Skip to main content

Advertisement

SpringerLink
Log in

Linearization of RF Power Amplifiers in Wideband Communication Systems by Adaptive Indirect Learning Using RPEM Algorithm

  • Published:
Mobile Networks and Applications Aims and scope Submit manuscript

Abstract

This paper proposes a new approach of digital predistortion (DPD) technique based on the adaptive indirect learning architecture (ILA) by using a recursive prediction error minimization (RPEM) algorithm for linearizing radio frequency (RF) power amplifiers (PAs) in emerging wideband communication systems. In the proposed RPEM-based linearization approach, the forgetting factor varies with time and is less sensitive to noise. Therefore, the predistorter (PD) parameter estimates become more consistent and accurate in steady state so that the mean square errors can be reduced. Both the error vector magnitude (EVM) and the adjacent channel power ratio (ACPR) are used to evaluate the DPD technique in RF PAs employing the proposed linearization. The efficiency validation of the proposed method is based on a simulated PA Wiener model. The simulation results have clarified the improvement of the proposed adaptive ILA-based DPD with RPEM algorithm in terms of both EVM and ACPR.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14

Similar content being viewed by others

References

  1. Chen Y, Guo Z, Yang X et al (2018) Optimization of coverage in 5g self-organizing small cell networks. Mobile Networks and Applications 23(6)

  2. Ahn J, Lee J, Park S et al (2019) Power efficient clustering scheme for 5g mobile edge computing environment. Mobile Netw Appl 24(2)

  3. Ghannouchi FM, Hammi O (2009) Behavioral modeling and predistortion. IEEE Microw Mag 10(7):52–64

    Article  Google Scholar 

  4. Chani-Cahuana J, Landin PN, Fager C, Eriksson T (2016) Iterative learning control for RF power amplifier linearization. IEEE Trans Microw Theory Tech 64(9):2778–2789

    Article  Google Scholar 

  5. Guan L, Zhu A (2014) Green communications: digital predistortion for wideband RF power amplifiers. IEEE Microw Mag 15(7):84–99

    Article  Google Scholar 

  6. Ding L, Zhou GT, Morgan DR, Ma Z, Kenney JS, Kim J, Giardina CR (2004) A robust digital baseband predistorter constructed using memory polynomials. IEEE Trans Commun 52(1):159– 165

    Article  Google Scholar 

  7. Guo Y, Yu C, Zhu A (2015) Power adaptive digital predistortion for wideband RF power amplifiers with dynamic power transmission. IEEE Trans Microw Theory Tech 63(11):3595–3607

    Article  Google Scholar 

  8. Schoukens M, Hammenecker J, Cooman A (2017) Obtaining the preinverse of a power amplifier using iterative learning control. IEEE Trans Microw Theory Tech 65(11):4266–4273

    Article  Google Scholar 

  9. Zhou D, DeBrunner VE (2007) Novel adaptive nonlinear predistorters based on the direct learning algorithm. IEEE Trans Signal Process 55(1):120–133

    Article  MathSciNet  Google Scholar 

  10. Choi S, Jeong ER, Lee YH (2009) Adaptive predistortion with direct learning based on piecewise linear approximation of amplifier nonlinearity. IEEE Select Topics Signal Process 3(3):397–404

    Article  Google Scholar 

  11. Suryasarman PM, Springer A (2015) A comparative analysis of adaptive digital predistortion algorithms for multiple antenna transmitters. IEEE Trans Circuits Syst I 62(5):1412–1420

    Article  MathSciNet  Google Scholar 

  12. Eun C, Powers EJ (1997) A new Volterra predistorter based on the indirect learning architecture. IEEE Trans Signal Process 45(1):223–227

    Article  Google Scholar 

  13. Morgan DR, Ma Z, Ding L (2003) Reducing measurement noise effects in digital predistortion of RF power amplifiers. In: Proc IEEE International Conference on Communications (ICC’03), pp 2436–2439

  14. Paaso H, Mammela A (2008) Comparison of direct learning and indirect learning predistortion architectures. In: Proc IEEE international symposium on wireless communication systems, pp 309–313

  15. Hussein MA, Bohara VA, Venard O (2012) On the system level convergence of ILA and DLA for digital predistortion. In: Proc. 2012 international symposium on wireless communication systems (ISWCS), pp 870–874

  16. Guan L, Zhu A (2011) Dual-loop model extraction for digital predistortion of wideband RF power amplifiers. IEEE Microwave and Wireless Components Letters 21(9):501–503

    Article  Google Scholar 

  17. Mohr B, Li W, Heinen S (2012) Analysis of digital predistortion architectures for direct digital-to-RF transmitter systems. In: Proc. 2012 IEEE 55th international midwest symposium on circuits and systems (MWSCAS), pp 650–653

  18. Söderström T, Stoica P (eds) (1989) System identification. Prentice-Hall Inc., Upper Saddle River

  19. Abdelrahman AE, Hammi O, Kwan AK, Zerguine A, Ghannouchi FM (2016) A novel weighted memory polynomial for behavioral modeling and digital predistortion of nonlinear wireless transmitters. IEEE Trans Industrial Electron 63(3):1745–1753

    Article  Google Scholar 

  20. Proakis JG, Manolakis DK (2006) Digital signal processing, 4th edn. Prentice-Hall Inc., Upper Saddle River

    Google Scholar 

  21. Haykin S (2014) Adaptive filter theory, 5th edn. Prentice-Hall Inc., Upper Saddle River

    MATH  Google Scholar 

  22. Mkadem F (2014) Behavioral modeling and digital predistortion of wide- and multi- band transmitter systems. Ph.D. dissertation

  23. Feng X, Wang Y, Feuvrie B, Descamps A-S, Ding Y, Yu Z (2016) Analysis on LUT based digital predistortion using direct learning architecture for linearizing power amplifiers. EURASIP Wireless Commun Netw 2016(1):132

    Article  Google Scholar 

  24. Kwon J, Eun C (2010) Digital feedforward compensation scheme for the non-linear power amplifier with memory. IJISTA 9:326–334

    Article  Google Scholar 

  25. Eun C, Powers EJ (1995) A predistorter design for a memory-less nonlinearity preceded by a dynamic linear system. In: Proc. GLOBECOM ’95, vol 1, pp 152–156

  26. Saleh AAM (1981) Frequency-independent and frequency-dependent nonlinear models of twt amplifiers. IEEE Trans Commun COM-29(11):1715–1720

    Article  Google Scholar 

Download references

Acknowledgment

This research is funded by Vietnam National Foundation for Science and Technology Development (NAFOSTED) under grant number 102.02-2016.12.

Author information

Authors and Affiliations

  1. Le Quy Don Technical University, no. 236 Hoang Quoc Viet Str., Hanoi, Vietnam

    Duc Han Le, Van-Phuc Hoang & Minh Hong Nguyen

  2. Duy Tan University, Da Nang, Vietnam

    Hien M. Nguyen

  3. Hanoi University of Science and Technology, no. 1 Dai Co Viet Str., Hanoi, Vietnam

    Duc Minh Nguyen

Authors
  1. Duc Han Le
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Van-Phuc Hoang
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Minh Hong Nguyen
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Hien M. Nguyen
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Duc Minh Nguyen
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Van-Phuc Hoang.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

This paper has been submitted in part to the 5th EAI International Conference on Industrial Networks and Intelligent Systems (INISCOM 2019). The corresponding and the first authors are the main authors contributing equally to the paper.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Le, D.H., Hoang, VP., Nguyen, M.H. et al. Linearization of RF Power Amplifiers in Wideband Communication Systems by Adaptive Indirect Learning Using RPEM Algorithm. Mobile Netw Appl 25, 1988–1997 (2020). https://doi.org/10.1007/s11036-020-01545-z

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11036-020-01545-z

Keywords

Search

Navigation