Antenna Beam Optimization Algorithm Pace Control
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Solution Overview
Problem
Current antenna beam optimization algorithms, such as RAS-SON, are inefficient and time-consuming due to the need for gradual adjustments to minimize the risk of creating coverage holes, leading to prolonged tuning times in wireless communication networks.
Innovation Solution
A wireless communication node determines the degree of coverage overlap with neighboring nodes and adjusts the optimization algorithm's pace accordingly, designating backup nodes to ensure efficient beam pattern optimization without increasing the risk of coverage holes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If antenna parameter settings are changed with very small steps to minimize the risk of creating coverage holes, then the risk of coverage holes is reduced, but the time consumption is increased
Solution Approach 1:
The system performs preliminary identification of backup nodes before executing the optimization algorithm. By pre-determining which neighboring nodes can provide backup coverage, the system creates a safety net that allows more aggressive optimization steps without risking coverage holes, thus resolving the contradiction between reliability and time consumption
Solution Approach 2:
The optimization algorithm dynamically adjusts its pace based on real-time feedback about backup node availability and coverage overlap degrees. When backup nodes are available, the algorithm accelerates; when coverage conditions are critical, it slows down, thereby adapting the optimization speed to current network conditions while maintaining reliability
2Productivity
If the optimization algorithm runs at a fast pace to reduce tuning time, then productivity is improved, but the risk of creating coverage holes increases
Solution Approach 1:
The system continuously monitors coverage overlap degrees and backup node status during the optimization process, using this feedback to dynamically adjust the algorithm pace. This feedback mechanism ensures that fast optimization does not compromise reliability, as the system can slow down or pause when coverage risks are detected
Solution Approach 2:
Before executing fast optimization, the system preliminarily identifies and confirms the availability of backup nodes. This preliminary action creates a permissive condition that allows high-speed optimization while maintaining a safety guarantee, thus achieving both high productivity and reliability
3Measurement precision
If the algorithm evaluates each RAS setting for a long time to gather enough statistics, then measurement precision is improved, but the duration of action is increased
Solution Approach 1:
The system performs partial evaluation by focusing statistical gathering only on the most critical parameters and settings rather than exhaustively evaluating all possible combinations. By identifying and prioritizing key optimization parameters, the system achieves sufficient measurement precision with reduced evaluation time
Solution Approach 2:
The system performs preliminary identification of backup nodes and coverage overlap assessment before detailed statistical evaluation. This preliminary action filters out settings that are already covered by backup nodes, reducing the number of settings that require extensive statistical gathering while maintaining measurement precision for critical parameters
Data Source
AI summary
The present disclosure relates to a first wireless communication node (1) comprising at least one antenna arrangement (2), each antenna arrangement (2) having a beam pattern (3) with a certain first coverage (4). The first wireless communication node (1) is arranged to nm a configuration algorithm to optimize the beam pattern (3). The first wireless communication node (1) is also arranged to determine if at least one neighbouring wireless communication node (5, 6; 5′) is arranged to at least partly cover said first coverage (4) such that an at least partial overlap occurs, and to which degree said neighbouring wireless communication node (5, 6; 5′) covers said first coverage (4). The first wireless communication node (1) is furthermore arranged to run the algorithm at a certain pace in dependence of said degree. The present disclosure also relates to a corresponding method.