Adaptive Correlation State Machine for Signal Processing
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Solution Overview
Problem
Conventional correlation techniques in communications systems are hardware intensive, computationally inefficient, and lack the ability for post-processing verification of correlation index values, making them unsuitable for dynamic adjustments and verification of suspected correlation peaks.
Innovation Solution
A state-based correlation method that employs a multi-resolution approach, transitioning between low-resolution, medium-resolution, and fine-resolution correlations, allowing for verification of correlation index values and reducing hardware and computational requirements through parallel processing and a state machine that adjusts correlation thresholds and sample sets.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a pipelined correlator is used to perform real-time correlation, then the correlation can be performed continuously, but post-processing verification of correlation index values is prevented and the system becomes hardware intensive
Solution Approach 1:
The patent implements a dynamic correlation length that can be adjusted based on processing needs. The system transitions between different correlation lengths (e.g., from a shorter length for initial processing to a longer length for verification), allowing the hardware to be reused flexibly rather than requiring dedicated hardware for each correlation length, thus reducing overall hardware complexity while maintaining real-time processing capability
Solution Approach 2:
The system employs periodic switching between different correlation processing modes. After an initial correlation pass, the system periodically performs verification passes with adjusted correlation lengths, enabling post-processing verification without requiring continuous dedicated hardware resources for all possible verification scenarios
2Measurement precision
If the correlation length is increased to ensure certain acquisition of the signal, then the accuracy is improved, but the number of arithmetic operations increases linearly with both the uncertainty window and the correlation length
Solution Approach 1:
The patent segments the correlation process into multiple passes with different correlation lengths. Instead of performing one long correlation that processes the entire uncertainty window at once, the system performs multiple shorter correlations with progressively adjusted lengths, reducing the computational burden of each individual operation while achieving the same level of acquisition certainty through cumulative processing
Solution Approach 2:
The system performs preliminary correlation operations with shorter correlation lengths to identify potential signal locations before committing to longer, more computationally intensive verification correlations. This preliminary action filters out false candidates early, preventing unnecessary computational operations in later stages
3Reliability
If N dedicated or re-used multipliers are required in the pipelined structure, then the correlation can be performed, but the system can only generate one correlation value per clock cycle and becomes hardware intensive
Solution Approach 1:
The patent makes the correlation hardware universal by designing the correlator to perform multiple functions: it can operate with different correlation lengths, perform both initial acquisition and verification operations, and process different signal conditions. This multi-functionality eliminates the need for separate dedicated hardware for each operation type, reducing the total number of multipliers required while maintaining reliable correlation value generation
Solution Approach 2:
The system changes operational parameters (particularly correlation length and sample window size) to optimize hardware utilization. By dynamically adjusting these parameters based on the processing stage and signal conditions, the same hardware resources can handle varying computational requirements without needing additional dedicated multipliers for each scenario
Data Source
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AI summary
A method is provided for correlating samples of a received signal and samples of an internally generated/stored sample sequence ("IGSSS"). The method involves performing a first iteration of a first-resolution correlation state. The first-resolution correlation state involves: selecting a first N sets of samples from the received signal; selecting a first set of samples from the IGSSS; and concurrently comparing each of the N sets of samples with the first set of samples to determine if a correlation exists between the same. If it is determined that a correlation does not exist between one of the N sets of samples and the first set of samples, then a second iteration of the first-resolution correlation state is performed. If it is determined that a correlation exists between one of the N sets of samples and the first set of samples, then a first iteration of a second-resolution correlation state is performed.