Wireless Network Parameter Control via Fixed Status
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Solution Overview
Problem
Self-organizing wireless telecommunication networks may not always set optimal parameters, and network operators need a method to manually intervene or test alternative parameters to improve network performance, especially in cases where self-organizing networks fail to address errors.
Innovation Solution
A method where a network entity sets a first parameter as fixed or temporarily fixed, allowing manual intervention, and then uses this parameter as a basis for optimizing other parameters within the network using self-organizing algorithms, ensuring that certain parameters cannot be changed by lower-priority algorithms and allowing for manual override or automatic adjustment based on trigger conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If self-organizing algorithms automatically optimize parameters, then network performance is improved through automated adaptation, but network operators lose the ability to manually intervene or test alternative parameters
Solution Approach 1:
The patent implements dynamic parameter status management where parameters can transition between different states (e.g., from fixed to variable). Network entities can mark parameters as fixed to prevent automatic changes, or change their status to allow self-organizing algorithms to optimize them. This dynamic state management resolves the contradiction by allowing both manual control and automated optimization depending on the operational context.
Solution Approach 2:
The patent changes the status parameter of network parameters to control their modifiability. By setting a parameter status to 'fixed', the system prevents self-organizing algorithms from modifying that parameter, thereby allowing manual intervention. When the status is changed to 'variable', automatic optimization can proceed. This parameter status mechanism enables operators to switch between manual control and automated optimization modes.
2Reliability
If parameters are set manually by network operators, then specific optimization goals can be achieved, but the self-organizing network's ability to adapt to changing conditions is reduced
Solution Approach 1:
The system dynamically manages parameter states, allowing operators to fix parameters when specific optimization goals are needed, and automatically change their state to variable when the network needs to adapt to changing conditions. This dynamic state transition enables the network to switch between manual optimization modes and automatic adaptation modes as required by operational needs.
Solution Approach 2:
The patent implements periodic review mechanisms where the system automatically checks whether manually fixed parameters should be changed to variable status based on current network conditions. This periodic action allows the network to maintain manual optimization benefits when needed while automatically transitioning to adaptive modes when conditions change, balancing reliability with versatility.
3Productivity
If self-organizing algorithms continuously optimize parameters, then network performance is maintained, but manual override capability is lost
Solution Approach 1:
The system uses parameter status changes to control optimization behavior. When a parameter is marked as 'fixed', self-organizing algorithms stop optimizing it, allowing manual override. When the status is changed to 'variable', automatic optimization resumes. This status mechanism maintains high productivity through continuous optimization while preserving manual override capability when operators mark parameters as fixed.
Solution Approach 2:
The system implements feedback mechanisms where network entities can detect when manual intervention is needed and communicate this to self-organizing algorithms. The algorithms respond by adjusting their optimization behavior based on feedback signals indicating fixed parameters, thereby maintaining efficient automatic optimization while respecting manual override intentions.
4Reliability
If network operators manually set parameters, then specific performance goals can be tested, but the self-organizing network structure is disrupted
Solution Approach 1:
The patent introduces a parameter status field that can be set to 'fixed' or 'variable'. This simple status change allows operators to manually control parameters without disrupting the overall self-organizing network structure. The status mechanism is lightweight and integrates seamlessly with existing self-organizing algorithms, maintaining network simplicity while enabling manual intervention for performance testing.
Solution Approach 2:
The system segments parameter control into two distinct modes: manual control mode (when status is fixed) and automatic optimization mode (when status is variable). This segmentation allows operators to manually set parameters for specific testing purposes without affecting the rest of the self-organizing network structure, thereby maintaining overall network simplicity while enabling targeted manual intervention.
Data Source
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AI summary
The invention relates to a method of setting a plurality of wireless telecommunication parameters in a wireless telecommunication network (400), wherein the method comprises the following steps: - setting (106) a first parameter of the plurality of wireless telecommunication parameters in a first cell by a network entity (104); - running (110; 206) an algorithm for optimizing at least one second parameter of the plurality of wireless telecommunication parameters in the first and/or at least one second cell dependent on the first parameter.