5G Standalone O-RAN Cell-Site Dimensioning for Traffic and Coverage
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Solution Overview
Problem
Existing wireless communication networks face challenges in efficiently determining the optimal number and placement of cell sites to meet capacity and coverage requirements in diverse geographic areas, leading to inefficiencies and increased capital expenditures.
Innovation Solution
A method and system for capacity dimensioning of cell sites that utilizes input data such as subscriber amounts, traffic models, and propagation models to estimate the number of cell sites needed for each sub-area within a target service area, considering factors like maximum allowable path loss and site capacity, to generate a report for network planning.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional methods are used to determine cell site placement, then network coverage can be achieved, but capital expenditures increase and efficiency decreases
Solution Approach 1:
The patent segments the service area into multiple sub-areas with different service area types (urban, suburban, rural). For each sub-area, the system independently determines the number of cell sites needed based on local traffic estimates and coverage requirements. This segmentation allows optimized resource allocation where urban areas receive more sites than rural areas, reducing overall capital expenditures while maintaining necessary network deployment efficiency.
Solution Approach 2:
The patent applies local quality by tailoring cell site determination to specific characteristics of each sub-area. Different service area types (urban, suburban, rural) receive different numbers of cell sites based on their unique traffic patterns, population density, and geographic characteristics. This localized approach ensures capital expenditures are optimized by not over-provisioning rural areas while adequately provisioning urban areas.
2Loss of time
If manual network planning methods are used, then cell site placement can be determined, but time required for deployment increases
Solution Approach 1:
The patent performs preliminary actions by automatically estimating traffic, determining coverage requirements, and calculating the number of cell sites needed for each sub-area before actual network deployment begins. The system processes subscriber forecasts, traffic models, and propagation models in advance to generate a complete cell site placement plan, significantly reducing the time required during the actual deployment phase while improving overall planning efficiency.
Solution Approach 2:
The patent uses copying by creating a virtual model of the service area with its sub-areas, subscriber distributions, and traffic patterns. This digital representation allows the system to simulate and determine optimal cell site placement without physical site surveys or manual calculations, dramatically reducing deployment time while enhancing planning efficiency through automated computational analysis.
3Measurement precision
If generic cell site estimation is used, then deployment can proceed quickly, but accuracy of cell site number estimation decreases
Solution Approach 1:
The patent improves measurement precision by segmenting the service area into multiple sub-areas with distinct service area types. Each sub-area undergoes independent traffic estimation using subscriber amounts, traffic mix models, and simulated busy hour data volumes. The system then separately determines coverage requirements and calculates cell sites needed for each sub-area based on its specific characteristics, yielding highly accurate estimates rather than generic approximations.
Solution Approach 2:
The patent applies local quality by using sub-area-specific parameters including service area type classifications, local subscriber densities, regional traffic patterns, and area-specific propagation models. This localized dimensioning approach tailors the complexity of the analysis to the specific needs of each sub-area, achieving high estimation accuracy where it matters most while managing overall system complexity through modular processing.
Data Source
AI summary
A method for capacity dimensioning of cell sites for a target service area having a set of sub-areas where each sub-area is associated with a service area type is provided. For each sub-area, the method includes determining a total traffic estimation based on a first set of inputs that includes a subscriber amount and forecast, subscriber class(es), a traffic mix end model, and a simulated busy hour data volume, determining a total coverage estimation based on a second set of inputs that includes an area size probability, a site area, a propagation model, and a maximum allowable path loss, determining a number of capacity sites based on the total traffic estimation and a site capacity, determining a number of coverage sites based on the total coverage estimation, and determining a number of cell sites for the sub-area based on the number of capacity sites and the number of coverage sites.