Adaptive Receiver Cancellation for Strong and Weak Signal Isolation
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Solution Overview
Problem
Conventional methods for cancelling strong signals in communications systems, such as STAR and cellular phone networks, face challenges in achieving accurate and stable isolation due to correlation between strong and weak signals, leading to degraded performance and inefficiencies, especially in dynamic environments where nodes move and propagation paths change rapidly.
Innovation Solution
A receiver system that includes a parametric cancellation circuit and an adaptation logic circuit to produce a cancellation signal by modeling the strong signal and adapting parameters based on error signals, allowing for effective cancellation of strong signals from combined weak and strong signals, using techniques like FIR filters and nonlinear transformations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional cancellation methods (circulators, summing junctions) are used to isolate strong signals, then some signal separation is achieved, but isolation accuracy is insufficient (only 20 dB when 100 dB or more is needed)
Solution Approach 1:
The patent implements dynamic adaptation by continuously adjusting cancellation parameters based on real-time signal conditions. The system uses adaptive filtering algorithms that modify filter coefficients dynamically to track changing signal characteristics, enabling the cancellation system to maintain high accuracy (100 dB or more) even when signals vary over time, thus resolving the contradiction between measurement precision and reliability
Solution Approach 2:
The patent employs feedback mechanisms where the output of the cancellation system is monitored and fed back to adjust the cancellation parameters. This closed-loop control allows the system to detect and correct deviations from optimal cancellation performance, ensuring both high isolation accuracy and stable reliable operation under varying conditions
2Device complexity
If slow adaptation methods are used for signal cancellation, then system complexity is reduced, but the system only works for static conditions where nodes are not in motion
Solution Approach 1:
The patent implements dynamic adaptation by continuously adjusting cancellation parameters based on real-time signal conditions. The system uses adaptive filtering algorithms that modify filter coefficients dynamically to track changing signal characteristics, enabling the cancellation system to maintain high accuracy (100 dB or more) even when signals vary over time, thus resolving the contradiction between measurement precision and reliability
Solution Approach 2:
The patent changes the operational parameters of the cancellation system dynamically based on signal conditions. By adjusting filter coefficients, gain factors, and other parameters in real-time, the system adapts to moving nodes and changing propagation paths without requiring complex reconfiguration, achieving both simplicity and dynamic capability
3Adaptability or versatility
If fast adaptation is used to handle moving nodes and changing propagation paths, then dynamic environment performance is improved, but the strong signal and weak signal correlation degrades cancellation behavior
Solution Approach 1:
The patent applies preliminary action by performing cancellation operations before the correlation between strong and weak signals can significantly degrade performance. The system proactively adjusts parameters based on predicted signal conditions and uses look-ahead techniques to anticipate correlation issues, maintaining cancellation accuracy even in dynamic environments where signal correlation varies over time
4Measurement precision
If adaptation is performed only when no received signal is present, then cancellation accuracy is improved, but the entire network must be shut down for adaptation
Solution Approach 1:
The patent ensures continuity of useful action by performing adaptation continuously during normal network operation rather than shutting down the network. The adaptive algorithm processes signals in real-time and adjusts parameters on-the-fly, allowing the network to maintain full operational productivity while achieving accurate cancellation through continuous adaptation to changing signal conditions
Data Source
AI summary
A receiver for cancelling strong signals from combined weak and strong signals includes: a first circuitry for inputting a weak and strong signal as an input; a parametric cancellation circuit for inputting a representation of the strong signal and an output of the first circuitry to produce a cancellation signal; a second circuitry electrically coupled to the parametric cancellation circuit for inputting the cancellation signal to produce a modulated output; a demodulator electronically coupled to the second circuitry for demodulating the modulated output to produce a demodulated output and an error signal, where the demodulated output is the data contained in the weak signal; and an adaptation logic circuit for inputting the representation of the strong signal, the demodulated output and the error signal to adaptively produce parameters for the parametric cancellation circuit. The parametric cancellation circuit further inputs the error signal and the parameters to produce the cancellation signal.