Network Deployment Analysis for 5G Planning
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Solution Overview
Problem
Current radio network design methods, reliant on propagation models like Okumura-Hata and ray tracing, face inaccuracies, especially in complex urban scenarios, due to varying propagation characteristics and limited model availability, leading to suboptimal cell deployment and antenna placement.
Innovation Solution
A network deployment analysis apparatus and method that evaluates potential cell deployments by performing signal measurements in legacy communication networks, using downlink measurements and link budget calculations to determine traffic absorption capability and coverage, facilitating more accurate radio network planning for 5G networks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If propagation models like Okumura-Hata and ray tracing are used for network design, then planning can be performed without measurements, but the accuracy of coverage and capacity predictions deteriorates in complex urban scenarios
Solution Approach 1:
The patent performs downlink measurements and link budget calculations in advance to establish traffic absorption capability values for different cell deployments. These preliminary measurements create a database of propagation characteristics that can be used for future network planning decisions, allowing accurate predictions without repeated measurements.
Solution Approach 2:
The system uses measured traffic absorption capability values as feedback to evaluate and compare different cell deployment scenarios. The measurements provide real-world validation that feeds back into the network design process, allowing planners to adjust configurations based on actual propagation characteristics rather than relying solely on theoretical models.
2Measurement precision
If propagation models are tuned for particular scenarios, then accuracy improves for those specific cases, but the complexity of selecting and tuning appropriate models increases
Solution Approach 1:
The system performs self-measurement of traffic absorption capability by having user equipment automatically measure downlink signals and report results. This eliminates the need for manual model tuning and selection, as the network itself gathers the necessary propagation data through standardized measurement procedures implemented at the device level.
3Device complexity
If traditional planning tools are used with limited propagation models, then device complexity remains low, but the ability to accurately evaluate cell deployments in diverse environments deteriorates
Solution Approach 1:
The patent introduces traffic absorption capability as a new evaluation parameter that quantifies the ability of different cell deployments to handle traffic demand. This parameter is calculated based on measured propagation characteristics and can be used universally across different deployment scenarios, providing a simple yet effective metric that adapts to various environments without requiring complex scenario-specific models.
Data Source
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AI summary
According to an aspect, there is provided a network deployment analysis apparatus. It is assumed that information on a wireless communications network of first and second types are maintained in a database. The network deployment analysis apparatus causes performing downlink measurements on reference signals transmitted by one or more access nodes in the wireless communications network of the first type using a plurality of terminal devices in said network. In response to receiving information on results of the downlink measurements, the network deployment analysis apparatus calculates one or more values of traffic absorption capability associated with one or more potential cell deployments in a wireless communications network of the second type based on the received information and the information maintained in the database. The results of the calculating are outputted to a user device for facilitating network planning of the wireless communications network of the second type.