Indoor Distribution Topology Acquisition via Position Feedback
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Solution Overview
Problem
The manual configuration of network topology in indoor distribution systems is labor-intensive and prone to errors, leading to high costs and reduced accuracy.
Innovation Solution
A method for acquiring network topology in indoor distribution systems involves the host unit receiving position information from extended units, including first-level and second-level information such as gain control values of remote units, to determine the network topology structure automatically, reducing labor costs and increasing accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual configuration of network topology is used, then deployment information can be recorded, but labor cost increases and accuracy decreases
Solution Approach 1:
The system automatically acquires network topology information by having each extended unit self-report its position information and gain control values to the host unit, eliminating the need for manual configuration by technicians. This self-service mechanism resolves the contradiction by automating the topology acquisition process while maintaining high accuracy through direct data collection from network elements.
Solution Approach 2:
The host unit receives position information and gain control values from extended units, processes this feedback data, and automatically determines the network topology structure. This feedback loop enables automated topology acquisition, resolving the contradiction between manual configuration requirements and automation extent while ensuring accurate topology representation.
2Productivity
If manual configuration of network topology is used, then deployment information can be recorded, but labor cost increases
Solution Approach 1:
Each extended unit automatically transmits its position information and gain control values to the host unit without requiring technician intervention. This self-service approach dramatically improves productivity by enabling automated topology acquisition while eliminating the need for manual labor, directly resolving the contradiction between productivity and labor cost.
Solution Approach 2:
The patent replaces the mechanical manual configuration process with an automated electronic information transmission system. Extended units electronically transmit their configuration data to the host unit, which automatically processes this information to determine network topology. This substitution of manual mechanical operations with automated electronic systems resolves the contradiction by improving productivity while reducing labor cost.
3Extent of automation
If automated topology acquisition is implemented, then labor cost reduces, but system complexity increases
Solution Approach 1:
The automated topology acquisition process is segmented into distinct functional components: extended units that generate and transmit position information, a transmission medium that carries the data, and a host unit that receives and processes the information to determine topology. This segmentation of the automation process into modular functional blocks manages system complexity by distributing processing tasks across different network elements rather than concentrating all complexity in one component.
Solution Approach 2:
The host unit performs multiple functions: it receives position information from extended units, processes this information to determine network topology, and maintains the topology database. This multi-functionality reduces overall system complexity by consolidating processing, transmission, and storage functions within the host unit rather than requiring separate dedicated components for each function.
Data Source
AI summary
The present disclosure provides a method for acquiring a network topology and an indoor distribution system. The method comprises: a host unit receives position information transmitted by each extended unit connected to the host unit, and determines a network topology structure according to the position information. In this way, the labor cost can be reduced. In addition, the network topology structure obtained by the method provided by the present disclosure has higher accuracy, so that position information of each node can be learnt at a host unit, the fault can be quickly located, and the system operation and maintenance cost is reduced.