OTA Digital Pre-Distortion Kernel Selection for Wireless Signal Quality
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Solution Overview
Problem
Wireless communication systems face challenges in managing and optimizing finite wireless channel resources due to signal attenuation and blocking in complex environments, which undermines established channel measuring and reporting mechanisms.
Innovation Solution
A method for over-the-air (OTA) digital pre-distortion (DPD) kernel function selection, where user equipment (UE) transmits capability information to a base station (BS), receives a request for DPD training, and selects an ordered set of kernel functions based on received reference signals to reduce power amplifier non-linearity, thereby improving signal quality and efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If established channel measuring and reporting mechanisms are used, then wireless channel resources can be managed, but signal attenuation and blocking in complex environments undermine the reliability of these mechanisms
Solution Approach 1:
The patent introduces reference signals as intermediary elements that are specifically designed for DPD training purposes. These reference signals serve as mediators between the transmitter and receiver, enabling reliable channel characterization even in complex environments with signal attenuation and blocking. The reference signals provide a known reference that can be used to estimate channel conditions and perform DPD training independently of the regular data transmission channels.
2Reliability
If digital pre-distortion training is performed to compensate for power amplifier non-linearity, then signaling quality improves, but processing complexity and computational requirements increase
Solution Approach 1:
The patent segments the DPD training process into distinct phases: capability exchange between UE and BS, reference signal transmission, kernel function selection based on received reference signals, and feedback transmission. This segmentation allows each component to be optimized independently and enables the system to perform DPD training only when needed and only for specific kernel functions, reducing overall processing complexity while maintaining signaling quality.
Solution Approach 2:
The patent implements partial DPD training by selecting only an ordered set of kernel functions based on the received reference signals, rather than performing exhaustive DPD training for all possible kernel functions. The UE transmits capability information indicating which DPD functions it supports, and the BS requests only the necessary DPD training, performing partial action that is sufficient to improve signaling quality without the full computational burden of complete DPD training.
3Reliability
If comprehensive DPD training is performed to reduce power amplifier non-linearity effects, then signal distortion is reduced, but power consumption during training increases
Solution Approach 1:
The patent implements periodic DPD training through a structured capability exchange and feedback mechanism. The UE periodically transmits capability information about its DPD support, and the BS periodically requests DPD training when needed. This periodic action allows the system to perform DPD training at optimized intervals rather than continuously, reducing power consumption while maintaining signal quality through timely distortion compensation.
Data Source
AI summary
Certain aspects of the present disclosure provide techniques for over-the-air digital pre-distortion (DPD) kernel function selection. A method that may be performed by a user equipment (UE) includes transmitting capability information to a base station (BS), indicating a capability of the UE for performing digital pre-distortion (DPD) training, receiving, based on the capability information, a request from the BS to perform the DPD training, performing, based on the received request, the DPD training, wherein performing the DPD training includes: receiving one or more reference signals (RSs) and selecting, based on the one or more RSs, an ordered set of kernel functions. Additionally, the method may include transmitting feedback information to the BS indicating the ordered set of kernel functions.