Advertisement

Adaptive Transmission in a MIMO-OFDM System in Nakagami-m Fading Channels

  • Vidhyacharan BhaskarEmail author
  • Kamireddy Narendra Reddy
Article
  • 190 Downloads

Abstract

The goal of fourth generation (4G) mobile communications system is to seamlessly integrate a wide variety of communication services such as high speed data, video and multimedia traffic as well as voice signals. One of the promising approaches in 4G is the Adaptive Orthogonal Frequency Division Multiplexing (AOFDM) technique. In Multiple Input Multiple Output (MIMO)-OFDM, adaptive transmission scheme is employed according to channel fading conditions in OFDM to improve the performance. In this paper, adaptive modulation is only considered. To further enhance the system performance, convolutional coding can be employed to the OFDM system. The obtained results show that significant improvement in bit error rate and average spectrum efficiency can be achieved demonstrating the superiority of the adaptive modulation schemes compared to fixed transmission schemes.

Keywords

Multiple input multiple output orthogonal frequency division multiplexing Nakagami-m fading channel Adaptive modulation Bit error rate Average spectrum efficiency Ergodic capacity 

References

  1. 1.
    H. Yang, A road to future broadband wireless access: MIMO-OFDM based air interface, IEEE Communications Magazine, Vol. 43, No. 1, pp. 53–60, 2005.CrossRefGoogle Scholar
  2. 2.
    V. Balakrishna, and Vidhyacharan Bhaskar, “Performance analysis over slowly fading multiple input multiple output channels using quantized and erroneous feedback,” IET Communications, vol. 6, no. 11, pp. 1397–1406, 2012.Google Scholar
  3. 3.
    S. Shyamala and Vidhyacharan Bhaskar, “Capacity of multiuser multiple input multiple output orthogonal frequency division multiplexing systems with doubly correlated channels for various fading distributions,” IET Communications, vol. 5, no. 9, pp. 1230–1236, June 2011.Google Scholar
  4. 4.
    P. Chan and R. Cheng, Capacity maximization for zero-forcing MIMO-OFDMA downlink systems with multiuser diversity, IEEE Transactions on Wireless Communications, Vol. 6, No. 5, pp. 1880–1889, 2007.CrossRefGoogle Scholar
  5. 5.
    Y. Zhang and K. Letaief, An efficient resource-allocation scheme for spatial multiuser access in MIMO/OFDM systems, IEEE Transactions on Communications, Vol. 53, No. 1, pp. 107–116, 2005.CrossRefGoogle Scholar
  6. 6.
    Sarma Sandeep Jayakrishnan, and Vidhyacharan Bhaskar, “Performance analysis of MIMO-OFDM in various outdoor fading environments,” International Journal of Electronics and Communications, vol. 66, no. 10, pp. 22–28, Jan. 2012.Google Scholar
  7. 7.
    Raj, U., and Bhaskar, V., “Performance analysis of scheduling schemes for MIMO-OSFBC-OFDM system in α − μ fading channel scenarios,” International Conference on Communications and Signal Processing (ICCSP), DOI:  10.1109/iccsp.2013.6577033, pp. 144–148, 2013.
  8. 8.
    Vidhyacharan Bhaskar, “Novel Closed-form expressions for Ergodic capacity of MIMO-OSFBC-OFDM systems over Channel adaptation policies,” Wireless Personal Communications, DOI:  10.1007/s11277-013-1537-6, vol. 77, no. 2, pp. 811–822, July 2014.
  9. 9.
    K. M. Hadi, R. Tripathi, and K. Kant, “Performance of adaptive modulation in a multipath fading channel,” 8 th International Conference on Advanced Communication Technology (ICACT), Phoenix Park, Korea, vol. 2, pp. 1277–1282, Feb. 2006.Google Scholar
  10. 10.
    M. Torabi, S. Aissa and M. Soleymani, On the BER performance of space-frequency block coded OFDM systems in fading MIMO channels, IEEE Transactions on Wireless Communications, Vol. 6, No. 4, pp. 1366–1373, 2007.CrossRefGoogle Scholar
  11. 11.
    J. Chen and T. Pratt, “Energy efficiency of adaptive transmission for MIMO-OFDM systems over polarization-sensitive channels”, 2014 National Wireless Research Collaboration Symposium (NWRCS), IdahoUSA, 2014. pp. 127–132.Google Scholar
  12. 12.
    P. Xia, S. Zhou and G. B. Giannakis, Adaptive MIMO-OFDM based on partial channel state information, IEEE Transactions on Signal Processing, Vol. 52, No. 1, pp. 202–213, 2004.MathSciNetCrossRefGoogle Scholar
  13. 13.
    N. Peram and V. Bhaskar, Performance modelling of finite-state Markov chains for Nakagami-q and α − μ distributions over adaptive modulation and coding schemes, AeUe International Journal of Electronics and Communications, Vol. 67, No. 1, pp. 64–71, 2013.CrossRefGoogle Scholar
  14. 14.
    S. Krithiga, and Vidhyacharan Bhaskar, “Performance of threshold conditions over independent and non-identically distributed α − μ fading channels over multiple input multiple output orthogonal space-time block coding systems,” IET Communications, vol. 8, no. 16, pp. 2891–2899, Nov. 2014.Google Scholar
  15. 15.
    S. Sampei and H. Harada, System Design Issues and Performance Evaluation for Adaptive Modulation in New Wireless Access Systems, Proceedings of the IEEE, Vol. 95, No. 12, pp. 2456–2471, 2007.CrossRefGoogle Scholar
  16. 16.
    T. S. Rappaport, Wireless Communications, Principles and Practice, vol. 2nd, Prentice Hall Inc.NJ, USA, 2001.Google Scholar
  17. 17.
    T. M. Duman, and A. Ghrayeb, Coding for MIMO Communication Systems, John Wiley & Sons, Ltd., West Sussex PO19 8SQ, UK, 2007.Google Scholar
  18. 18.
    I. S. Gradshteyn and I. M. Ryzhik, Table of Integrals, Series and Products, vol. 7th, Academic PressBurlington, MA, USA, 2007.zbMATHGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2015

Authors and Affiliations

  • Vidhyacharan Bhaskar
    • 1
    • 2
    Email author
  • Kamireddy Narendra Reddy
    • 3
  1. 1.Department of Electrical and Computer EngineeringSan Francisco State UniversitySan FranciscoUSA
  2. 2.Department of Electrical EngineeringNorthwestern Polytechnic UniversityFremontUSA
  3. 3.Department of Electronics and Communication EngineeringSRM UniversityKattankulathur, Kancheepuram Dt.India

Personalised recommendations