Cell Site Deployment Planning with Clutter-Aware Signal Modeling
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Solution Overview
Problem
Existing methods for enhancing mobile network performance through overprovisioning cell sites are resource-intensive and ineffective in real-world conditions due to signal interference from obstacles, leading to suboptimal network deployment.
Innovation Solution
A method that generates and evaluates a range of cell site deployment plans by modeling signal propagation using clutter location maps and installation site maps, calculating fitness scores for each plan, and selecting optimal subsets of cell sites to improve network performance efficiently.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If overprovisioning cell sites is used to increase network capacity, then network performance is improved, but resource consumption and investment time increase significantly
Solution Approach 1:
The system performs preliminary signal propagation modeling and fitness score evaluation for multiple potential cell site locations before actual deployment. By pre-computing which locations will be most effective based on clutter maps and network requirements, the system avoids deploying cell sites that would be ineffective, thus reducing resource consumption while maintaining network performance improvements.
Solution Approach 2:
The system changes the approach from brute-force overprovisioning to optimized selection by introducing fitness scores that evaluate multiple parameters including signal propagation characteristics, clutter interference, and network capacity requirements. This parameter-based optimization allows achieving the same network performance improvement with fewer cell sites, reducing resource consumption.
2Reliability
If traditional cell site deployment methods are used without considering obstacles, then deployment speed is faster, but signal transmission effectiveness decreases due to interference from buildings and clutter
Solution Approach 1:
The system creates clutter location maps and performs signal propagation modeling before cell site deployment. By pre-identifying areas with poor signal transmission due to obstacles and selecting cell site locations that avoid these problematic areas, the system ensures effective signal transmission while managing deployment complexity through automated planning.
Solution Approach 2:
The system uses computational models to create virtual representations (signal propagation maps) of how radio waves will behave in the physical environment with buildings and clutter. These modeled maps allow evaluation of deployment effectiveness without physical trial-and-error, improving signal transmission effectiveness while keeping actual deployment relatively simple.
3Measurement precision
If signal propagation maps are re-computed for each deployment plan evaluation, then evaluation accuracy is higher, but computational time and resources increase significantly
Solution Approach 1:
The system pre-computes signal propagation maps for each individual cell site location before evaluating deployment plans. By having these baseline propagation maps ready in advance, the system can efficiently evaluate multiple deployment plans by combining pre-computed maps rather than re-computing signal propagation from scratch for each plan, thus maintaining evaluation accuracy while reducing computational time.
Solution Approach 2:
The system merges pre-computed signal propagation maps from multiple individual cell sites to evaluate the combined effect of different deployment plans. This approach allows accurate evaluation of how multiple cell sites work together without requiring separate full recomputations, achieving both high evaluation accuracy and computational efficiency.
Data Source
AI summary
A computer-implemented method is described, for generating and evaluating a range of cell site deployment plans, the method including: 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; and 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.