DPD Regularization for Gain Flatness in Wideband RF Transitions
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Solution Overview
Problem
In dynamic signal traffic scenarios, RF systems experience a tilt in output spectrum during transitions from narrowband to wideband due to inadequate DPD adaptation, leading to issues like throughput inaccuracies and beamforming errors, especially in MIMO radio scenarios where additional calibration tones are often not permitted.
Innovation Solution
Incorporating a regularization term into the DPD coefficient estimation process using pre-stored wideband waveform data to maintain gain flatness, without requiring additional calibration tones, by applying a weighing factor to the least squares solution.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If DPD adaptation is performed using conventional methods during narrowband to wideband transitions, then the DPD algorithm can adapt to signal changes, but gain tilt occurs in the output spectrum leading to throughput inaccuracies and beamforming errors
Solution Approach 1:
The patent applies preliminary action by incorporating a regularization term into the DPD cost function that is derived from pre-stored wideband waveform data. This regularization term is computed in advance during system calibration and stored, then applied during operation to prevent gain tilt before it occurs during narrowband to wideband transitions, rather than correcting it after the fact
Solution Approach 2:
The patent changes the parameter space of the DPD algorithm by adding a regularization term to the conventional cost function. This regularization term modifies the coefficient estimation process by incorporating constraints derived from wideband waveform characteristics, thereby changing how the DPD coefficients are optimized to maintain gain flatness during dynamic transitions
2Manufacturing precision
If additional calibration tones are transmitted to correct gain flatness during narrowband to wideband transitions, then gain flatness can be improved, but system complexity increases and additional calibration signals are required
Solution Approach 1:
The patent uses copying by utilizing pre-stored wideband waveform data that was captured during a calibration phase. Instead of transmitting additional calibration tones during operation, the system copies the characteristics of wideband signals from pre-stored data and uses this copied information to construct the regularization term, thereby avoiding the need for additional real-time calibration signals
Solution Approach 2:
The patent applies self-service by making the DPD system self-correcting through the regularization term. The system uses its own pre-stored wideband waveform data to automatically correct gain tilt during transitions without requiring external calibration signals or additional complexity in the transmission path, enabling the system to self-regulate its performance
Data Source
AI summary
In a dynamic signal traffic scenario, a narrowband to wideband transition in a DPD system results in a tilt in the output spectrum until the next DPD adaptation cycle occurs. To address this problem, regularization term is applied with a weighing factor when performing DPD coefficient estimation and adaptation. The regularization term can be obtained from in a variety of ways: using pre-stored waveforms, through factory or in-situ calibration, or through an adaptive or opportunistic update by observing the system. Application of the regularization term improves the spectrum flatness for a narrow to wideband signal transition, and does not require transmitting additional calibration tones to correct the gain flatness.