Dynamic Antenna Azimuth Adjustment for Network Performance
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Solution Overview
Problem
Existing radio planning processes for base stations rely on approximations and simulations, leading to inconsistencies and inefficiencies in antenna azimuth settings, resulting in underperformance due to uneven user distribution and traffic variations over time.
Innovation Solution
A method and system for dynamically adjusting antenna azimuth headings based on real-time data from mobile users, optimizing network performance by comparing average values of network performance parameters across different azimuth settings to determine the optimal heading for improved resource allocation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If radio planning parameters are based on propagation models and simulations, then antenna azimuth can be initially configured, but inconsistencies and errors occur due to approximation of radio conditions and traffic distribution
Solution Approach 1:
The system collects actual network performance data from mobile users in the geographical area, compares it with predicted performance from propagation models, and uses this feedback to dynamically adjust antenna azimuth values. This closed-loop feedback mechanism resolves the contradiction by continuously correcting the initial model-based configuration with real-world measurements, thereby improving prediction accuracy while maintaining ease of configuration.
Solution Approach 2:
The system performs preliminary configuration using propagation models and simulations to establish initial antenna azimuth values before actual deployment. This preliminary action provides a starting point that is easy to configure, while subsequent dynamic adjustments based on actual performance data refine the accuracy of radio condition predictions, thus resolving the contradiction between ease of configuration and prediction accuracy.
2Device complexity
If antenna azimuth is fixed based on initial planning, then implementation is simple, but performance deteriorates due to uneven user distribution and traffic variations over time
Solution Approach 1:
The system transitions from a static, fixed antenna azimuth configuration to a dynamic system that automatically adjusts azimuth values based on real-time network performance data and user distribution patterns. This dynamic adaptation resolves the contradiction by maintaining system simplicity through automation while significantly improving network capacity and coverage performance in response to changing traffic conditions.
Solution Approach 2:
The system enables the antenna configuration to self-adjust based on collected performance data without requiring manual reconfiguration by network operators. The automated process monitors network performance, identifies optimal azimuth values, and implements adjustments independently, thus maintaining operational simplicity while enhancing productivity through continuous optimization.
3Reliability
If antenna radiation is directed according to planned user distribution, then initial coverage is established, but signal quality deteriorates due to actual user mobile distribution and behaviours
Solution Approach 1:
The system collects actual signal quality measurements and network performance data from mobile users, compares these measurements with the coverage established by planned antenna orientation, and uses this feedback to adjust azimuth values. This feedback loop resolves the contradiction by maintaining reliable initial coverage while continuously improving signal quality per user based on actual distribution patterns.
Solution Approach 2:
The system changes the antenna azimuth parameter dynamically based on collected performance data and actual user distribution patterns. By adjusting this key parameter, the system maintains reliable coverage establishment while improving signal quality for individual users, thus resolving the contradiction between initial coverage reliability and per-user signal quality precision.
Data Source
AI summary
A method of determining the optimum radio planning parameter of an antenna azimuth heading, comprising receiving, by a control system, a first set of data indicative of network performance for mobile devices of users within a specified geographical area covered by an antenna sector having a first azimuth heading; determining, by the control system, a first set of average values of parameters indicative of network performance based on the first set of data; receiving, by the control system, a second set of data indicative of network performance for mobile users within the specified geographical covered by an antenna having a second azimuth heading, wherein the second azimuth heading is different from the first azimuth heading, determining, by the control system, a second set of average values of parameters indicative of network performance for the antenna sector having the second azimuth value based on the second set of data; comparing the first and second sets of average values of parameters indicative of network performance at the first and second azimuth headings for the antenna sector to determine the azimuth heading at which the network performance is optimized.