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- Title
自适应稀疏重构的双频预失真结构.
- Authors
高明明; 吴月; 房少军; 南敬昌
- Abstract
To solve the problem of high sampling rate in the dual frequency amplifier predistortion system, this paper proposed an adaptive sparse predistortion structure based on compressed sensing. Firstly, it used the memory effect compensator based on piecewise polynomial model, and then understood the signal fusion as the compressive sensing sampling reconstruction problem. That was, the pre-distortion feedback loop used the adaptive sparse algorithm to reconstruct the missing intermodulation signals of the fifth order and the higher order with high accuracy, so that the minimum mean square solution of coefficient weight value approximated to the optimal value. This method could reduce the acquisition error and improve linearization. The experimental results show that normalized mean squared error display is about 2 ~ 3 dB better than 2 dimensional-memory polynomial ( 2D-MP) and 2 dimensional-canonical piecewise linear(2D-CPWL) in improving the system stability. The adjacent channel power radio( ACPR) can be improved to 20 dBc. It is of great significance to reduce the predistortion sampling rate of dual frequency band and improve the linearity of power amplifier.
- Subjects
COMPRESSED sensing; ALGORITHMS; POWER amplifiers; INTERMODULATION; PROBLEM solving; BACOPA monnieri
- Publication
Application Research of Computers / Jisuanji Yingyong Yanjiu, 2020, Vol 37, Issue 8, p2428
- ISSN
1001-3695
- Publication type
Article
- DOI
10.19734/j.issn.1001-3695.2019.03.0103