Decentralized Small Cell Pilot Power Adjustment
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Solution Overview
Problem
Current methods for optimizing radio coverage in small cell networks, such as femtocells, face challenges due to random deployment patterns and increased backhaul signalling load, making centralized computation approaches impractical for decentralized systems.
Innovation Solution
A fully decentralized method that adjusts pilot channel transmit power based on local measurements and user reports, allowing each base station to operate independently without external information, and applies to any number of cells, optimizing coverage by reducing pilot signal strength to prevent overloading and increasing it to fill coverage holes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If centralized computation approaches are used for coverage optimization, then optimal network configuration can be calculated, but backhaul signalling load increases significantly
Solution Approach 1:
The patent divides the centralized optimization problem into independent local decision-making units at each base station. Each BS segments the optimization task by independently determining its own coverage area and adjusting parameters based on local measurements, eliminating the need for continuous centralized computation and reducing backhaul signalling load.
Solution Approach 2:
Each base station autonomously performs coverage optimization by making local decisions based on measurements from user equipment. The system enables self-service optimization where BSs independently adjust their coverage parameters without requiring centralized control, thereby reducing backhaul signalling requirements.
2Manufacturing precision
If precise pre-rollout network planning is implemented, then initial configuration accuracy improves, but deployment flexibility decreases
Solution Approach 1:
The patent implements dynamic coverage optimization where base stations continuously adapt their coverage parameters based on real-time measurements from user equipment. This dynamic adjustment allows the network to maintain flexibility in deployment while achieving accurate coverage optimization post-deployment, resolving the contradiction between initial configuration precision and deployment flexibility.
3Productivity
If coverage optimization requires information from neighbouring cells, then load balancing improves, but system complexity increases
Solution Approach 1:
The patent implements local quality by having each base station optimize its coverage independently based on local measurements from its own user equipment. Each BS determines its coverage area and adjusts parameters locally without requiring information exchange with neighbouring cells, thereby achieving load balancing through localized decisions while minimizing system complexity.
Data Source
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AI summary
In order to provide a fully decentralised procedure for optimising radio coverage in small cells of a mobile telecommunications system, which does not require significant transmission of information on backhaul connections of the system, a method of optimising radio coverage of a cell comprises: determining the current number of users of the base station of the cell, and comparing the current number with a predetermined maximum value, determining, from signal reports from users to the base station, candidate users that are detecting more than one base station and may be dropped and handed over to a neighbouring cell, and if the current number of users is greater than the maximum value, adjusting pilot transmission signal strength of the base station by an amount dependent on the signal reports made by the candidate users