Skip to main content
SpringerLink
Log in

Optimum power allocation in OFDM systems under power amplifier nonlinearity

  • Published:
Analog Integrated Circuits and Signal Processing Aims and scope Submit manuscript

Abstract

In this paper, the optimum power allocation for subcarriers in orthogonal frequency division multiple system is derived which maximizes the total rate of system under nonlinearity of practical power amplifier. The rate of system by using analytical signal to interference ratio formula is optimized to derive optimal power scales for subcarriers. The problem is nonconvex and a comprehensive learning particle swarm optimization method is designed to solve the problem. The simulation results demonstrate that by considering nonlinearity in power allocation, better rate can be achieved compared to conventional power allocation methods.

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

Similar content being viewed by others

References

  1. Jang, J., & Lee, K. B. (2003). Transmit power adaptation for multiuser OFDM systems. IEEE Journal on Selected Areas in Commununications, 21, 171–178.

    Article  Google Scholar 

  2. Majidi, M., Mohammadi, A., & Abdipour, A. (2013). Accurate analysis of spectral regrowth of nonlinear power amplifier driven by cyclostationary modulated signals. Springer Journal on Analog Integrated Circuits and Signal Processing, 74, 425–437.

    Article  Google Scholar 

  3. Bohara, V. A., & Ting, S. H. (2008). Analysis of OFDM signals in nonlinear high power amplifier with memory. In IEEE international conference on communication (ICC) (pp. 3653–3657).

  4. Majidi, M., Mohammadi, A., & Abdipour, A. (2014). Analysis of the power amplifier nonlinearity on the power allocation in cognitive radio networks. IEEE Transactions on Communications, 62, 467–477.

    Article  Google Scholar 

  5. Baghani, M., Mohammadi, A., Majidi, M., & Valkama, M. (2014). Analysis and rate optimization of OFDM-based cognitive radio networks under power amplifier nonlinearity. IEEE Transactions on Communications, 62, 3410–3419.

    Article  Google Scholar 

  6. Kennedy, J., & Eberhart, R. (1995). Particle swarm optimization. In IEEE International Conference on Neural Network (ICNN) (pp. 1942–1948).

  7. Hassan, R., Cohanim, B., & de Weck, O. (2005). A comparison of particle swarm optimization and the genetic algorithm. Presented at the AIAA/ASME/ASCE/AHS/ASC 46th structures, structural dynamics and materials conference.

  8. Scott-Hayward, S., & Garcia-Palacios, E. (2015). Multimedia resource allocation in mmwave 5G networks. IEEE Commununication Magazine, 53, 240–247.

    Article  Google Scholar 

  9. Chen, W. N., Zhang, J., Lin, Y., Chen, N., Zhan, Z., Chung, H. S.-H., et al. (2013). Particle swarm optimization with an aging leader and challengers. IEEE Transactions on Evolutionary Computation, 17, 241–258.

    Article  Google Scholar 

  10. Cottais, E., Wang, Y., & Toutain, S. (2008). Spectral regrowth analysis at the output of a memoryless power amplifier with multicarrier signals. IEEE Transactions on Communications, 56, 1111–1118.

    Article  Google Scholar 

  11. Ku, H., & Kenney, J. (2003). Behavioral modeling of nonlinear RF power amplifiers considering memory effects. IEEE Transactions on Microwave Theory and Techniques, 51, 2495–2504.

    Article  Google Scholar 

  12. Dardari, D., Tralli, V., & Vaccari, A. (2000). A theoretical characterization of nonlinear distortion effects in OFDM systems. IEEE Transactions on Commununication, 48, 1755–1763.

    Article  Google Scholar 

  13. Baghani, M., Mohammadi, A., & Majidi, M. (2017). Downlink resource allocation in OFDMA wireless networks under power amplifier nonlinearity. IET Communications, 11, 2751–2757.

    Article  Google Scholar 

  14. Liang, J. J., Qin, A. K., Suganthan, P. N., & Baskar, S. (2006). Comprehensive learning particle swarm optimizer for global optimization of multimodal functions. IEEE Transactions on Evolutionary Computation, 10, 281–295.

    Article  Google Scholar 

  15. Gong, Y. J., Zhang, J., Chung, H., Chen, W. N., Zhan, Z. H., Li, Y., et al. (2013). An efficient resource allocation scheme using particle swarm optimization. IEEE Transactions on Evolutionary Computation, 16, 801–816.

    Article  Google Scholar 

  16. Tang, M., Long, C., & Guan, X. (2011). Nonconvex optimization for power control in wireless CDMA networks. Wireless Personal Communications, 58, 851–865.

    Article  Google Scholar 

  17. Kennedy, J., & Eberhart, R. C. (2001). Swarm intelligence. San Francisco, CA: Morgan Kaufmann Publishers Inc.

    Google Scholar 

  18. Raich, R., & Zhou, G. T. (2004). Spectral analysis for bandpass nonlinearity with cyclostationary input. In IEEE international conference on acoustics, speech, and signal processing (ICASSP) (pp. ii465–ii468).

Download references

Author information

Authors and Affiliations

  1. Microwave and Wireless Communication Research Lab., Electrical Engineering Department, Amirkabir University of Technology, Tehran, Iran

    Mina Baghani & Abbas Mohammadi

  2. Department of Electrical and Computer Engineering, University of Kashan, Kashan, Iran

    Mahdi Majidi

Authors
  1. Mina Baghani
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Abbas Mohammadi
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Mahdi Majidi
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Mina Baghani.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Baghani, M., Mohammadi, A. & Majidi, M. Optimum power allocation in OFDM systems under power amplifier nonlinearity. Analog Integr Circ Sig Process 99, 33–38 (2019). https://doi.org/10.1007/s10470-018-1314-2

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10470-018-1314-2

Keywords

Search

Navigation