Network Planning for Fixed Wireless Backhaul
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Solution Overview
Problem
Current network planning tools for wireless backhaul networks are slow, require significant data inputs, and do not provide real-time performance results, especially in urban areas where high-resolution digital maps and building polygons are not available, and they fail to effectively predict terrain path loss and foreign interference.
Innovation Solution
A method for network planning that uses reference use case channel models for downtown, urban, and suburban scenarios to predict terrain path loss and perform antenna gain calculations, allowing for rapid and effective planning with limited input data, and optimizes small cell deployment by considering end-to-end performance across both backhaul and access links.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If commercially available RF planning tools are used for network planning, then pathloss prediction and network design can be performed, but the tools are slow, require significant data inputs, and do not provide real-time performance results
Solution Approach 1:
The patent segments the complex terrain pathloss prediction problem into distinct urban scenarios (downtown, urban, suburban) with specific channel models for each. This segmentation allows the system to handle different environments with simplified, pre-defined models rather than requiring comprehensive high-resolution digital maps and building polygons for all areas, thereby reducing data input requirements while maintaining planning speed.
Solution Approach 2:
The patent changes the approach from using detailed physical parameters (high-resolution digital maps, building polygons, topographical details) to using scenario-based parameters (urban scenario types with predefined channel models). This parameter transformation enables faster network planning by trading detailed spatial information for categorized environmental descriptors, directly addressing the contradiction between planning speed and data complexity.
2Measurement precision
If detailed terrain information and high-resolution digital maps are used for pathloss prediction, then prediction accuracy is improved, but the complexity and time required for network planning increases significantly
Solution Approach 1:
The patent applies preliminary action by pre-defining channel models for different urban scenarios (downtown, urban, suburban) before actual network planning occurs. These pre-configured models contain typical pathloss characteristics for each scenario type, allowing the system to provide accurate predictions without performing time-consuming detailed terrain analysis during the planning process itself.
Solution Approach 2:
The patent uses copying by creating simplified representative models that copy the essential pathloss characteristics of complex urban environments. Instead of modeling each specific building and terrain feature, the system copies the aggregate behavior of entire urban scenarios into predefined channel models, maintaining prediction accuracy while dramatically reducing computation time and data requirements.
3Adaptability or versatility
If network planning is performed independently by each operator without considering neighboring networks, then operator-specific optimization is achieved, but foreign interference prediction and overall network performance optimization are compromised
Solution Approach 1:
The patent applies universality by creating a common framework of urban scenario channel models that can be used by multiple operators simultaneously. The same scenario-based models (downtown, urban, suburban) serve as a universal language for all operators to predict both their own network performance and potential foreign interference, enabling coordinated planning while maintaining operator-specific optimization capabilities.
Data Source
AI summary
Systems and methods are disclosed for networking planning for fixed backhaul networks comprising a plurality of hubs, each serving one or more RBMs. The method comprises one or more of terrain pathloss (PL) and antenna gain prediction; network design comprising site association, hub dimensioning and pointing; and optimization of small cell (SC) deployment. PL prediction is based on correlation of user input parameters with reference use cases for channel models for each of downtown, urban, and suburban deployment scenarios. Rapid and effective network planning is achieved with limited input data, even in the absence of high resolution digital maps or building polygons, by selecting the channel model having a highest correlation with available environmental parameters. Optimization of network topology design, system design, and SC deployment, with both access link and backhaul link evaluation, is based on optimization of a sum-utility function across all links for feasible SC site locations.