Mobile Base Station Dynamic Parameter Adjustment
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Solution Overview
Problem
Conventional wireless communication systems lack effective methods for network planning when base stations are mobile, leading to inefficiencies in resource utilization and increased network interference due to changing locations and conditions.
Innovation Solution
A method where a base station establishes initial operating parameters, performs searches to determine neighboring base stations and network conditions, and adjusts its parameters to optimize resource allocation and reduce interference, continuously monitoring and adapting to changes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If base stations are made mobile to improve network flexibility and coverage, then adaptability is improved, but network interference increases and resource utilization deteriorates due to changing locations and invalid a priori cell planning
Solution Approach 1:
The patent makes the base station parameters dynamic rather than static. The mobile base station continuously monitors neighboring base stations and network conditions, then adjusts its operating parameters (scrambling codes, CPICH power, etc.) in real-time based on current network state. This dynamic adaptation resolves the contradiction by allowing mobility while maintaining optimal interference levels through continuous parameter reconfiguration.
Solution Approach 2:
The patent implements a feedback mechanism where the mobile base station monitors network conditions and neighboring base stations, then uses this information to adjust its parameters. The search function continuously gathers network state information, and based on this feedback, the base station modifies its operating parameters to minimize interference while maintaining flexibility from mobility.
2Ease of manufacture
If a priori cell planning is performed for fixed base stations, then resource allocation is simplified, but the planning becomes invalid when base stations move, requiring network reconfiguration
Solution Approach 1:
The patent performs preliminary parameter establishment before base station admission to the network. The mobile base station pre-configures its operating parameters (scrambling codes, power levels, etc.) based on initial network information obtained through search functions. This preliminary configuration simplifies the admission process while maintaining the ability to adapt later through continuous monitoring and parameter adjustment.
Solution Approach 2:
The patent transitions from static a priori planning to dynamic continuous reconfiguration. Instead of performing cell planning only once for fixed base stations, the system continuously monitors network conditions and adjusts parameters as base stations move. This dynamic approach maintains the simplicity of initial configuration while adapting to mobility through ongoing parameter optimization.
3Device complexity
If base station parameters are fixed upon admission, then configuration is simplified, but resource utilization deteriorates as network conditions change and parameters become suboptimal
Solution Approach 1:
The patent implements continuous feedback monitoring where the mobile base station tracks network conditions and neighboring base stations after admission. Based on this feedback, the system automatically adjusts operating parameters (scrambling codes, CPICH power, resource allocations) to maintain optimal resource utilization. This feedback loop resolves the contradiction by keeping configuration management simple while achieving high resource utilization through adaptive reconfiguration.
Solution Approach 2:
The patent enables the mobile base station to self-adjust its parameters based on monitored network conditions. The base station performs searches, analyzes network state, and modifies its own operating parameters without requiring complex external reconfiguration procedures. This self-service capability maintains configuration simplicity while optimizing resource utilization through autonomous adaptation.
Data Source
AI summary
Prior to being admitted into the network, a base station establishes a set of operating parameters. Next, a search is performed to determine the presence and configuration of neighboring base stations and current network conditions. Based on the search results, an improved operating configuration is determined for the base station and the base station's operating parameters are adjusted. Once the base station is admitted to and is operating in the network, the base station continues to monitor neighboring base stations and network conditions and adjusts its operating parameters accordingly.