BER Performance of SFBC–OFDM Systems Working Over Fading Channels Under Impulsive Environment

  • Amit Kumar Kohli
  • Divneet Singh KapoorEmail author
Research Article - Electrical Engineering


This correspondence presents the bit-error-rate (BER) performance analysis of the space-frequency-block-coded OFDM (SFBC–OFDM) communication systems, working over wireless fading channels under the impulsive environment. The effects of imperfect channel state information (CSI) on the BER performance are also investigated, while using the M-ary phase-shift keying and M-ary quadrature amplitude modulation for digital data transmission over the fading channels corrupted by the impulse noise and additive white Gaussian noise (AWGN). The imperfect CSI usually arises due to the noisy channel estimates at receiver. The major focus is on the description of closed-form expressions for the BER performance of underlying SFBC–OFDM systems impaired by impulse noise, in which the noise bucket concept helps in quantifying its performance under the Rayleigh fading scenario. Simulation results are presented to connote the deterioration of BER performance of SFBC–OFDM systems due to the presence of impulse noise, AWGN and noisy channel estimates at the receiver, under different channel fading conditions exhibiting Rayleigh and Nakagami-m probability distributions. For lower values of m in the range \(0.5 \le m < 1\), the adverse impact of impulse noise can be reduced by increasing the number of subcarriers in an OFDM symbol block period.


SFBC STBC OFDM Rayleigh fading Nakagami-m fading Impulse noise 


  1. 1.
    Chang, R.W.: Synthesis of band-limited orthogonal signals for multichannel data transmission. Bell Syst. Tech. J. 45(10), 1755–1796 (1966)CrossRefGoogle Scholar
  2. 2.
    Peled, A.; Ruiz, A.: Frequency domain data transmission using reduced computational complexity algorithms. In: Proceedings of the IEEE ICASSP-80, Denver, CO, pp. 964–967 (1980)Google Scholar
  3. 3.
    Cimini, L.J.: Analysis and simulation of a digital radio channel using orthogonal frequency division multiplexing. IEEE Trans. Commun. 33(7), 665–675 (1985)CrossRefGoogle Scholar
  4. 4.
    Bingham, J.A.C.: Multicarrier modulation for data transmission: an idea whose time has come. IEEE Commun. Mag. 28(5), 5–14 (1990)CrossRefGoogle Scholar
  5. 5.
    Lee, K.F.; Williams, D.B.: A space-frequency transmitter diversity technique for OFDM systems. In: Proceedings of the IEEE GLOBECOM, San Francisco, CA, USA, vol. 3, pp. 1475–1477 (2000)Google Scholar
  6. 6.
    Lee, K.F.; Williams, D.B.: A space-time coded transmitter diversity technique for frequency selective fading channels. In: Proceedings of the IEEE Sensor Array and Multichannel Signal Processing Workshop, Cambridge, MA, USA, pp. 149–152 (2000)Google Scholar
  7. 7.
    Zhidkov, S.V.: Analysis and comparison of several simple impulsive noise mitigation schemes for OFDM receivers. IEEE Trans. Commun. 56(1), 5–9 (2008)CrossRefGoogle Scholar
  8. 8.
    Suraweera, H.A.; Armstrong, J.: Noise bucket effect for impulse noise in OFDM. Electron. Lett. 40(18), 1156–1157 (2004)CrossRefGoogle Scholar
  9. 9.
    Armstrong, J.; Suraweera, H.A.: Impulse noise mitigation for OFDM using decision directed noise estimation. In: Proceedings of the IEEE ISSSTA 2004, Sydney, Australia, pp. 174–178 (2004)Google Scholar
  10. 10.
    Lago-Fernandez, J.; Salter, J.: Modelling impulsive interference in DVB-T: statistical analysis, test waveforms and receiver performance. BBC R&D White Paper. (2004). Accessed 15 Jan 2019
  11. 11.
    Poole, R.: DVB-T Transmission, Reception and Measurement, DTG Monograph No. 4, Digital TV Group (2002)Google Scholar
  12. 12.
    Al-Dhahir, N.: Single-carrier frequency-domain equalization for space-time block-coded transmissions over frequency-selective fading channels. IEEE Commun. Lett. 5(7), 304–306 (2001)CrossRefGoogle Scholar
  13. 13.
    Jang, J.-H.; Won, H.-C.; Im, G.-H.: Cyclic prefixed single carrier transmission with SFBC over mobile wireless channels. IEEE Signal Process. Lett. 13(5), 261–264 (2006)CrossRefGoogle Scholar
  14. 14.
    Hanzo, L.L.; Munster, M.; Choi, B.; Keller, T.: OFDM and MC-CDMA for Broadband Multi-user Communications, WLANs and Broadcasting. Wiley, New York (2005)Google Scholar
  15. 15.
    Ye, S.; Blum, R.S.; Cimini, L.J.: Adaptive OFDM systems with imperfect channel state information. IEEE Trans. Wireless Commun. 5(11), 3255–3265 (2006)CrossRefGoogle Scholar
  16. 16.
    Torabi, M.; Aissa, S.; Soleymani, M.R.: On the BER performance of space-frequency block coded OFDM systems in fading MIMO channels. IEEE Trans. Wireless Commun. 6(4), 1366–1373 (2007)CrossRefGoogle Scholar
  17. 17.
    Armstrong, J.; Feramez, M.; Suraweera, H.A.: Optimum noise thresholds in decision directed impulse noise mitigation for OFDM. In: Proceedings of the IEEE CSNDSP 2004, Newcastle, UK, pp. 168–171 (2004)Google Scholar
  18. 18.
    Suraweera, H.A.; Chai, C.; Shentu, J.; Armstrong, J.: Analysis of impulse noise mitigation techniques for digital television systems. In: Proceedings of the 8th International OFDM Workshop, Hamburg, Germany, pp. 172–176 (2003)Google Scholar
  19. 19.
    Grover, A.; Kapoor, D.S.; Kohli, A.K.: Characterization of impulse noise effects on space-time block-coded orthogonal frequency division multiplexing (OFDM) signal reception. Int. J. Phys. Sci. 7(25), 4003–4011 (2012)Google Scholar
  20. 20.
    Chung, S.T.; Goldsmith, A.J.: Degrees of freedom in adaptive modulation: a unified view. IEEE Trans. Commun. 49(9), 1561–1571 (2001)CrossRefGoogle Scholar
  21. 21.
    Nakagami, M.: The m-distribution, a general formula of intensity distribution of rapid fading. In: Hoffman, W.G. (ed.) Statistical Methods in Radio Wave Propagation. Pergamon, Oxford (1960)Google Scholar
  22. 22.
    Zhang, Q.T.: Maximal-ratio combining over Nakagami fading channels with an arbitrary branch covariance matrix. IEEE Trans. Veh. Technol. 48(4), 1141–1150 (1999)CrossRefGoogle Scholar
  23. 23.
    Scaglione, A.; Barbarossa, S.; Giannakis, G.B.: Optimal adaptive precoding for frequency-selective Nagakami-m fading channels. In: Proceedings of the IEEE VTS Fall VTC2000, Boston, MA, USA, vol. 3, pp. 1291–1295 (2000)Google Scholar
  24. 24.
    Du, Z.; Cheng, J.; Beaulieu, N.C.: Accurate error-rate performance analysis of OFDM on frequency-selective Nakagami-m fading channels. IEEE Trans. Commun. 54(2), 319–328 (2006)CrossRefGoogle Scholar
  25. 25.
    Kang, Z.; Yao, K.; Lorenzelli, F.: Nakagami-m fading modeling in the frequency domain for OFDM system analysis. IEEE Commun. Lett. 7(10), 484–486 (2003)CrossRefGoogle Scholar
  26. 26.
    Beaulieu, N.C.; Cheng, C.: Efficient Nakagami-m fading channel simulation. IEEE Trans. Veh. Technol. 54(2), 413–424 (2005)CrossRefGoogle Scholar
  27. 27.
    Torabi, M.: Adaptive modulation for space–frequency block coded OFDM systems. AEU Int. J. Electron. Commun. 62(7), 521–533 (2008)CrossRefGoogle Scholar
  28. 28.
    Kohli, A.K.; Kapoor, D.S.: Adaptive filtering techniques using cyclic prefix in OFDM systems for multipath fading channel prediction. Circuits Syst. Sig. Process. 35(10), 3595–3618 (2016)MathSciNetCrossRefGoogle Scholar
  29. 29.
    Bansal, A.; Kohli, A.K.: Suppression of impulsive noise in OFDM system using imperfect channel state information. Optik Int. J. Light Electron Opt. 127(4), 2111–2115 (2016)CrossRefGoogle Scholar
  30. 30.
    Sehrawat, S.; Kohli, A.K.: Optimized mitigation of impulsive noise in OFDM system using CSI. Optik Int. J. Light Electron Opt. 127(20), 9627–9634 (2016)CrossRefGoogle Scholar
  31. 31.
    Alamouti, S.M.: A simple transmit diversity technique for wireless communications. IEEE J. Sel. Areas Commun. 16(8), 1451–1458 (1998)CrossRefGoogle Scholar
  32. 32.
    Yoo, T.; Goldsmith, A.J.: Capacity of fading MIMO channels with channel estimation error. In: Proceedings of the IEEE International Conference on Communication (ICC’04), Paris, France, vol. 2, pp. 808–813 (2004)Google Scholar
  33. 33.
    Torabi, M.; Soleymani, M.R.; Aissa, S.: On the performance of MIMO–OFDM systems with imperfect channel information. In: Proceedings of the IEEE Conference on Wireless Networks, Communication, and Mobile Computing (ICWCMC’05), Maui, USA, vol. 1, pp. 600–605 (2005)Google Scholar
  34. 34.
    Proakis, J.G.: Digital Communications, 3rd edn. McGraw-Hill, New York (1995)zbMATHGoogle Scholar
  35. 35.
    Papoulis, A.: Probability Random Variables and Stochastic Processes, 3rd edn. McGraw-Hill, New York (1991)zbMATHGoogle Scholar
  36. 36.
    Ghosh, M.: Analysis of the effect of impulse noise on multicarrier and single carrier QAM systems. IEEE Trans. Commun. 44(2), 145–147 (1996)MathSciNetCrossRefGoogle Scholar
  37. 37.
    Sandhu, S.; Paulraj, A.: Space-time block codes: a capacity perspective. IEEE Commun. Lett. 4(12), 384–386 (2000)CrossRefGoogle Scholar
  38. 38.
    Zhang, H.; Gulliver, T.A.: Capacity and error probability analysis for orthogonal space-time block codes over fading channels. IEEE Trans. Wirel. Commun. 4(2), 808–819 (2005)CrossRefGoogle Scholar
  39. 39.
    Kapoor, D.S.; Kohli, A.K.: Simulation of basis expansion model for channel fading using AR1 process. Wireless Pers. Commun. 85(3), 791–798 (2015)CrossRefGoogle Scholar
  40. 40.
    Kohli, A.K.: Fading model for antenna array receiver for a ring-type cluster of scatterers. Int. J. Electron. 98(7), 933–940 (2011)CrossRefGoogle Scholar
  41. 41.
    Wang, H.S.; Chang, P.: On verifying the first-order Markovian assumption for a Rayleigh fading channel model. IEEE Trans. Veh. Technol. 45(2), 353–357 (1996)CrossRefGoogle Scholar
  42. 42.
    Hastings, C.: Approximations for Digital Computers. Princeton University Press, Princeton, NJ (1955)CrossRefGoogle Scholar
  43. 43.
    Cheng, C.: A Nakagami-m fading channel simulator. M.Sc. thesis, Department of Electrical and Computer Engineering, Queen’s University, Kingston, ON, Canada (2000)Google Scholar
  44. 44.
    Khan, M.N.: Importance of noise models in FSO communications. EURASIP J. Wirel. Commun. Netw. 2014(1), 102 (2014)CrossRefGoogle Scholar
  45. 45.
    Khan, M.N.; et al.: Maximizing throughput of hybrid FSO-RF communication system: an algorithm. IEEE Access 6, 30039–30048 (2018)CrossRefGoogle Scholar
  46. 46.
    Li, C.; Yang, H.J.; Sun, F.; Cioffi, J.M.; Yang, L.: Adaptive overhearing in two-way multi-antenna relay channels. IEEE Signal Process. Lett. 23(1), 117–120 (2016)CrossRefGoogle Scholar
  47. 47.
    Li, C.; Liu, P.; Zou, C.; Sun, F.; Cioffi, J.M.; Yang, L.: Spectral-efficient cellular communications with coexistent one- and two-hop transmissions. IEEE Trans. Veh. Technol. 65(8), 6765–6772 (2016)CrossRefGoogle Scholar
  48. 48.
    Li, C.; Zhang, S.; Liu, P.; Sun, F.; Cioffi, J.M.; Yang, L.: Overhearing protocol design exploiting intercell interference in cooperative green networks. IEEE Trans. Veh. Technol. 65(1), 441–446 (2016)CrossRefGoogle Scholar
  49. 49.
    Li, C.; Yang, H.J.; Sun, F.; Cioffi, J.M.; Yang, L.: Multiuser overhearing for cooperative two-way multiantenna relays. IEEE Trans. Veh. Technol. 65(5), 3796–3802 (2016)CrossRefGoogle Scholar
  50. 50.
    Zhidkov, S.V.: Impulse noise suppression in OFDM based communication systems. IEEE Trans. Conserv. Electron. 49(4), 944–948 (2003)CrossRefGoogle Scholar
  51. 51.
    Kuai, X.; Sun, H.; Zhou, S.; Cheng, E.: Impulsive noise mitigation in underwater acoustic OFDM systems. IEEE Trans. Veh. Technol. 65(10), 8190–8202 (2016)CrossRefGoogle Scholar
  52. 52.
    Kohli, A.K.; Lamba, G.S.: Impact of phase noise on single-tap equalization for fast–OFDM signals under generic linear fading channels. Optik Int. J. Light Electron Opt. 169, 382–391 (2018)CrossRefGoogle Scholar

Copyright information

© King Fahd University of Petroleum & Minerals 2019

Authors and Affiliations

  1. 1.Department of Electronics and Communication EngineeringThapar Institute of Engineering and TechnologyPatialaIndia

Personalised recommendations