研究目的
To estimate the coefficients of a multiple-look-up table (LUT) digital predistortion (DPD) architecture for concurrent dual-band envelope tracking power amplifiers using partial least-squares (PLS) regression method, aiming to reduce complexity while maintaining linearity.
研究成果
The PLS regression method effectively addresses the ill-conditioning problem in DPD coefficient estimation, enabling a reduction in the number of coefficients without significant loss of accuracy. The 3D-DML DPD model, combined with OMP-LUT selection and PLS estimation, meets linearity requirements while simplifying implementation complexity.
研究不足
The study focuses on concurrent dual-band signals and may not cover all scenarios of multi-band or carrier aggregated signals. The FPGA implementation's efficiency is highlighted, but specific hardware constraints are not detailed.
1:Experimental Design and Method Selection:
The study employs a 3-D distributed memory LUT (3D-DML) DPD model for FPGA implementation, utilizing PLS regression for coefficient estimation. A modified orthogonal matching pursuit (OMP) algorithm, OMP-LUT, is used for selecting relevant LUTs.
2:Sample Selection and Data Sources:
The evaluation uses a concurrent dual-band signal composed of two OFDM signals with 10- and 5-MHz bandwidth, spaced 80 MHz apart, processed through a Texas Instruments LM3290-91-1EVM ET board with a Skyworks SKY776621 4G handset PA.
3:List of Experimental Equipment and Materials:
Equipment includes a Rohde & Schwarz SMW200A vector signal generator for RF upconversion and a Rohde & Schwarz FSW8 signal and spectrum analyzer for RF downconversion and data acquisition.
4:Experimental Procedures and Operational Workflow:
The remoteUPCLab test bed is used for DPD evaluation, where baseband I/Q waveforms and a supply waveform are processed through the PA, with output signals analyzed for linearity and efficiency.
5:Data Analysis Methods:
Performance is evaluated in terms of adjacent channel power ratio (ACPR), normalized mean square error (NMSE), and power efficiency, comparing PLS and PCA techniques for coefficient reduction.
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