Affiliations: [a] Department of Electronics and Communication Engineering, Amrita School of Engineering, Bengaluru, Amrita Vishwa Vidyapeetham, India
| [b] RF and Baseband team, Redpine Signals, Raheza Mindspace, Hi-Tech City, Hyderabad, India
Correspondence:
[*]
Corresponding author. Sanjika Devi R V, Department of Electronics and Communication Engineering, Amrita School of Engineering, Bengaluru, Amrita Vishwa Vidyapeetham, India. E-mail: r_sanjika@blr.amrita.edu.
Abstract: This article presents a novel information criterion based optimal model parameter selection algorithm for behavioral modeling of Radio Frequency Power Amplifiers (RF PAs). The proposed approach uses Particle Swarm Optimization (PSO) along with the Information Criterion (IC) based cost functions for determining the most parsimonious model from all the available combinatorial models. The proposed technique thereby helps in deriving complexity reduced models without compromising modeling accuracy. The validation of the proposed approach was carried out by modeling a GaAs based PA driven by a 20-MHz generic random input signal. It was shown that, the model performance was maintained while its complexity in terms of number of coefficients was reduced by around 35% in the considered cases. In addition, the proposed PSO based approach helps in deriving the most parsimonious PA model in a very short amount of time compared to the conventional sweep technique.
Keywords: RF Power amplifiers, particle swarm optimization (PSO), information criterion (IC), maximum entropy (ME)
