Self-optimizing network balancing coverage and capacity
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Solution Overview
Problem
Wireless communication networks face challenges in optimizing coverage, capacity, and interference simultaneously, with existing algorithms often conflicting and neglecting uplink considerations, leading to suboptimal performance, especially at the cell edge where user satisfaction is poorest.
Innovation Solution
The technology jointly optimizes coverage, capacity, and layer balance by modifying antenna parameters, handover biases, scheduling priorities, and interference mitigation, considering both uplink and downlink aspects to achieve synergistic improvements while maintaining minimum cell edge user performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If coverage optimization is performed by increasing antenna uptilt, then coverage is improved, but capacity deteriorates due to antenna downtilt requirements
Solution Approach 1:
The patent implements dynamic adjustment of antenna parameters (electrical tilt, azimuth, power) based on real-time network conditions and user distribution. Instead of static optimization, the system continuously adapts antenna configurations to balance coverage and capacity requirements, allowing the network to transition between coverage-mode and capacity-mode operations as needed.
Solution Approach 2:
The system changes multiple antenna parameters simultaneously (tilt angle, azimuth direction, transmit power) rather than adjusting single parameters in isolation. This multi-parameter optimization allows the network to achieve both improved coverage and maintained capacity by coordinating changes across different antenna characteristics to produce synergistic effects.
2Ease of operation
If separate independent optimization algorithms are used for coverage, capacity and interference, then each optimization can be performed independently, but the algorithms counteract each other and overall performance deteriorates
Solution Approach 1:
The patent merges separate optimization algorithms into a unified joint optimization framework that simultaneously considers coverage, capacity, and interference objectives. The system integrates multiple optimization goals into a single coordinated optimization process, eliminating counteracting effects while maintaining the ability to address each objective through specialized sub-routines that work together harmoniously.
Solution Approach 2:
The optimization system performs multiple functions simultaneously - it optimizes for coverage, capacity, and interference reduction in a single unified process. The algorithm is designed to handle diverse optimization objectives with a single multi-functional framework, making the system versatile enough to address various network conditions and performance requirements without needing separate independent algorithms.
3Area of stationary object
If downlink coverage optimization is prioritized, then downlink performance is improved, but uplink performance deteriorates due to neglected uplink considerations
Solution Approach 1:
The system creates equipotential optimization by treating uplink and downlink coverage with equal importance and applying symmetric optimization principles to both directions. The joint optimization algorithm balances uplink and downlink performance metrics, ensuring that improvements in one direction do not come at the expense of the other, thereby achieving equitable performance across both transmission directions.
Solution Approach 2:
The system implements feedback mechanisms that monitor both uplink and downlink performance metrics simultaneously. By measuring actual uplink coverage conditions and feeding this information back into the optimization process, the system can adjust antenna parameters to maintain balanced uplink-downlink performance, preventing downlink-optimized configurations from degrading uplink service quality.
Data Source
AI summary
The described technology is generally directed towards jointly optimizing coverage, capacity, and layer balance in a wireless communications network while maintaining cell edge use device performance constraints. Aspects comprise monitoring edge user devices for performance information, and modifying the network based on the performance information, including jointly optimizing by changing antenna parameter data, layer balancing, handover biasing per cell neighbor pair, modifying scheduling priorities, and optimizing sector face harmonic throughput. Balancing uplink and downlink coverages are considered in the joint optimization. Further, interference is detected, predicted (as needed) and mitigated.