Smart Taps Noise Source Isolation via CMTS Signal Blocking
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Mitigating noise in networks, particularly in hybrid fiber-coaxial (HFC) plants, is inefficient due to noise funneling, which obscures the source of noise, leading to costly truck roll hours and customer disruptions, as technicians rely on manual searches and guesswork to identify noise sources in a trial-and-error process.
Innovation Solution
Implementing a system with a cable modem termination system (CMTS) that selectively controls taps and switches to block signaling, using an iterative process to isolate noise sources by measuring noise deviations, and employing solid-state switches that can open and close rapidly to minimize service disruption, allowing for precise identification of noise sources through controlled signal blocking.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If technicians perform manual search and physical inspection to identify noise sources, then noise sources can be located, but technician time and customer downtime increase significantly
Solution Approach 1:
The system enables automatic noise source identification through the CMTS that autonomously controls taps and switches to isolate and identify noise sources without requiring manual technician intervention. The CMTS performs self-diagnosis by systematically blocking signals from different network segments and measuring noise deviations, eliminating the need for technicians to physically search for noise sources.
Solution Approach 2:
The patent replaces the mechanical manual search process with an automated electronic system. The CMTS uses electronic control of taps and switches, combined with electronic noise measurement and analysis, to substitute the physical trial-and-error inspection method. This automation eliminates the need for technicians to manually disconnect and isolate network portions.
2Measurement precision
If technicians physically disconnect or isolate portions of the network to check for noise association, then noise sources can be identified, but service disruption and customer downtime occur
Solution Approach 1:
The system implements periodic action by using the CMTS to systematically and sequentially control taps and switches to block signals from different network segments in a structured manner. This periodic control allows the system to methodically isolate noise sources through repeated measurement cycles without requiring permanent disconnections, thereby maintaining service continuity while identifying noise sources.
3Productivity
If noise funneling occurs at CMTS from multiple taps and branches, then signals converge for processing, but noise sources become obscured and harder to isolate
Solution Approach 1:
The system applies segmentation by using the CMTS to divide the network into separate segments corresponding to different taps and branches. By independently controlling taps and switches for each segment, the system can isolate and measure noise from individual segments despite the funneling effect, transforming the obscured noise problem into manageable segmentated measurements.
Solution Approach 2:
The CMTS acts as an intermediary that mediates between the multiple noise sources from different taps and branches and the measurement system. By introducing the CMTS's tap control and switch control mechanisms as intermediaries, the system can selectively block signals from specific segments and measure the resulting noise deviations, thereby identifying noise sources that would otherwise be obscured by funneling.
Data Source
AI summary
Mitigating noise in a network is contemplated, such as but not necessarily limited to mitigating noise through a detection process whereby noise deviations resulting from selectively controlling smart taps, switches or other devices to block signaling in the network may be used to locate sources of noise.