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GaN Power Amplifier Digital Predistortion by Multi-Objective Optimization for Maximum RF Output Power
| Content Provider | MDPI |
|---|---|
| Author | Mengozzi, Mattia Gibiino, Gian Piero Angelotti, Alberto M. Florian, Corrado Santarelli, Alberto |
| Copyright Year | 2021 |
| Description | While digital predistortion (DPD) usually targets only the linearity performance of the radio–frequency (RF) power amplifier (PA), this work addresses more than a single PA performance metric exploiting a multi-objective optimization approach. We present a predistorer learning procedure based on a constrained optimization algorithm that maximizes the RF output power, while guaranteeing a prescribed linearity level, i.e., a maximum normalized mean square error (NMSE) or adjacent-channel power ratio (ACPR). Experimental results on a Gallium Nitride (GaN) PA show that the proposed approach outperforms the classical indirect learning architecture (ILA), yet using the same predistorter structure with predetermined nonlinearity and memory orders. |
| Starting Page | 244 |
| e-ISSN | 20799292 |
| DOI | 10.3390/electronics10030244 |
| Journal | Electronics |
| Issue Number | 3 |
| Volume Number | 10 |
| Language | English |
| Publisher | MDPI |
| Publisher Date | 2021-01-21 |
| Access Restriction | Open |
| Subject Keyword | Electronics Telecommunications Digital Predistortion Multi-objective Optimization Power Amplifier Linearization Techniques |
| Content Type | Text |
| Resource Type | Article |
