Cell Site Deployment Planning for Capacity and Interference Balance
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Solution Overview
Problem
Existing cell site deployment strategies in telecommunications networks often require significant investment and can lead to uneven performance improvements, leaving zones of poor connectivity due to uneven capacity distribution and increased interference.
Innovation Solution
A method involving obtaining a baseline network performance map, generating signal propagation maps for potential cell sites, and predicting network performance post-deployment to evaluate the impact of deployment plans, allowing for quantitative assessment of effects and cost-benefit analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If new cell sites are added to increase capacity uniformly, then network capacity is improved, but investment cost and time increase significantly
Solution Approach 1:
The system performs preliminary signal propagation modeling and impact assessment before actual deployment. By predicting the effects of potential cell sites in advance using baseline network performance maps and signal propagation models, the system identifies optimal deployment locations and evaluates their impact beforehand, enabling more efficient and targeted deployment strategies that reduce overall time and resource investment.
2Quantity of substance
If new cell sites are added to increase capacity uniformly, then network capacity is improved, but investment cost increases significantly
Solution Approach 1:
The system applies local quality by analyzing and addressing specific areas with poor network performance rather than implementing uniform improvements across the entire network. By generating signal propagation maps and assessing impacts at localized levels, the system identifies specific zones that require capacity enhancement and targets deployments to those areas, optimizing the investment-cost to capacity-gain ratio.
Solution Approach 2:
The system changes the approach from uniform capacity increase to targeted capacity enhancement by modifying deployment parameters based on predicted impact. Using baseline network performance data and signal propagation models, the system adjusts deployment strategies to focus on locations where signal propagation analysis indicates highest impact, thereby reducing overall investment cost while achieving necessary capacity improvements.
3Quantity of substance
If new cell sites are deployed, then capacity is improved, but signal interference increases
Solution Approach 1:
The system converts the potentially harmful effect of increased signal interference into a beneficial planning parameter by using signal propagation models to predict interference patterns before deployment. By analyzing baseline network performance and modeling signal propagation from potential cell sites, the system identifies locations where capacity improvement can be achieved with minimal interference, effectively turning interference prediction into a tool for optimizing deployment decisions.
4Productivity
If deployment plan is implemented without evaluation, then deployment speed increases, but performance improvement is uneven
Solution Approach 1:
The system performs preliminary impact assessment using baseline network performance maps and signal propagation models before deployment is executed. This preliminary analysis predicts the effects of proposed cell sites and identifies potential performance issues beforehand, allowing the deployment plan to be optimized for uniform performance improvement while maintaining efficient deployment speed through automated evaluation processes.
Data Source
AI summary
A computer-implemented method is described for determining the impact of a cell site deployment plan on a telecommunications network, the method including: obtaining a map of baseline network performance of the telecommunications network in a target area; obtaining a deployment plan for the telecommunications network in the target area, wherein the deployment plan comprises a plurality of potential cell sites; generating, using a model, a signal propagation map for each of the plurality of potential cell sites; generating a map of predicted network performance of the telecommunications network after deployment of the deployment plan based on combining the map of baseline network performance and the plurality of signal propagation maps; determining an impact of the deployment plan by performing a comparison between the baseline network performance and predicted network performance.