Cell Parameter Optimization for Wireless Coverage and Call Quality
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Solution Overview
Problem
Wireless communication networks face limitations in call quality and coverage, with traditional solutions like adding base stations being costly and inflexible, and existing optimizations being computationally complex and ineffective at the cell or neighbor granularity.
Innovation Solution
A computer-implemented method that adjusts radio access network parameters based on key performance indicators correlated with predefined rules, allowing for iterative optimization of cell size, shape, and handover settings to improve call quality and coverage without requiring additional hardware.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If more base station sites are added to provide additional coverage, then coverage is improved, but capital expenditure and operating expenses increase significantly
Solution Approach 1:
The patent changes operational parameters of existing base stations (transmit power levels, antenna tilt angles, handover thresholds) to expand coverage areas without adding new hardware. By adjusting these parameters, the system achieves coverage improvement equivalent to adding new sites while avoiding the associated capital and operating expenses.
Solution Approach 2:
The system performs self-optimization by automatically analyzing performance data and adjusting parameters to improve coverage. This self-service capability eliminates the need for manual site surveys and hardware installations, providing coverage expansion through intelligent parameter management rather than physical infrastructure expansion.
2Reliability
If radio resource parameters are adjusted at network or cluster level to improve call quality, then call quality may be improved, but computational complexity and data analysis requirements become prohibitively high
Solution Approach 1:
The patent segments the optimization problem from network-wide to cell-level granularity. By focusing adjustments on individual cells rather than the entire network, the computational complexity is dramatically reduced while maintaining call quality improvements. Each cell can be optimized independently using localized performance data.
Solution Approach 2:
The system applies partial optimization by focusing on specific parameters and cells that have the most impact on call quality, rather than attempting to optimize all parameters across the entire network. This selective approach achieves practical call quality improvement without the prohibitive computational burden of exhaustive optimization.
3Reliability
If traditional parameter adjustments are made at network level, then some call quality improvement may be achieved, but the solution lacks flexibility for localized optimization
Solution Approach 1:
The patent implements local quality by enabling independent parameter optimization for each cell based on its specific performance characteristics and local conditions. This allows tailored adjustments to transmit power, antenna tilt, and handover parameters for individual cells, providing the flexibility needed for localized call quality improvement while maintaining network-wide coordination.
Data Source
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AI summary
Described herein is a computer implemented method for improving call quality and coverage of cells (A, B, C) within a mobile wireless communication network (20, 210). Such improvements can be accomplished by adjusting various radio access network parameters. The adjustments may be made at the cell level or at the neighbor level. An iterative process can periodically collect key performance indicator (KPI) statistics from the mobile wireless network. System improvements may derive from one or more rules (240) relating to performance indicators to parameters in the wireless communications network. Each rule can have a unique combination of minimum or maximum KPI thresholds. System issues may be identified when a cell correlates (530) with one or more of the rules which may then suggest one or more parameter changes to reduce the identified system issue. System capacity policies may be provided as limits to the coverage and call quality triggers.