Wireless Load Balance Model Using Server-Side Training
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Solution Overview
Problem
In wireless communication systems, there is a need to address the imbalance in data throughputs and communication loads between cells using different frequency bands, and existing methods lack effective methods for evaluating load balancing parameters and their performance.
Innovation Solution
A method and apparatus that utilize a server to acquire configuration and performance management information, train a load balance model, and determine a second load balance parameter for distributing communication traffic, based on output from candidate parameters, to optimize load balancing across cells with different frequency bands.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If load balance parameters are applied to base stations to control traffic distribution, then communication load balance between cells is improved, but there is a lack of effective methods for evaluating the applied parameters and their performance
Solution Approach 1:
The patent implements a feedback mechanism where the server continuously monitors performance management information (PMI) including throughput, load, and service quality indicators. This feedback loop enables automatic adjustment of load balance parameters based on actual network performance, resolving the contradiction by providing both performance improvement through continuous optimization and reduced complexity through automated closed-loop control without manual intervention
Solution Approach 2:
The load balance system operates autonomously with the server automatically acquiring configuration management information, training load balance models using machine learning algorithms, determining optimal parameters, and applying them to base stations without external intervention. This self-service approach improves load balance performance while eliminating the complexity of manual parameter evaluation and adjustment
2Productivity
If multiple cells with different frequency bands are used in a sector, then communication capacity and coverage are improved, but imbalance in data throughputs and communication loads occurs between cells
Solution Approach 1:
The patent applies different load balance parameters to different cells within the same sector based on their specific characteristics such as frequency band, throughput performance, and load conditions. The server dynamically adjusts parameters like handover thresholds and cell reselection offsets for each cell, enabling local optimization that maintains overall system capacity while achieving throughput balance across heterogeneous cells
Solution Approach 2:
The system dynamically changes load balance parameters including handover hysteresis, cell reselection offsets, and traffic steering ratios based on real-time performance management information. By continuously adjusting these parameters in response to throughput imbalances and load variations, the system maintains both high communication capacity and equitable resource distribution across cells with different frequency bands
Data Source
AI summary
A method performed by a server in a wireless communication system is provided. The method includes acquiring first configuration management (CM) information and first performance management (PM) information during a first period for a sector managed by the server, training a load balance model based on the first CM information and the first PM information, and determining a second load balance parameter to be used for distribution of communication traffic within the sector based on output information output upon an input of each of multiple candidate load balance parameters to the load balance model. The first CM information includes a first load balance parameter, and the first PM information includes at least one PM value.