV ad hoc network routing algorithm based on Q-learning technology only realizes part of the functions of the cognitive network routing algorithm, and is limited to adjusting the network state by judging whether the route is successful

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  • Routing method of self-adapting self-organized network in cognitive network
  • Routing method of self-adapting self-organized network in cognitive network
  • Routing method of self-adapting self-organized network in cognitive network

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[0024] refer to figure 1 , the route establishment of the present invention comprises the following steps:

[0025] In step 1, the source node sends RREQ information to find a path, and the destination node sends RREP information to reply to the source node.

[0026] (1a) The source node in the network sends RREQ information by means of broadcast flooding. After receiving the RREQ information, the destination node establishes and sends RREP information to reply to the source node according to the principle of first come first return. The sending path of RREP information is based on the The path that the received RREQ message passes is returned by the original path;

[0027] (2a) After the source node receives the RREP information sent by the destination node, it completes the initial establishment of the route, and the destination node sends data packets on this path for data transmission;

[0028] (2a) After the route is established, within the lifetime of the route, the de...

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Abstract

The invention discloses a routing method of a self-adapting self-organized network in a cognitive network, mainly solving the problem that the traditional cognitive network routing methods lack of network QoS (quality of service) guarantees. The routing method comprises the following steps of: sending RREQ information by a source node by adopting a broadcast flooding method; when a relay node transmits the RREQ information, extracting the state of a network node, estimating the waiting time delay of the node in the network and adding the waiting time delay during transmitting the RREQ information; after a target node receives the RREQ information, sending the RREQ information according to a principle of firstly returning early arrived information and establishing a route; after establishing the route, repeatedly sending the same RREQ information to the resource node by the target node to update network state information; and detecting the quality of the route and determining whether to increase or reduce the life time of the route or not. The method has the advantages of short data transmission time delay, small packet loss, high route efficiency and large network load capacity and can be applied to cognitive radio networks.

Description

technical field [0001] The invention relates to the field of wireless communication, in particular to a method for establishing a route, which can be used in a cognitive wireless network. Background technique [0002] The definition of cognitive wireless network (Cognitive Network) is: the wireless cognitive network has a cognitive process for the current network situation, and generates network behavior based on this process. The wireless cognitive network can learn the changes of the network and make predictions for future behaviors, while considering the end-to-end target requirements. [0003] A routing mechanism suitable for cognitive wireless network environment in the prior art is an improved AODV (Ad hoc on-demand distance vector) ad hoc network routing based on Q-learning technology proposed by Minsoo Lee et al. algorithm. The algorithm combines Q-learning technology with on-demand routing, adopts an on-demand routing mechanism similar to AODV on-demand distance v...

Claims

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Application Information

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IPC IPC(8): H04W40/04H04W84/18
Inventor 盛敏徐扬史琰张琰李建东李红艳吕晨
Owner XIDIAN UNIV
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