Wireless body area network data transmission method based on reinforced learning algorithm

A data transmission method and wireless body area network technology, applied in wireless communication, wireless communication services, machine-to-machine/machine-type communication services, etc. Node heterogeneity and other issues to achieve the effect of ensuring accuracy and preventing diseases

Active Publication Date: 2017-05-17
DONGHUA UNIV
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Problems solved by technology

After all, the scale of the wireless body area network is not large. If the multi-hop transmission method is simply adopted, it will inevitably bring about unnecessary data forwarding, which will cause delays and more energy consumption.
(2) The heterogeneity of nodes is not considered in the existing data transmission scheme

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  • Wireless body area network data transmission method based on reinforced learning algorithm
  • Wireless body area network data transmission method based on reinforced learning algorithm
  • Wireless body area network data transmission method based on reinforced learning algorithm

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Embodiment Construction

[0027] Below in conjunction with specific embodiment, further illustrate the present invention. It should be understood that these examples are only used to illustrate the present invention and are not intended to limit the scope of the present invention. In addition, it should be understood that after reading the teachings of the present invention, those skilled in the art can make various changes or modifications to the present invention, and these equivalent forms also fall within the scope defined by the appended claims of the present application.

[0028] The present invention relates to two types of nodes, one is a sensor node and the other is an aggregation node. Deploy sensor nodes on the ankles, legs, wrists, and arms of the human body to collect and transmit data on signs such as blood pressure, blood sugar, and pulse to the aggregation node. In the present invention, the mobile phone is used as the convergence node, and the convergence node finally sends the data t...

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Abstract

The invention relates to a wireless body area network data transmission method based on a reinforced learning algorithm. The method aims at characteristics of a wireless body area network and is a hybrid data transmission method. The wireless body area network data transmission method comprises the steps of dividing nodes to different grades according to heterogeneous characteristics of different node energy levels, different data services and different workloads; calculating channel states of nodes and a convergent node according to a Markov channel model, determining whether a relay node is required in data transmission; if channel state is good, directly transmitting node data to a convergent node, and otherwise, searching an optimal path between the nodes and the convergent node by means of the reinforced learning algorithm based on node grade dividing, and continuously optimizing path selection in a data transmission process. The wireless body area network data transmission method can ensure efficient and reliable physiological data related in the wireless body area network. The wireless body area network data transmission method can be applied in multiple fields for ensuring accuracy of data received by a monitoring center.

Description

technical field [0001] The invention relates to a method for solving the data transmission problem of a wireless body area network by using an enhanced learning algorithm, which is used in the field of medical care for monitoring by using a wireless body area network, and provides a method for ensuring the accuracy of data received by a monitoring center. Background technique [0002] According to the results of the sixth population census of the National Bureau of Statistics, the population aged 60 and above accounted for 13.26%, an increase of 2.93% compared with the fifth population census. Among the elderly aged 60 and above, 44% are healthy, 39% are basically healthy, 14% are unhealthy but able to take care of themselves, and 3% are unable to take care of themselves. It can be seen that 56% of the elderly need to be concerned about their physical condition at all times. Even for the 44% of the elderly who are currently healthy, pathological changes may occur in their b...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): H04W4/00
CPCH04W4/70
Inventor 郭文静燕彩蓉甘杨兰
Owner DONGHUA UNIV
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