Receiver Nonlinearity Cancellation via Segmented Estimation
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Solution Overview
Problem
Conventional methods for handling receiver nonlinearity are costly, cumbersome, and inefficient, often introducing errors or distortion, and fail to meet high linearity requirements in communication systems.
Innovation Solution
The implementation of adaptive nonlinearity detection and estimation, followed by narrowband estimation and wideband correction, which involves using a processing block with components like ADC/IQ calibration, anti-aliasing filtering compensation, nonlinearity cancellation circuits, and a controller to optimize linearity in receiver analog front-ends.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If conventional methods are used to handle receiver nonlinearity, then implementation is simpler, but linearity performance is insufficient and errors/distortion are introduced
Solution Approach 1:
The nonlinearity correction is divided into narrowband estimation (for accurate local characterization) and wideband correction (for broad frequency coverage). This segmentation allows the system to achieve high linearity performance across wide bandwidths by combining localized precision with global coverage, resolving the contradiction between performance and complexity.
Solution Approach 2:
The system performs preliminary nonlinearity estimation using training sequences before actual data reception. By pre-characterizing the nonlinearities of the receiver front-end, the system prepares correction parameters in advance, enabling efficient real-time correction without introducing computational complexity during critical data processing phases.
2Manufacturing precision
If narrowband estimation and wideband correction are implemented, then linearity is optimized, but processing time and computational load increase
Solution Approach 1:
The system uses periodic training sequences inserted at regular intervals to update nonlinearity estimates. This periodic approach allows the system to maintain optimized linearity performance through continuous adaptation while managing processing time by confining intensive computations to scheduled intervals rather than continuous operation.
Solution Approach 2:
Nonlinearity parameters are estimated in advance using training sequences before actual communication data is processed. This preliminary estimation separates the computationally intensive characterization phase from the data processing phase, reducing real-time processing time while maintaining optimization accuracy.
3Manufacturing precision
If adaptive nonlinearity detection is used, then signal quality improves, but power consumption increases
Solution Approach 1:
The system applies full adaptive nonlinearity correction only during training sequence periods when quality optimization is critical, and uses the estimated parameters for correction during data reception. This partial application of intensive processing achieves signal quality improvement while reducing overall power consumption compared to continuous full-power adaptation.
Data Source
AI summary
Systems and methods are provided for receiver nonlinearity estimation and cancellation. Narrowband (NB) estimation may be performed in a receiver during handling of received radio frequency (RF) signals. The narrowband (NB) may include generating estimation channelization information relating to received RF signals; generating reference nonlinearity information relating to one or more other signals, which may cause or contribute to nonlinearity that affects the processing of the received RF signals; and generating, based on the estimation channelization information relating to the received RF signals and the reference nonlinearity information relating to the other signals, control data for configuring nonlinearity cancellation functions. The received RF signals may be channelized, and the estimation channelization information may be generated based on the channelization of the received RF signals. The other signals may be channelized, and the reference nonlinearity information may be generated based on the channelization of the other signals.