Dynamic CFR Filter Estimation for Mixed-Mode Wireless Signals
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Solution Overview
Problem
Higher order modulation wireless signals in systems like CDMA and OFDM have high Peak to Average signal power Ratio (PAR), causing power amplifiers to saturate, and existing digital PAR reduction techniques are inefficient due to the need for frequent re-design of FIR filters to match dynamic signal characteristics, especially in applications like repeaters where prior knowledge of signal characteristics is lacking.
Innovation Solution
A mechanism for automatically re-estimating Crest Factor Reduction (CFR) cancellation filters in hardware based on signal characteristics, using periodic snapshots of the signal, Fast Fourier Transform (FFT), and Inverse FFT (IFFT) to generate dynamic CFR filters that adapt to changing signal power distributions and frequency allocations, allowing for efficient power amplifier operation even in applications without prior information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional FIR filters are used to spectrally shape cancellation noise, then spectral mask compliance is maintained, but the filters must be frequently re-designed and updated for dynamic signals, increasing hardware complexity and computational burden
Solution Approach 1:
The patent implements dynamic adaptation of CFR filter coefficients to match changing signal characteristics in real-time. The system continuously updates filter parameters based on instantaneous signal spectrum analysis, enabling the filter to adapt to frequency hopping and power variations without manual re-design, thus maintaining spectral mask compliance while reducing hardware complexity for static filter storage
Solution Approach 2:
The system changes filter parameters (coefficients) dynamically based on signal conditions. By computing and updating CFR filter coefficients according to the current signal spectrum, the system maintains optimal performance for dynamic signals without requiring pre-computed filter sets for all possible signal configurations
2Productivity
If pre-computed CFR filters are stored for all frequency and power level combinations, then optimal PAR reduction is achieved, but hardware storage requirements and cost increase significantly
Solution Approach 1:
The system computes CFR filter coefficients on-demand based on actual signal characteristics rather than relying on pre-stored filters. The adaptive algorithm automatically determines appropriate filter parameters from the current signal spectrum, eliminating the need for extensive pre-computation and storage of filter sets for all possible signal conditions
Solution Approach 2:
Instead of static pre-computed filters, the system dynamically generates filter coefficients that match the current signal properties. This dynamic approach allows optimal PAR reduction for any signal configuration without requiring hardware storage for all possible filter combinations
3Measurement precision
If CFR filters are updated with software interaction, then filter accuracy is maintained, but the update rate cannot keep up with rapid signal characteristic changes
Solution Approach 1:
The system implements a feedback mechanism where the CFR filter coefficients are continuously updated based on real-time signal spectrum analysis. The instantaneous spectrum measurement feeds back to the filter coefficient computation, creating a closed-loop system that maintains filter accuracy while adapting to rapid signal changes without requiring external software intervention
Data Source
AI summary
A method to form a CFR cancellation filter for signals with dynamic power and frequency distribution by estimating the filter at the rate required by the input signal's dynamics. For mixed mode systems (for example CDMA and LTE) the CFR is computed for each stream, and combined to form the final filter.