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Content Provider | IEEE Xplore Digital Library |
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Author | Bertran, E. Montoro, G. Talavera, N. |
Copyright Year | 1994 |
Description | Author affiliation: Dept. of Signal Theory & Commun., Univ. Politecnica de Catalunya, Barcelona, Spain (Bertran, E.; Montoro, G.; Talavera, N.) |
Abstract | A new approach to the RF power amplifier linearization problem is presented. The proposed solution applies non-linear theories (Lyapunov direct method) to adaptive filtering in order to improve the linearity of the RF amplifiers. The obtained design requires lower circuit complexity than the LINC amplifier, and is not based on iterative algorithms nor sub-system identification. Up to 100 MHz these functions could be implemented, at present, with operational amplifiers and integrated analog multipliers (four quadrants). The adjusting algorithm convergence or the interruption of the communication are not problems in the proposed adaptive solution. The canceller structure design is based on model reference adaptive systems (MRAS): to cancel the error between the plant output (distortion output of the RF amplifier) and reference model (the desired signal obtained from a linear and low-power amplifier) by using continuous-time techniques. The proposed structure is studied by computer simulation (SPICE program) in a class-A RF power amplifier, The behaviour of the adapted amplifier is studied when power transistors approach nonlinear operating zones (saturation state).< |
Starting Page | 160 |
Ending Page | 163 |
File Size | 289530 |
Page Count | 4 |
File Format | |
ISBN | 0780317726 |
DOI | 10.1109/MELCON.1994.381119 |
Language | English |
Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Publisher Date | 1994-04-12 |
Access Restriction | Subscribed |
Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Subject Keyword | Adaptive control Radiofrequency amplifiers Power amplifiers Radio frequency Iterative algorithms Power system modeling Adaptive filters Linearity Algorithm design and analysis Complexity theory |
Content Type | Text |
Resource Type | Article |
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