Mesh Network Time Synchronization Failure Diagnosis And Frequency Calibration
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Solution Overview
Problem
Existing mesh networks face challenges in accurately maintaining pairwise time synchronization and frequency calibration due to errors in frequency offset, time bias, and distance values, which affect network-wide accuracy and applications such as localization and high-data rate TDMA protocols.
Innovation Solution
A method for identifying and diagnosing failures in pairwise time synchronization and frequency calibration by calculating diagnostic scores for transceivers based on edge values, triggering recalibration or resynchronization, and using a network graph to maintain accurate reference time and location.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If pairwise time synchronization and frequency calibration are performed in mesh networks, then network-wide timing accuracy and localization precision are improved, but errors in frequency offset, time bias, and distance values accumulate and degrade synchronization reliability
Solution Approach 1:
The patent implements a feedback mechanism where transceivers continuously exchange synchronization messages and calculate diagnostic scores based on observed frequency offsets, time biases, and distance values. The system monitors synchronization quality metrics and triggers corrective actions when deviations exceed thresholds, creating a closed-loop feedback system that maintains synchronization reliability despite accumulated errors
Solution Approach 2:
The mesh network performs self-diagnosis and self-correction through automated diagnostic scoring and recalibration procedures. Each transceiver independently calculates its own diagnostic score based on local measurements and triggers its own recalibration when needed, enabling the network to maintain accuracy without external intervention or centralized control
2Measurement precision
If diagnostic scores are calculated for all transceivers based on edge values in the network graph, then failure identification accuracy is improved, but computational complexity and processing time increase
Solution Approach 1:
The patent segments the network analysis into triangular graphs, where diagnostic scores are calculated independently for each triangle formed by three transceivers. This segmentation allows parallel processing of discrete triangular units rather than analyzing the entire network graph at once, reducing computational complexity while maintaining comprehensive failure identification through aggregation of triangular diagnostic results
Solution Approach 2:
The system calculates diagnostic scores for triangles rather than all possible node combinations, representing a partial action approach. By focusing on triangular configurations (the minimal complete subgraph), the system achieves sufficient failure identification accuracy with reduced computational effort compared to exhaustive analysis of all network relationships
3Measurement precision
If automatic recalibration and resynchronization are triggered when diagnostic scores exceed thresholds, then network accuracy is maintained, but network operations are interrupted and productivity decreases
Solution Approach 1:
The patent implements periodic monitoring of diagnostic scores and threshold-based triggering of recalibration actions. Rather than continuous recalibration, the system periodically evaluates synchronization quality and only interrupts operations when diagnostic scores exceed predefined thresholds, balancing accuracy maintenance with minimal disruption to data transmission productivity
Solution Approach 2:
The system dynamically adjusts operational parameters based on diagnostic score thresholds. When scores indicate degradation, the system changes state from normal operation to recalibration mode, modifying transmission timing and frequency parameters. This parameter-based control allows accurate maintenance while minimizing interruptions by only changing parameters when necessary
Data Source
AI summary
A method including accessing a network graph including: a set of transceiver nodes representing a set of transceivers operating in a mesh network of transceivers; a set of transmitter nodes representing a set of transmitters communicating with the mesh network of transceivers; and a set of edges, each connecting a pair of nodes in the set of nodes. The method also includes: identifying a subgraph of the network graph associated with a node in the set of nodes, the node representing a transceiver; accessing a network state of the subgraph comprising a set of edge values for each edge in the subgraph; calculating a probability of failure of the transceiver based on the network state of the subgraph; and in response to detecting the probability of failure of the transceiver exceeding a threshold likelihood, triggering a corrective action at the transceiver.