A Comparative Analysis of the Complexity/Accuracy Tradeoff in Power Amplifier Behavioral Models
Ali Soltani Tehrani,Haiying Cao,Sepideh Afsardoost,Thomas Eriksson,Magnus Isaksson,Christian Fager +5 more
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TLDR
The results show that the generalized memory polynomial behavioral model has the best tradeoff for accuracy versus complexity for both PAs, and can obtain high performance at half of the computational cost of all other models analyzed.Abstract:
A comparative study of state-of-the-art behavioral models for microwave power amplifiers (PAs) is presented in this paper. After establishing a proper definition for accuracy and complexity for PA behavioral models, a short description on various behavioral models is presented. The main focus of this paper is on the modeling accuracy as a function of computational complexity. Data is collected from measurements on two PAs-a general-purpose amplifier and a Doherty PA designed for WiMAX-for different output power levels. The models are characterized in terms of accuracy and complexity for both in-band and out-of-band error. The results show that, among the models studied, the generalized memory polynomial behavioral model has the best tradeoff for accuracy versus complexity for both PAs, and can obtain high performance at half of the computational cost of all other models analyzed.read more
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IEEE Transactions on Microwave Theory and Techniques and Antennas and Propagation Announce a Joint Special Issue on Ultra-Wideband (UWB) Technology
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Digital Predistortion Using a Vector-Switched Model
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Iterative Learning Control for RF Power Amplifier Linearization
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Behavioral Modeling and Predistortion of Power Amplifiers Under Sparsity Hypothesis
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