State Discovery via Adaptive Probing and Candidate Elimination
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Solution Overview
Problem
Current methods for identifying the current state of an electronic system, such as in communications systems, face challenges in accurately determining the operating channel due to the possibility of false-negative results and incorrect interpretation or processing of probing results, which can lead to inefficiencies and inaccuracies.
Innovation Solution
A method is developed to identify the current state of an electronic system by selecting a probing parameter based on probabilities of false-negative results and incorrect processing, probing the system, and iteratively removing candidate states that do not intersect or are intersected by the probing parameter, ultimately identifying the last remaining state as the current state.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional probing methods are used to identify system state, then the system can determine the operating channel, but false-negative results and incorrect interpretation of probing results occur, reducing accuracy
Solution Approach 1:
The system performs preliminary actions by sending multiple probes with different parameters before final state determination. The method sends a first probe with a first parameter and a second probe with a second parameter, evaluating multiple possible states before concluding the current state, thereby reducing false-negative results and improving measurement precision through pre-planned probing sequences.
2Reliability
If multiple probes are sent to improve accuracy, then the reliability of state identification increases, but the number of probes required increases, reducing efficiency
Solution Approach 1:
The system dynamically adjusts the probing process by evaluating possible states after each probe and adaptively selecting subsequent probe parameters. The method determines a set of possible states, sends probes based on current knowledge, and updates the state set dynamically, allowing the probing sequence to be optimized in real-time rather than following a fixed predetermined sequence, thus improving efficiency while maintaining reliability.
3Measurement precision
If the system sends probes with different parameters to cover all possible states, then measurement precision improves, but device complexity and resource usage increase
Solution Approach 1:
The system segments the state identification process into discrete steps: determining an initial set of possible states, sending probes with specific parameters, evaluating results, and narrowing down the state set. By dividing the complex task of identifying the current state into manageable segments with clear decision points, the method reduces overall system complexity while maintaining high measurement precision through systematic state elimination.
Data Source
AI summary
A method for identifying a current state of an electronic system is provided. The method includes identifying a pool of candidate states of the electronic system, selecting a probing parameter in accordance with a model, and probing the electronic system based on the selected probing parameter. When the probing yields a positive result, all candidate states that are not intersected by the probing parameter are removed from the pool. When the probing parameter yields M negative results, all candidate states that are intersected by the probing parameter are removed from the pool, where M≥1. A last remaining candidate state in the pool is identified as the current state of the electronic system. The model is based on at least one of a probability that the probing would yield a false-negative result or a probability that a result of the probing would be interpreted and/or processed incorrectly.