Advertisement

Performance Analysis of Interference for OFDM Systems

  • Jun Luo
  • Jean H. Andrian
  • Chi Zhou
  • James P. StephensSr
Chapter
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 44)

Abstract

The bit error rate (BER) analysis of various interference types is discussed for orthogonal frequency-division multiplexing (OFDM) systems in both analytical form and software simulation results. Specifically, the BER performance of barrage noise interference (BNI), partial band interference (PBI), and multitone interference (MTI) has been investigated in time-correlated Rayleigh fading channel with additive white Gaussian noise (AWGN). In addition, two novel intentional interference injecting methods – optimal-fraction PBI and optimal-fraction MTI – for OFDM systems are proposed with detailed theoretical analysis. Simulation results validate the analytical results. It is shown that under the various channel conditions, the optimal-fraction MTI always gives the best interference effect among all the interference models given in this chapter. Both analysis and simulation indicate that the proposed optimal-fraction MTI can be used to obtain improved interference effect under various channel conditions with low complexity for OFDM systems.

Keywords

Fading Channel Additive White Gaussian Noise Power Spectrum Density Rayleigh Fading Channel OFDM System 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

References

  1. 1.
    R. F. Ormondroyd and E. Al-Susa, “Impact of multipath fading and partial-band interference on the performance of a COFDM/CDMA modulation scheme for robust wireless communications,” IEEE MILCOM, 2, 673–678, 1998.Google Scholar
  2. 2.
    H. Zhang and Y. Li, “Anti-jamming property of clustered OFDM for dispersive channels,” IEEE MILCOM, 1, 336–340, October 2003.Google Scholar
  3. 3.
    J. Park et al., “Effect of partial band jamming on OFDM-based WLAN in 802.11 g,” ICASSP 2003, 4, 560–563, April 2003.Google Scholar
  4. 4.
    S. Lijun et al., “BER Performance of frequency domain differential demodulation OFDM in flat fading channel,” GLOBECOM, 1, 1–5, 2003.Google Scholar
  5. 5.
    A. Goldsmith, Wireless Communications, Cambridge University Press, Cambridge, 2005.Google Scholar
  6. 6.
    Y.R. Zheng and C. Xiao, “Improved models for the generation of multiple uncorrelated Rayleigh fading waveforms,” IEEE Communications Letters, 6, 6, 256–258, 2002.CrossRefGoogle Scholar
  7. 7.
    L. Hanzo et al., OFDM and MC-CDMA for Broadband Multi-User Communications, WLANs and Broadcasting, Wiley-IEEE Press, US, September 2003. Google Scholar
  8. 8.
    N. Kingsbury, “Approximation Formulae for the Gaussian Error Integral, Q(x),” Connexions, June 7, 2005.Google Scholar
  9. 9.
    N. Kostov, “Mobile radio channels modeling in Matlab,” Journal of Radioengineering, 12, part 4, 12–17, 2003.Google Scholar
  10. 10.
    A. Papoulis, Probability, Random Variables and Stochastic Processes, 3rd Edition, McGraw-Hill, New York, Feb. 1991Google Scholar
  11. 11.
    IEEE 802.11a, “Part 11: Wireless LAN Medium Access Control (MAC) and Physical Layer (PHY) Specifications: High-speed Physical Layer in the 5 GHz Band,” supplement to IEEE 802.11 Standard, September 1999.Google Scholar

Copyright information

© Springer Science+Business Media, LLC 2009

Authors and Affiliations

  • Jun Luo
    • 1
  • Jean H. Andrian
    • 1
  • Chi Zhou
    • 2
  • James P. StephensSr
    • 3
  1. 1.Department of Electrical and Computer EngineeringFlorida International UniversityMiamiUSA
  2. 2.Department of Electrical and Computer EngineeringIllinois Institute of TechnologyChicagoUSA
  3. 3.Air Force Research LaboratoryWright-Patterson AFBUSA

Personalised recommendations