Multi-Hop Cellular Path Management Using Link Quality and Traffic Load
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Solution Overview
Problem
Existing multi-hop cellular networks face inefficiencies in path establishment, leading to suboptimal service admission rates and performance, as they typically rely on selecting paths based solely on signal strength without considering link quality, traffic load, and frequency channel size.
Innovation Solution
A mobile system that receives information on link quality, traffic load, and frequency channel size to calculate and select the most efficient path to a base station or relay station, using an increasing resource usage rate calculation unit and selection unit to balance resource allocation and minimize resource usage rates.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If path selection is based solely on signal strength, then the path establishment process is simple, but the service admission rate decreases and system performance deteriorates
Solution Approach 1:
The patent changes the selection parameters from only signal strength to multiple parameters including signal strength, link quality, traffic load, and frequency channel size. This allows the system to make more informed path selection decisions that improve service admission rates while maintaining reasonable complexity through structured evaluation of these parameters.
Solution Approach 2:
The system implements feedback mechanisms where link quality information, traffic load information, and resource usage rates are continuously monitored and used to adjust path selection decisions. This feedback loop enables dynamic path optimization that improves service admission rates based on current network conditions.
2Productivity
If path selection considers multiple parameters (link quality, traffic load, frequency channel size), then service admission rate increases, but the complexity of path establishment increases
Solution Approach 1:
The path establishment process is segmented into distinct evaluation components: signal strength evaluation, link quality evaluation, traffic load evaluation, and frequency channel size evaluation. Each parameter is assessed separately and then integrated to form the final path selection decision, making the complex process more manageable and systematic.
Solution Approach 2:
The system introduces a standardized multi-parameter evaluation framework that transforms complex path selection into a structured process. By defining specific parameters (link quality, traffic load, frequency channel size) and their evaluation methods, the system manages complexity through parameter standardization while achieving improved service admission rates.
3Stability of the object's composition
If resources are allocated to balance efficiency and evenness across the system, then system evenness improves, but resource usage rates increase
Solution Approach 1:
The system changes the resource allocation approach by introducing increasing resource usage rate calculations that consider future resource consumption patterns. This allows the system to balance efficiency and evenness while controlling overall resource usage through predictive resource management rather than simple load balancing.
Solution Approach 2:
The system performs preliminary calculations of increasing resource usage rates before final path selection. By anticipating future resource consumption and planning resource allocation in advance, the system can balance load across the network to improve evenness while preventing excessive resource usage through proactive resource management.
Data Source
AI summary
A mobile system, a mobile system, a method for managing a path in a multi-hop cellular network, and a data frame used in the mobile system. The mobile system includes: an information receiving unit to receive information about at least one of link quality, traffic load, and frequency channel size, via a network; and a path establishment unit to establish a path to a base station based on the received information.


