Signal Separator for Removing Inband Interference
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Solution Overview
Problem
Existing communication systems face challenges in removing unwanted inband signals, such as noise and interference, from received communication signals without prior knowledge of their characteristics, which degrades the quality and capacity of the communication channel.
Innovation Solution
A system and method that processes the received communication signal to estimate and remove unwanted inband signals without prior knowledge of their characteristics, using a signal separator and performance improver to enhance the desired communication signal, allowing for improved carrier-to-noise ratio and increased channel capacity by separating multiple communication signals within the same bandwidth.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Object-affected harmful factors
If traditional filtering methods are used to remove unwanted signals, then out-of-band signals can be filtered, but inband signals cannot be effectively removed as they occupy the same frequency range
Solution Approach 1:
The received signal is segmented into multiple components using independent component analysis (ICA), which decomposes the mixed signal into statistically independent source signals. This segmentation allows separation of desired communication signals from unwanted inband interferers without requiring prior knowledge of their characteristics.
Solution Approach 2:
An intermediary processing stage involving covariance matrix computation and eigenvalue decomposition is introduced between signal reception and output. This intermediary process transforms the mixed signal into a form where independent components can be identified and separated, enabling removal of inband interference.
2Productivity
If multiple communication signals are transmitted in the same bandwidth to increase capacity, then channel capacity increases, but signal interference and quality degradation worsen
Solution Approach 1:
The mixed communication signals are segmented into individual independent components through ICA, allowing each signal to be recovered separately. This enables multiple signals to be transmitted simultaneously in the same bandwidth while maintaining signal quality through post-reception separation.
Solution Approach 2:
The system changes the parameter space from frequency domain to statistical independence domain. By transforming the separation criterion from frequency-based filtering to statistical independence-based decomposition, the system can separate signals that occupy the same bandwidth, thereby increasing channel capacity while maintaining reliability.
3Reliability
If unwanted inband signals are removed without prior knowledge of their characteristics, then signal quality improves, but the complexity of signal processing increases
Solution Approach 1:
The system uses the statistical properties of the signals themselves to perform separation, without requiring external information or prior knowledge about the interferers. The ICA algorithm automatically identifies and separates independent components based on their inherent statistical characteristics, making the system self-sufficient.
Solution Approach 2:
The processing pipeline includes iterative refinement where the separated components are evaluated and the decomposition is refined. The feedback mechanism allows the system to improve separation accuracy by repeatedly adjusting the decomposition based on the statistical independence criterion, thereby enhancing carrier-to-noise ratio.
4Productivity
If conventional signal processing is used, then simple filtering is possible, but channel capacity and signal separation capability are limited
Solution Approach 1:
The system transitions from frequency-domain filtering parameters to statistical parameter-based separation. By using covariance matrices, eigenvalues, and statistical independence measures instead of traditional frequency filters, the system achieves superior signal separation accuracy while enabling higher channel capacity through multiple simultaneous transmissions.
Data Source
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AI summary
A system for and method of removing one or more unwanted inband signals from a received communications signal is described. The inband signal or signals may comprise noise, interference signals, or any other unwanted signals that impact the quality of the underlying communications. A receiver receives a communication signal, the received communication signal including the desired communication signal and one or more inband signals. A signal separator processes the received signal to form an estimate of the desired communication signal and an estimate of the inband signals. A performance improver processes the received signal and the estimate of the one or more inband signals to form an improved estimate of the desired communication signal and an improved estimate of the inband signals.