Extended COST-231-WI Model for 3D Signal Prediction
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Solution Overview
Problem
Current outdoor propagation models, such as the COST-231-Walfisch-Ikegami model, are limited in predicting signal field strength in three-dimensional spaces and do not accurately account for indoor high-rise building signal coverage from outdoor base stations, as they primarily focus on horizontal plane predictions at a height of 1 m above the ground.
Innovation Solution
An extended COST-231-Walfisch-Ikegami propagation model is developed, which establishes a three-dimensional scene model, measures signal strength at 1 m height, predicts signal strength using key parameters, corrects errors, and filters buildings outside the Fresnel circle to calculate signal strength at various heights, enabling accurate three-dimensional signal field strength prediction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the conventional COST-231-Walfisch-Ikegami model is used for outdoor signal prediction, then the calculation efficiency is high, but the prediction accuracy is limited to horizontal plane at 1 m height only
Solution Approach 1:
The patent extends the conventional two-dimensional horizontal plane prediction model to a three-dimensional prediction model by introducing vertical height dimension. The model now predicts signal field strength at arbitrary heights above ground, not limited to 1 m height, enabling vertical coverage analysis for indoor and outdoor unified network planning.
Solution Approach 2:
The extended model serves multiple functions: it can predict signal strength both at traditional 1 m height and at arbitrary heights above ground. The model is applicable to both outdoor microcell environments and indoor coverage analysis, making it a universal tool for unified network planning.
2Adaptability or versatility
If a three-dimensional prediction model is developed to predict signal field strength at various heights, then the adaptability for indoor and outdoor unified planning is improved, but the model complexity increases
Solution Approach 1:
The patent segments the propagation environment into different height zones and applies appropriate prediction methods for each zone. The model divides the three-dimensional space into cells and processes signal prediction in a structured manner, reducing overall complexity through systematic segmentation.
Solution Approach 2:
The model dynamically adjusts prediction parameters based on height, distance, and environmental factors. By changing parameters adaptively rather than using fixed complex structures, the model achieves three-dimensional prediction capability while managing complexity through parameter-based flexibility.
3Measurement precision
If the model is extended to predict signal field strength up to twice the height of base station antenna, then the coverage prediction accuracy is improved, but the calculation time increases
Solution Approach 1:
The patent performs preliminary calculations by establishing the three-dimensional scene model and determining key propagation parameters in advance. By pre-processing the environment data and setting up the prediction framework beforehand, the model reduces real-time calculation time while maintaining accurate coverage prediction across extended height ranges.
Data Source
AI summary
A method for predicting outdoor three-dimensional space signal field strength by extended COST-231-Walfisch-Ikegami propagation model, comprising: establishing a three-dimensional scene model between a transmitting base station and a predicted region space; performing an on-site measurement according to a certain resolution in a prediction region and recording wireless signal strength information at a height of 1 m above the ground; acquiring a vertical cross section between the transmitting base station and a receiving point at a height of 1 m above the ground, and acquiring therefrom an average roof height, an average street width and an average between-building space; predicting a reception signal strength at a measurement point in a calculation formula of a COST-231-Walfishch-Ikegami propagation model; correcting the COST-231-Walfishch-Ikegami propagation model of the measurement point according to an error Δ between measured data and a prediction result; acquiring a vertical cross section between the transmitting base station and a receiving point at other height of the measurement point, and filtering therefrom buildings outside a Fresnel circle to re-acquire the average roof height, the average street width and the average between-building space; and calculating a reception signal strength at other height of the measurement point according to the corrected COST-231-Walfishch-Ikegami propagation model.