Node Positioning Algorithm Using Channel Classification for Wireless Sensor Networks
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Solution Overview
Problem
Conventional WLS node positioning algorithms in wireless sensor networks require prior knowledge of path loss decay exponents and variance terms, which are often unknown or changeable, and are affected by limited receiver sensitivity, leading to inaccurate distance estimation and positioning.
Innovation Solution
A supervised node positioning algorithm that classifies propagation channels into LOS, NLOS, and NLOS2 categories, assigns appropriate path loss parameters and shadowing coefficients, and uses a weighted least squares optimization to estimate node positions, while accounting for receiver sensitivity limitations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional WLS positioning algorithms are used, then positioning can be performed, but inaccurate distance estimation occurs due to unknown or changeable path loss decay exponents and variance terms
Solution Approach 1:
The patent changes the approach from using fixed path loss decay exponents and variance terms to dynamically classifying propagation channels into LOS, NLOS, and NLOS2 categories. Each category is assigned appropriate path loss parameters and shadowing coefficients, allowing the system to adapt to varying channel conditions and improve both positioning accuracy and algorithm robustness.
Solution Approach 2:
The patent implements a feedback mechanism where received signal strength measurements are used to classify propagation channels and update path loss parameters. This feedback loop allows the system to continuously refine its distance estimation by adjusting parameters based on actual channel conditions, thereby improving positioning accuracy without requiring prior knowledge of environment or channel configurations.
2Ease of operation
If WLS algorithms assume known path loss parameters, then positioning calculations can proceed, but the algorithms fail when receivers have limited sensitivity
Solution Approach 1:
The patent introduces propagation channel classification as an intermediary step between signal reception and positioning calculation. By classifying channels into LOS, NLOS, and NLOS2 categories and assigning appropriate path loss parameters to each, the system mediates between the raw received signal strength measurements and the final distance estimation, enabling accurate positioning even with receivers of limited sensitivity.
Solution Approach 2:
The patent changes the parameter estimation approach by using received signal strength-based channel classification to determine path loss decay exponents and shadowing coefficients. This allows the system to adapt parameters to actual channel conditions rather than relying on predefined values, improving distance estimation accuracy for receivers with limited sensitivity.
3Reliability
If range-free positioning algorithms are used, then positioning can be achieved without distance measurements, but positioning accuracy is reduced
Solution Approach 1:
The patent merges the advantages of range-free and range-based approaches by using received signal strength measurements to classify propagation channels and estimate distances. This combination allows the system to achieve both robustness (through classification-based error correction) and accuracy (through direct distance estimation), overcoming the limitations of purely range-free algorithms.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach provides accurate node positioning without prior knowledge of environment or channel configurations and effectively handles real receivers with limited sensitivity, improving estimation accuracy and robustness.
Implementation Method 1
the path loss over a radio link between two neighboring nodes i and j can be modeled as follows: PLij = PL0,ij + 10αij log10(dij/d0,ij)
Implementation Method 2
each regular node i of the network measures the respective received signal strengths (RSSs) of the signals it respectively receives from its neighbors j
Data Source
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Figure 2A~2B
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AI summary
The present invention relates to a method for positioning a collection of nodes within a wireless sensor network in which each node measures the respective strengths of signals, RSSs, from its neighboring nodes (310), the channels linking regular nodes and its neighboring nodes are classified into different categories (320) and are allocated path loss parameters accordingly (330). The distances separating each regular node from each of its neighboring nodes, and the respective variances thereof are estimated (340) on the basis of the measured RSSs and the allocated path loss parameters. The positions of the regular nodes are then estimated (350) by weighted least square, WLS, optimization where the distances to be matched and the variances used for the weighting are those estimated in (340).