SVD-Based Linear Precoding Using Channel Estimation for MIMO-OFDM Systems

  • R. Raja KumarEmail author
  • R. Pandian
  • C. Satheeswaran
  • M. KaviPriya
  • P. Indumathi
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 989)


Orthogonal Frequency Division Multiplexing is an approach that can be used to combat the effect of frequency selective fading channels. Apart from spectral efficiency, reliability over fast fading channels is a primary concern in OFDM. MIMO systems offer a solution to this problem owing to the high capacity and beamforming gain. The integration of MIMO with the traditional OFDM systems allow parallel transmission of data with a significant reduction in inter-carrier interference. The tradeoff to be considered is the increase in complexity of the user equipment. This is due to the advanced modulation and estimation operations performed at the receiver. In this paper, we present a transmitter site channel estimation scenario with the help of pilot symbols. Further, a MIMO-OFDM transceiver is designed which utilizes the information of the channel state at the transmitter to perform Singular Value Decomposition (SVD) based linear precoding on the data. Such a type of precoding scheme provides reduction in bit error rate to an optimum range. The simulation results show that a singular value-based precoding technique performs better than the traditional Alamouti space–time block code. But the requirement of additional time slot for channel estimation is a challenge that accompanies this technique.


MIMO-OFDM SVD Alamouti coding QR precoding MMSE 


  1. 1.
    Alamouti, S.M.: A simple transmit diversity technique for wireless communications. IEEE J. Sel. Areas Commun. 16(8)CrossRefGoogle Scholar
  2. 2.
    Gesbert, D.: From theory to practice: an overview of MIMO space–time coded wireless systems. IEEE J. Sel. Areas Commun. 21(3) (2003)CrossRefGoogle Scholar
  3. 3.
    Hochwald, B.M., Marzetta, T.L.: Unitary space–time modulation for multiple-antenna communications in rayleigh flat fading. IEEE Trans. Inf. Theory 46(2), 543–564 (2000)MathSciNetCrossRefGoogle Scholar
  4. 4.
    Jose, J., Ashikhmin, A., Whiting, P., Vishwanath, S.: Channel estimation and linear precoding in multiuser multiple-antenna TDD systems. IEEE Trans. Veh. Technol. 60(5) (2011)CrossRefGoogle Scholar
  5. 5.
    Lopes, A., Aalam, Z.: Performance analysis and hardware implementation of a 802.lln 4×4 MIMO OFDM transceiver using 16-QAM. Int. J. Adv. Inf. Sci. Technol. (IJAIST) 27(27) (2014)Google Scholar
  6. 6.
    Molisch, A.: Wireless Communications. Wiley-IEEE Press (2005)Google Scholar
  7. 7.
    Rappaport, T.S.: Wireless Communications: Principles and Practice, 2nd edn. Pearson, India (2010)Google Scholar
  8. 8.
    Thiagarajan, G., et al.: Novel precoding methods for Rayleigh fading multiuser TDD-MIMO systems. In: IEEE International Conference on Communications, pp. 5586–5591, 10–14 June 2014Google Scholar
  9. 9.
    Thiagarajan, G., et al.: Novel transmit precoding methods for Rayleigh fading multiuser TDD-MIMO systems with CSIT and no CSIR. IEEE Trans. Veh. Technol. 64(3), 973–984 (2015)CrossRefGoogle Scholar
  10. 10.
    Tse, D., Viswanath, P.: Fundamentals of Wireless Communication. Cambridge University Press (2005)Google Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2020

Authors and Affiliations

  • R. Raja Kumar
    • 1
    Email author
  • R. Pandian
    • 2
  • C. Satheeswaran
    • 3
  • M. KaviPriya
    • 4
  • P. Indumathi
    • 4
  1. 1.Mathematics DepartmentSathyabama Institute of Science and TechnologyChennaiIndia
  2. 2.Department of Electronics and Instrumentation EngineeringSathyabama Institute of Science and TechnologyChennaiIndia
  3. 3.Department of Electronics and Communication EngineeringDhaanish Ahmed College of EngineeringChennaiIndia
  4. 4.Department of Electronics EngineeringAnna University, MIT CampusChennaiIndia

Personalised recommendations