Cell Site Deployment Planning with Cached Propagation Maps
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Solution Overview
Problem
Existing methods for increasing network capacity by adding cell sites to address high performance demands are resource-intensive and ineffective due to real-world obstacles interfering with signal transmission.
Innovation Solution
A method for generating and evaluating cell site deployment plans by obtaining clutter and installation site maps, modeling signal propagation, creating deployment plans with subsets of potential cell sites, and calculating fitness scores to determine effective network expansions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If new cell sites are added to increase network capacity, then network performance is improved, but resource investment and time requirements increase significantly
Solution Approach 1:
The system performs preliminary actions by pre-computing signal propagation maps for each potential cell site location before actual deployment. This allows the evaluation of multiple deployment plans using cached propagation data, avoiding repeated computationally intensive calculations and reducing resource requirements for plan evaluation.
Solution Approach 2:
The system creates simplified representations (copies) of the physical environment through signal propagation maps that model clutter effects. These maps serve as virtual copies that can be reused across multiple deployment plan evaluations, eliminating the need for repeated physical measurements or full-wave simulations.
2Measurement precision
If signal propagation is modeled for each potential cell site, then deployment plan accuracy is improved, but computational intensity increases
Solution Approach 1:
Signal propagation characteristics are pre-computed and stored as cached data for each potential cell site location before deployment planning begins. This preliminary computation allows multiple deployment plans to be evaluated using the same pre-computed propagation maps, significantly reducing the computational intensity of the overall planning process while maintaining accurate signal propagation modeling.
Solution Approach 2:
The computational problem is segmented by separating the signal propagation calculation from the deployment plan evaluation. The propagation map generation is performed once per potential cell site, while the deployment plan evaluation reuses these segmented results through combinatorial analysis of pre-computed data, reducing redundant calculations.
3Reliability
If clutter locations are taken into account, then signal transmission effectiveness is improved, but data processing complexity increases
Solution Approach 1:
The physical clutter environment is copied into simplified signal propagation maps that represent the effects of buildings and obstacles on signal transmission. These map copies capture the essential clutter characteristics without requiring complex real-time processing of detailed geometric models, enabling effective signal transmission prediction with reduced data processing complexity.
Data Source
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AI summary
A computer-implemented method for generating and evaluating a range of cell site deployment plans, the method comprising: obtaining a clutter location map comprising locations of buildings; obtaining an installation sites map comprising locations for possible cell sites; generating, using a model and the clutter location map, a signal propagation map for each of a plurality of possible cell sites from the installation sites map in a target deployment area; creating a plurality of deployment plans wherein each deployment plan comprises a different subset of the plurality of possible cell sites in the target deployment area; generating for each of the plurality of deployment plans a fitness score based on the signal propagation maps of the subset of the plurality of possible cell sites in the deployment plan.