Interfering Signal Parameter Estimation by Residual Error Minimization
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Solution Overview
Problem
Existing communication devices face interference issues due to mismatched manual settings of alpha values for interfering signals, leading to residual interference components that degrade performance and increase error rates.
Innovation Solution
A method involving iterative parameter refinement for interfering signals, including adjusting amplitude, carrier frequency, symbol rate, and pulse shape to minimize residual errors through dynamic generation and subtraction of interfering signal components.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If manual settings of alpha values are used for interfering signals, then device complexity is reduced, but measurement precision of interfering signal parameters deteriorates
Solution Approach 1:
The system performs self-calibration by automatically determining alpha values through iterative optimization of residual errors, eliminating the need for manual configuration while achieving precise measurement of interfering signal parameters
Solution Approach 2:
The system dynamically adjusts alpha values as可变 parameters through iterative optimization, changing the parameter from fixed manual setting to adaptive determined value to resolve the contradiction between simplicity and precision
2Measurement precision
If iterative parameter refinement is performed to minimize residual errors, then measurement precision of interfering signal parameters is improved, but computing time increases
Solution Approach 1:
The system performs iterative refinement only to the extent necessary to achieve acceptable residual error thresholds, avoiding excessive computation while maintaining sufficient measurement precision for practical applications
Solution Approach 2:
The system uses feedback from residual error measurements to guide iterative parameter refinement, stopping when convergence criteria are met, thus balancing precision improvement with computing time constraints
3Reliability
If dynamic generation and subtraction of interfering signal components is performed, then reliability of signal detection is improved, but device complexity increases
Solution Approach 1:
The system creates simplified copies or models of interfering signal components with determined alpha values, allowing accurate subtraction and isolation of desired signals while maintaining manageable computational complexity through parameterized signal models
Data Source
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AI summary
Systems and methods comprising: receiving a signal (S) having a first interfering signal component (FISC); generating a replicated SOI (RSOI); and iteratively performing a process to obtain residual errors for FISC. The process involves: modifying an amplitude of RSOI; obtaining a reference signal (RS) by removing RSOI with the modified amplitude from S; analyzing frequency of RS to obtain an estimated carrier frequency and an estimated symbol rate for FISC; generating a remaining signal by removing, from FRS, a signal having the estimated carrier frequency and symbol rate; and determining a residual error of the remaining signal. Parameters for FISC are then set equal to the estimated carrier frequency and symbol rate that are associated with a lowest residual error. The parameters may be further refined in accordance with another process which involves iteratively modifying a symbol rate of FISC. Yet another process may be performed to determine filter parameters.