Cellular Network Optimization via Iterative Parameter Adjustment
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Solution Overview
Problem
Existing methods for optimizing cellular wireless communication networks fail to efficiently balance subscriber traffic across cells, particularly in third-generation networks with diverse services, leading to suboptimal throughput and network quality, while maintaining existing network coverage and avoiding cell location changes.
Innovation Solution
A method that iteratively adjusts network configuration parameters such as aerial orientation and transmission power of reference signals to balance subscriber traffic distribution between cells, using available measured data and graphic displays to identify and address problem areas, without requiring elaborate simulations or measurements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional network optimization methods are used, then network coverage is maintained, but traffic distribution between cells remains unbalanced and throughput is suboptimal
Solution Approach 1:
The patent changes network configuration parameters (aerial orientation, transmission power of reference signals) to balance traffic distribution and improve throughput. This involves systematically adjusting parameters to achieve optimal traffic balancing without changing cell locations or requiring elaborate simulations.
Solution Approach 2:
The optimization method uses available measured data from the network itself to perform self-optimization. The system leverages existing network measurements and data to automatically determine optimized configurations without requiring external elaborate simulations or additional expensive field measurements.
2Productivity
If iterative adjustment of network configuration parameters is performed, then traffic distribution is balanced and throughput improves, but optimization time and computational resources increase
Solution Approach 1:
The patent performs iterative adjustments of network configuration parameters to achieve traffic balancing. Rather than requiring complete re-optimization, the method applies partial adjustments to specific parameters (aerial orientation, transmission power) that have the most impact on traffic distribution, reducing overall optimization time while still achieving throughput improvement.
3Manufacturing precision
If detailed simulations and measurements are used for optimization, then optimization accuracy improves, but cost and complexity of the optimization process increase
Solution Approach 1:
The optimization method uses available measured data from the network itself to perform self-optimization. The system leverages existing network measurements and data to automatically determine optimized configurations without requiring external elaborate simulations or additional expensive field measurements.
Solution Approach 2:
The patent creates a simplified model or representation of the network using available measured data, rather than requiring detailed physical simulations. This copying approach allows for accurate enough optimization decisions to be made using computational models based on real measurement data, reducing the need for expensive elaborate simulations.
Data Source
AI summary
A method of optimising real cellular, wireless communication networks comprising the steps of providing location-referenced values of subscriber traffic for area elements; transmitting a reference signal of constant transmission power; providing a cell-referenced value of the power received from the reference signal; providing a model of the communication network having an original model network configuration, and iteratively optimising the model network configuration by accumulating and weighting the subscriber traffic values of the area elements and by locally adjusting the model network configuration, to provide an optimised model network configuration.