Cellular Site Selection Using Geographic Data and Radio APIs
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional 5G network planning is cumbersome and complex, involving manual and tedious work, undefined planning processes, challenges with crowd-sourced data, and a steep learning curve, making it difficult to determine optimal site locations for various service types.
Innovation Solution
An automated system and method using a cloud-native architecture with radio APIs for site selection, incorporating a web interface to ingest and analyze geographic and infrastructure data, enabling efficient site selection and deployment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional manual approach is used for network planning, then flexibility in handling complex scenarios is maintained, but productivity and time efficiency deteriorate significantly
Solution Approach 1:
The patent replaces manual mechanical planning processes with an automated computer-based system that uses algorithms to analyze geographic data, identify candidate sites, and determine optimal locations. The system automatically processes large datasets, performs radio predictive tasks, and generates site plans without requiring manual iteration by engineers, thereby significantly improving productivity while reducing the complexity burden on planners.
Solution Approach 2:
The system enables self-service planning by allowing users to input basic requirements and geographic boundaries, then automatically generating comprehensive site plans through integrated algorithms. The platform performs data collection, analysis, and optimization autonomously, reducing the need for manual intervention in routine planning tasks while maintaining planning quality.
2Productivity
If automated system is implemented, then productivity improves, but ease of operation deteriorates due to steep learning curve
Solution Approach 1:
The system provides a universal interface that handles multiple planning scenarios and service types through a single unified platform. Users can select different service categories (eMBB, uRLLC, mMTC) and geographic regions without needing to learn separate procedures for each. The system automatically adapts its analysis parameters based on the selected service type, maintaining ease of operation while improving productivity across diverse planning needs.
Solution Approach 2:
The system incorporates feedback mechanisms that provide real-time guidance and recommendations during the planning process. When users input geographic boundaries and service requirements, the system immediately generates candidate site lists and optimization suggestions, allowing users to review and adjust parameters intuitively. This interactive feedback loop reduces the learning curve by guiding users through complex analysis automatically.
3Manufacturing precision
If multiple iterations are performed manually, then optimization precision improves, but loss of time increases significantly
Solution Approach 1:
The system maintains continuous optimization by automatically performing multiple iterations of site analysis, ranking, and validation without interruption. The algorithm continuously refines candidate site lists based on coverage criteria, capacity requirements, and interference constraints, delivering optimized results in a single continuous processing cycle rather than requiring discrete manual iteration cycles, thereby reducing total time while maintaining precision.
Solution Approach 2:
The system performs preliminary data collection, processing, and pre-analysis actions automatically before the user initiates the planning process. Geographic data, infrastructure information, and radio predictive models are pre-loaded and processed in advance, so when users start a new planning task, the system can immediately begin optimization without time-consuming manual data preparation, significantly reducing the overall planning cycle duration while maintaining optimization quality.
4Productivity
If manual data collection is used, then data accuracy can be verified, but productivity deteriorates due to tedious work
Solution Approach 1:
The system introduces automated data intermediaries that collect, validate, and process geographic and infrastructure data from multiple sources including satellite imagery, census data, and existing network databases. These automated intermediaries perform data verification and quality control through built-in validation rules and cross-checking algorithms, ensuring data reliability while processing information at speeds impossible for manual collection, thereby improving both productivity and maintaining accuracy.
Data Source
AI summary
The present invention discloses a method for determining and deploying a nominal site location for cellular planning in a wireless network. The method comprising receiving, from one or more data sources, geographic data related to a geographic region of interest. The method comprising obtaining a data for the geographic region of interest. The method comprising receiving at least one input for the cellular planning. The method comprising identifying a first nominal location based on the obtained data and the at least one input. The method comprising determining at least one second nominal location based on processing the first nominal location, the obtained data and the at least one input.