Finding Structural Information about RF Power Amplifiers using an Orthogonal Nonparametric Kernel Smoothing Estimator
2016 (English)In: IEEE Transactions on Vehicular Technology, ISSN 0018-9545, E-ISSN 1939-9359, Vol. 65, no 5, 2883-2889 p., 7109926Article in journal (Refereed) Published
A non-parametric technique for modeling the behavior of power amplifiers is presented. The proposed technique relies on the principles of density estimation using the kernel method and is suited for use in power amplifier modeling. The proposed methodology transforms the input domain into an orthogonal memory domain. In this domain, non-parametric static functions are discovered using the kernel estimator. These orthogonal, non-parametric functions can be fitted with any desired mathematical structure, thus facilitating its implementation. Furthermore, due to the orthogonality, the non-parametric functions can be analyzed and discarded individually, which simplifies pruning basis functions and provides a tradeoff between complexity and performance. The results show that the methodology can be employed to model power amplifiers, therein yielding error performance similar to state-of-the-art parametric models. Furthermore, a parameter-efficient model structure with 6 coefficients was derived for a Doherty power amplifier, therein significantly reducing the deployment’s computational complexity. Finally, the methodology can also be well exploited in digital linearization techniques.
Place, publisher, year, edition, pages
2016. Vol. 65, no 5, 2883-2889 p., 7109926
Power amplifier, non-parametric model, kernel, basis functions, power amplifier linearization, Digital pre distortion.
Electrical Engineering, Electronic Engineering, Information Engineering
Research subject Electrical Engineering
IdentifiersURN: urn:nbn:se:hig:diva-19395DOI: 10.1109/TVT.2015.2434497ISI: 000376094500004ScopusID: 2-s2.0-84970016798OAI: oai:DiVA.org:hig-19395DiVA: diva2:814623