Triangular Coverage Region Analysis for Cellular Site Prioritization
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Solution Overview
Problem
Existing cellular network systems face issues with problematic service coverage due to new network areas, geography, or weather conditions, leading to dropped calls and poor network coverage, with no comprehensive solution available.
Innovation Solution
A system and method for determining signal transmission optimization by analyzing data, creating a grid layout, applying a coverage region algorithm, and prioritizing cellular site deployment based on numerical metrics and technological impacts, such as population density and signal strength, to enhance coverage and capacity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If cellular sites are deployed to improve coverage in problematic service areas, then network coverage and reliability are improved, but deployment cost and complexity increase
Solution Approach 1:
The geographical area is divided into triangular coverage regions formed by groups of three cellular sites. Each triangle represents a discrete coverage unit that can be independently analyzed and optimized. This segmentation allows the system to identify specific problem areas without having to evaluate the entire network at once, reducing deployment complexity while improving coverage reliability in targeted regions.
Solution Approach 2:
The system performs preliminary analysis by creating a grid layout of potential cellular site locations and pre-calculating triangular coverage regions before actual deployment. By intersecting these grids with cellular transmission data sets and applying coverage region algorithms in advance, the system identifies optimal deployment locations and prioritizes them based on technological impact, thereby reducing on-site deployment complexity and improving reliability through pre-planned strategic placement.
2Measurement precision
If comprehensive data analysis is performed to optimize site deployment, then deployment precision and coverage assessment accuracy are improved, but computational time and processing complexity increase
Solution Approach 1:
The system segments the comprehensive network analysis into discrete triangular coverage regions, each bounded by three cellular sites. By analyzing each triangle independently with specific coverage region algorithms, the system achieves precise coverage assessment for each localized area rather than performing monolithic network-wide analysis, thereby improving measurement precision while reducing overall computational time through parallel processing of segmented regions.
Solution Approach 2:
The system applies different analysis methods and criteria to different triangular coverage regions based on their specific characteristics. By intersecting cellular transmission data sets with grid layouts and applying coverage region algorithms tailored to each triangle's geometry and signal propagation characteristics, the system achieves locally optimized coverage assessment accuracy without uniformly applying complex computations across the entire network, thus balancing precision with computational efficiency.
Data Source
AI summary
Embodiments are directed towards systems and methods for determining signal transmission optimization of coverage regions. The method includes: creating a grid layout over a geographical area of coverage regions, the layout including a plurality of coverage region grids with associated cellular transmission data sets; applying a coverage region algorithm to analyze the cellular transmission data sets; prioritizing the plurality of coverage region grids for cellular site deployment; analyzing technological impacts on the geographical area of the prioritization of the plurality of coverage region grids; filtering the plurality of coverage region grids based on criteria set for each category; and prioritizing the plurality of coverage region grids for cellular site deployment.