Indoor Small-Cell Location Identification and Building Prioritization
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Solution Overview
Problem
Current solutions lack the ability to effectively identify and prioritize buildings for the deployment of indoor small cells, such as Wi-Fi, LTE small cells, and FTTx solutions, leading to inefficient network management and coverage issues.
Innovation Solution
An IISCs algorithm utilizing crowdsourced data and building layer information to identify potential buildings for indoor solutions, combined with a correlation engine for coverage and capacity checks, prioritizes buildings based on priority levels (P1, P2, P3, and P4) using RSRP and user utilization thresholds.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If indoor small cells are deployed without systematic identification and prioritization of buildings, then deployment cost and time are reduced, but network coverage and congestion management deteriorate
Solution Approach 1:
The system performs preliminary identification and prioritization of buildings before actual small cell deployment. By analyzing building characteristics, user density, and network capacity requirements in advance, the system creates a prioritization list that guides subsequent deployment actions, ensuring that high-need buildings are addressed first while maintaining efficient resource utilization
Solution Approach 2:
The deployment process is segmented into distinct phases: building identification, priority assignment (P1-P4 levels), capacity analysis, and deployment execution. This segmentation allows the system to systematically manage the complex deployment task by breaking it down into manageable steps, each with specific objectives and criteria
2Reliability
If comprehensive building analysis and prioritization systems are implemented, then network coverage and resource optimization improve, but system complexity and implementation cost increase
Solution Approach 1:
The prioritization system serves multiple functions simultaneously: it identifies buildings needing coverage, ranks them by priority, analyzes network capacity requirements, and generates deployment recommendations. This multi-functionality consolidates what would otherwise require separate systems into a single integrated platform, managing complexity while delivering comprehensive network optimization
Solution Approach 2:
The system transforms raw network data and building information into standardized priority parameters (P1-P4) and capacity metrics. By converting diverse input data into uniform output parameters that drive deployment decisions, the system simplifies the complexity of analyzing multiple variables while maintaining the ability to make informed coverage and resource optimization decisions
Data Source
AI summary
In some embodiments, a method includes determining whether a network serving cell serving a building is highly utilized; and determining an amount of users of the network serving cell that are included in the building per twenty-four-hour period.