3D Propagation Model Tuning for Radio Network Planning
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Solution Overview
Problem
Current 3D propagation models for wireless network planning face challenges in accurately predicting propagation path losses, especially for Line-of-sight (LOS) and Non-line-of-sight (NLOS) transmissions, and require extensive drive tests and calibration, making them time-consuming and costly. Additionally, they struggle to create models for varying geographical areas and clutter types without sufficient data.
Innovation Solution
A method using a Continuous-Wave (CW) based 3D propagation model that automatically tunes propagation path loss parameters by collecting network parameters from RF scanners and user equipment, utilizing Key Point Indicators (KPIs) to optimize the model for LOS and NLOS transmissions, and generates models for similar geographical areas without the need for drive tests, using periodically measured UE data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional 3D propagation models are used for radio network planning, then coverage and capacity can be estimated, but the models require extensive drive tests and calibration which are time-consuming and costly
Solution Approach 1:
The patent applies preliminary action by pre-calculating and storing propagation path loss parameters for different transmission types (LOS, NLOS, partially blocked) in a database before actual network planning. Instead of performing extensive drive tests and calibration during the planning phase, the system prepares propagation models in advance using simulated or historical data, then quickly retrieves and applies these pre-computed parameters when planning radio networks, significantly reducing the time required for on-site measurements and calibration
Solution Approach 2:
The patent uses copying by creating simplified representations of complex propagation environments through transmission type classifications. Instead of replicating entire drive test scenarios for each planning situation, the system copies relevant propagation characteristics into categorized models (LOS, NLOS, partially blocked) that can be rapidly applied to different geographical areas and network configurations, reducing the need for repeated extensive measurements
2Measurement precision
If conventional 3D propagation models are used for radio network planning, then coverage prediction is possible, but extensive drive tests and calibration are required making the process costly
Solution Approach 1:
The patent applies preliminary action by pre-calculating and storing propagation path loss parameters for different transmission types (LOS, NLOS, partially blocked) in a database before actual network planning. Instead of performing extensive drive tests and calibration during the planning phase, the system prepares propagation models in advance using simulated or historical data, then quickly retrieves and applies these pre-computed parameters when planning radio networks, significantly reducing the time required for on-site measurements and calibration
Solution Approach 2:
The patent applies this principle by using computationally inexpensive propagation models that can be rapidly calibrated and discarded for different planning scenarios. Rather than investing in expensive, highly accurate models requiring extensive calibration, the system uses simpler models that can be quickly adjusted and replaced, reducing the cost of each planning iteration while maintaining sufficient accuracy for decision-making
3Productivity
If standard propagation models with low-resolution map data are used, then initial RF planning can be performed, but the accuracy is insufficient for optimizing network capacity and coverage
Solution Approach 1:
The patent applies segmentation by dividing the propagation environment into distinct transmission type categories (LOS, NLOS, partially blocked) based on spatial relationships between base stations and user equipment. This segmentation allows the system to apply different propagation models and parameters to different spatial zones, improving accuracy without requiring uniformly high-resolution data across the entire coverage area, thus maintaining planning efficiency while enhancing precision where critical
Solution Approach 2:
The patent applies parameter changes by dynamically adjusting propagation path loss parameters based on transmission type classification. The system changes key parameters such as path loss exponents and offset values depending on whether the transmission is LOS, NLOS, or partially blocked, allowing accurate RF planning without requiring high-resolution map data for all scenarios, thus maintaining both efficiency and accuracy
4Reliability
If manual tuning of RF parameters is performed as per conventional approach, then network optimization can be achieved, but the process is time-consuming and expensive
Solution Approach 1:
The patent applies self-service by enabling the propagation model to automatically select and apply appropriate path loss parameters based on transmitted location information and pre-stored transmission type classifications. Instead of requiring manual expert tuning of RF parameters, the system autonomously determines the transmission type (LOS, NLOS, partially blocked) and retrieves the corresponding calibrated parameters from the database, significantly reducing the time and expertise required for network optimization while maintaining high reliability
Solution Approach 2:
The patent applies feedback by using transmitted location information from user equipment to dynamically determine the current transmission type and select appropriate propagation parameters. The system continuously receives location feedback, updates the transmission type classification based on spatial relationships with base stations, and adjusts propagation parameters accordingly, enabling automatic network optimization without manual intervention while maintaining high accuracy
Data Source
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AI summary
A system and method for 3D propagation modelling for planning of a radio network, is disclosed. In the present invention, automatic tuning of propagation path loss parameters of a Continuous Wave (CW) based 3D propagation model for LOS (line of sight) and NLOS (non-line of sight) radio transmissions in a first geographical area, is performed. Further, in the present invention, 3D propagation models for remaining geographies having similar geographical area and clutter types as the first geographical area, are generated without performing any drive test while compensating the propagation path loss parameters of the generated model using periodically measured user equipment (UE) data. The generated 3D models may be updated dynamically as the 3D models are developed based on UE data updated from time to time.