Abstract
In this paper, Improved Digital Predistortion (DPD) Algorithm using an active filter and approximation Hessian technique is suggested. The algorithm optimized the performance of the DPD based on Quasi-Newton family method. In modeling power amplifier, the memory polynomial model which can model the memory effect of the power amplifier is used. And we compared with Least Mean-Squares (LMS) and Recursive Least squares (RLS) algorithm.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Jian W, Yu C, Wang J, Yu J, Wang L (2006) OFDM adaptive digital predistortion method combines RLS and LMS algorithm. In: IEEE conference on industrial electronics and applications, pp 3900–3903
Yu X (2008) Stability enhancement of digital predistortion through iterative methods to solve system of equations. In: Microwave conference APMC 2008, pp 1–4
Eun C, Powers EJ (1997) A new Volterra predistorter based on the indirect learning architecture. IEEE Trans Signal Process 45(1):223–227
Rao SS (2008) Engineering optimization theory and practice, 4th edn. Wiley, New York
Jang JS, Choi YG, Suh KW, Hong US (2011) A design of new digital adaptive predistortion linearizer algorithm based on DFP method. J. Korean Inst Electromagn Eng Soc 25(3):312–319
Haykin S (2008) Adaptive filter theory, 4th edn. Prectice Hall Inc., New Jersey
Luenberger DG, Ye Y ( 2008) Linear and nonlinear programming. Springer, New York
Sun W, Yuan Y-X (2007) Optimization theory and methods (Nonlinear Programming). Springer, New York
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer Science+Business Media Dordrecht
About this paper
Cite this paper
Jang, JS., Lee, GH. (2013). Implementation of Improved DPD Algorithm Using the Approximation Hessian Technique and an Adaptive Filter. In: Kim, K., Chung, KY. (eds) IT Convergence and Security 2012. Lecture Notes in Electrical Engineering, vol 215. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-5860-5_40
Download citation
DOI: https://doi.org/10.1007/978-94-007-5860-5_40
Published:
Publisher Name: Springer, Dordrecht
Print ISBN: 978-94-007-5859-9
Online ISBN: 978-94-007-5860-5
eBook Packages: EngineeringEngineering (R0)