Wireless sensor network interference model estimating method based on Sigmoid function

A wireless sensor and interference model technology, which is applied in transmission monitoring, transmission system, electrical components, etc., can solve the problem of difficult realization of sensor nodes, achieve the effect of reducing modeling complexity, reducing modeling overhead, and avoiding Gaussian error function
CN106685545AActive Publication Date: 2017-05-17XIDIAN UNIV
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Patent Information

Authority / Receiving Office
CN Β· China
Patent Type
Applications(China)
Current Assignee / Owner
XIDIAN UNIV
Publication Date
2017-05-17

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Abstract

The invention discloses a wireless sensor network interference model estimating method based on Sigmoid function; the method is characterized in that an interference model is constructed by introducing stretch coefficient and translation coefficient based on standard Sigmoid function model, and each node initializes the stretch coefficient and translation coefficient of the interference model according to an experience value; sample value of the interference model is collected continuously during normal data transmission; the interference model is adjusted in real time by using linear regression estimation model parameters according to the sample value. The wireless sensor network interference model is simulated by introducing stretch coefficient and translation coefficient and using Sigmoid function as a prototype, calculating complex Gaussian error function is avoided, the model precision is adjusted by means of parameter estimation, and modeling complexity is decreased; the stretch coefficient and translation coefficient in the model are estimated by collecting samples in a network during normal data transmission, and modeling expense is decreased.
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Description

technical field

[0001] The invention relates to the technical field of wireless sensor networks, in particular to a method for estimating an interference model of a wireless sensor network based on a Sigmoid function. Background technique

[0002] The wireless sensor network is composed of a large number of cheap micro-sensor nodes deployed in the target area. It is a multi-hop self-organizing network formed by wireless communication. It is mainly used in the monitoring of the target area. In the wireless communication process, the packet reception rate (PRR: Packet Reception Ratio) mainly depends on the signal-to-interference-noise ratio (SINR: Signalto Interference plus Noise Ratio), and this packet-level interference model is also called the PRR-SINR model. Establishing an accurate interference model can greatly improve the performance of wireless sensor network communication protocols.

[0003] Establishing interference models quickly and accurately plays an important r...

Claims

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