Interference Cancellation Circuit With Adaptive CIR Estimation
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Solution Overview
Problem
Existing wireless communication systems face interference issues due to intermodulation distortion (IMD) and self-interference, particularly in high-bandwidth scenarios, which degrade reception sensitivity and require effective interference cancellation methods that account for memory terms in transmission paths.
Innovation Solution
A channel impulse response (CIR) estimation circuit and interference cancellation circuit are employed, utilizing a finite impulse response (FIR) filter, kernel generation circuit, adaptive filter, and CIR estimation circuit to estimate and cancel interference signals through backpropagation methods, adjusting CIR coefficients for each transmission path.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If interference cancellation is performed without incorporating memory terms for each transmission path, then the interference model is simpler, but interference cancellation effectiveness deteriorates
Solution Approach 1:
The patent segments the interference model by incorporating separate memory terms for each transmission path. The FIR filter processes transmission signals through multiple delay taps, each with its own CIR coefficient, allowing independent modeling of memory effects for different paths. This segmentation enables effective interference cancellation while maintaining manageable complexity through structured organization.
Solution Approach 2:
The patent implements dynamic adaptation by estimating CIR coefficients in real-time using the backpropagation method. The CIR estimation circuit continuously updates coefficients based on interference-cancelled signals, allowing the system to adapt to changing channel conditions. This dynamic approach improves cancellation effectiveness without requiring a fixed, overly complex static model.
2Productivity
If bandwidth for data transmission is increased, then communication capacity increases, but memory terms are introduced that complicate the interference cancellation process
Solution Approach 1:
The patent segments the high-bandwidth signal processing into discrete delay taps within the FIR filter structure. Each tap handles a specific time-shifted version of the signal, allowing the system to manage high bandwidth by processing multiple delayed versions independently through structured memory terms for each transmission path.
Solution Approach 2:
The patent employs feedback through the backpropagation method, where the CIR estimation circuit uses interference-cancelled signals to continuously update CIR coefficients. This feedback mechanism enables the system to handle the complexity introduced by high bandwidth by adaptively adjusting parameters based on actual signal conditions, thereby maintaining communication capacity while managing processing complexity.
3Reliability
If transmission signals are processed with high complexity to handle multiple paths, then reception sensitivity is maintained, but self-interference from transmission signals leaking into reception paths increases
Solution Approach 1:
The patent converts the harmful self-interference from transmission signals into a beneficial cancellation target. By modeling transmission signals through the FIR filter with multiple delay taps and memory terms, the system creates an interference model that can accurately represent self-interference patterns. The adaptive filter then uses this model to generate cancellation signals that subtract self-interference from reception paths, transforming the harmful effect into a manageable and cancellable parameter.
Solution Approach 2:
The patent implements feedback through continuous CIR coefficient estimation using the backpropagation method. The CIR estimation circuit receives interference-cancelled signals and continuously updates the CIR coefficients, creating a closed-loop system that adapts to changing interference conditions. This feedback mechanism enables the system to maintain reception sensitivity by dynamically adjusting the interference cancellation strategy in response to actual self-interference levels.
Data Source
AI summary
An interference cancellation circuit includes finite impulse response (FIR) filter configured to set a channel impulse response (CIR) coefficient for each transmission path for a transmission signal and obtain a CIR-adapted transmission signal by applying the CIR coefficient to the transmission signal, a kernel generation circuit configured to generate an interference model based on the CIR-adapted transmission signal, an adaptive filter configured to estimate an interference signal for each reception path by estimating an interference model coefficient for the interference model and generate an interference-cancelled signal by filtering out the interference signal from a reception signal, and a CIR estimation circuit configured to estimate the CIR coefficient in a next sample period based on the interference-cancelled signal through a backpropagation method and transmit the estimated CIR coefficient to the FIR filter.