Performance Analysis of Digital Predistortion on Orthogonal Frequency Division Multiplexing Systems

  • Divya DickshawEmail author
  • P. Shanthi
Conference paper
Part of the Lecture Notes on Data Engineering and Communications Technologies book series (LNDECT, volume 39)


Wireless communication technologies are constantly evolving since the commencement of the cellular networks. Due to increase in high data rate which is observed from 1G to 4G, spectacular innovations from text to video conferencing. Orthogonal Frequency Division Multiplexing(OFDM) is one of the most promising technique that is capable to provide outrageous data rate. Drawbacks of OFDM systems is that its high Peak-to-Average Power Ratio (PAPR) and to deal with these high fluctuations of Peak-to-Average Power Ratio many amplifiers linearizing methods have been developed. One of the most commonly used linearizing technique for power amplifier to operate in linear region is digital predistortion. Digital Predistortion (DPD) technique placed preceding to power amplifier and provide the inverse transfer function of Power Amplifier (PA) and also balances the amplitude and phase harmonics. Because of its simplicity and good performance baseband band digital predistortion is preferred choice over all other linearization methods. Paper analyses the model of power amplifier which develops the impairments when compared that of input signals. Derived the DPD coefficients through general polynomial method. With PA measurements and DPD coefficients static DPD is designed. Due to the varying characteristics of power amplifier static DPD is turned to adaptive one through indirect learning architecture which uses Least Mean Square (LMS) algorithm. The advantage of using this digital predistortion technique it reduces the spectral growth, the power amplifier is operated in the linear region for longer time, efficiency is also increased. LMS algorithm provides the better reduction in spectral growth when compared with static DPD design, low complexity in designing and provide better rate of convergence. All the modelling and simulations are performed in MATLAB and SIMULINK environments.


Power Amplifier (PA) Orthogonal Frequency Division Multiplexing (OFDM) Peak to Average Power ratio (PAPR) Digital predistortion General memory polynomial Static DPD Adaptive DPD Indirect learning architecture LMS algorithm 


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© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Department of TCERVCEBengaluruIndia

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