Cellular Network Load Balancing via Signal and Population Data
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Solution Overview
Problem
Current cellular communication networks face challenges in automatically balancing load between cells of different priorities, leading to inefficient resource utilization and potential user experience issues due to manual parameter setting and lack of real-time optimization.
Innovation Solution
A computer-implemented method using a network model with signal level and population data to dynamically adjust a threshold parameter, automatically directing users between higher and lower priority cells to balance load, with periodic repetition and conditional parameter updates to ensure resource availability and minimal impact on other cells.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If manual parameter setting is used to balance load between cells, then network operator control is maintained, but automation and real-time optimization are lost
Solution Approach 1:
The network system performs self-optimization by automatically detecting high load conditions in first cells and adjusting network parameters to balance load with second cells, eliminating the need for manual operator intervention while maintaining intelligent control
Solution Approach 2:
The system pre-calculates network models including signal level information and population data before load balancing is needed, enabling rapid automatic response when high load conditions are detected without complex real-time computations
2Productivity
If network parameters are adjusted to balance load, then user distribution is optimized, but impact on other cells and resource availability must be managed
Solution Approach 1:
The system monitors load conditions in first cells and resource availability in second cells, using this feedback to dynamically adjust network parameters and determine when load balancing should be applied or avoided
Solution Approach 2:
The load balancing mechanism applies parameter adjustments locally to specific first cells experiencing high load, rather than uniformly across the entire network, allowing targeted optimization without disrupting other cells
Data Source
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AI summary
A computer implemented method of balancing load in a cellular network comprising first cells with a first priority and second cells with a second priority. The method comprises: detecting a high load condition in a first cell (21); using a network model comprising signal level information on different geographical locations for different cells to find a second cell (22) having at least partially overlapping service area (25) with the first cell; using said network model and population data comprising information about number of users on different geographical locations to determine a value to a network parameter that has an effect on whether a user connects to the first cell or to the second cell; and conditionally taking the determined value of the network parameter in use in the cellular network to balance load between the first and the second cell in the overlapping service area.