BER Performance Analysis of Wireless Communication System in Flat Fading Environment

  • O. RavinderEmail author
  • M. Ravinder
  • K. Krishna Kumar
Conference paper
Part of the Lecture Notes in Networks and Systems book series (LNNS, volume 33)


The performance of any wireless communication system mainly depends on the wireless channel environment. Because of huge demand and growth in mobile communication and Internet services the optimization of the wireless communication is critical. If we know the perfect channel characteristics we can easily develop a high bandwidth-efficient wireless communication system. The wireless channel mainly suffers from 3 different modes. They are Reflection, Diffraction, and Scattering. Combination of these three phenomena’s is called fading. Fading is fluctuations in the power levels of the signal. In this paper we find the Bit Error Rate (BER) of wireless communication system in Flat Fading environment. At the same time we evaluate the system performance of M-PSK modulation schemes using MATLAB.


Optimization Reflection Diffraction Scattering Flat fading BER M-PSK 


  1. 1.
    Rappaport TS (2002) Wireless communications: principles and practice, 2nd ednGoogle Scholar
  2. 2.
    Biglieri E, Proakis J, Shamai S (1998) Fading channels: Information-theoretic and communications aspects. IEEE Trans Inform Theory 44:2619–2692Google Scholar
  3. 3.
    Price R, Green PE (1958) A communication technique for multipath channels. Proc IEEE 46:555–570Google Scholar
  4. 4.
    Foschini GJ (1996) Layered space-time architecture for wireless communication in a fading environment when using multi-element antennas. Bell Labs Tech J 1(2):41–59Google Scholar
  5. 5.
    Yoo D-S, Hafeez A, Stark WE (1999) Trellis-based multiuser detection for DS-CDMA systems with frequency selective fading. In: Wireless communications and networking conference, vol 2. IEEE, pp 829–833Google Scholar
  6. 6.
    Winters JH (1994) The diversity gain of transmit diversity in wireless systems with rayleigh fading. In: ICC ’94, pp 1121–1125Google Scholar
  7. 7.
    Proakis JG (2001) Digital communications, 4th edn; Monsen P (1974) Adaptive equalization of the slow fading channel. IEEE Trans 22:1064–1075Google Scholar
  8. 8.
    Crozier S, Falconer D, Mahmoud, S (1989) Shortblock equalization techniques employing channel estimation for fading time dispersive channels. In: IEEE vehicular technology conference, pp 142–146Google Scholar
  9. 9.
    Cimini LJ, Sollenberger NR (1997) OFDM with diversity and coding for high-bit-rate mobile data applications. Mobile Multimedia Communications. Springer, Boston, MA, pp 247–254Google Scholar
  10. 10.
    Simon MK, Divsalar D (1990) Multiple symbol Differential detection of M -PSK. IEEE Trans Commun 38:300–308Google Scholar
  11. 11.
    Bitner JR, Ehrlich G, Reingold EM (1976) Efficient generation of the binary reflected Gray code and its applications. Commun ACM 19(9):517–521Google Scholar
  12. 12.
    Marzetta TL, Hochwald BM (1999) Capacity of a mobile multiple-antenna communication link in Rayleigh flat fading. IEEE Trans Inform Theory 45:139–157Google Scholar
  13. 13.
    Ziv J (1965) Probability of decoding error for random phase and Rayleigh fading channels. IEEE Trans 11:53–61; Pukkila M (2000) Channel estimation modelingGoogle Scholar
  14. 14.
    Noneaker DL, Pursley MB (1994) Error probability bounds for M-PSK and M-DPSK and selective fading diversity channels. IEEE Trans Veh Technol 43(4):997–1005Google Scholar
  15. 15.
    Proakis J (1968) On the probability of error for multichannel reception of binary signals. IEEE Trans Commun Technol COM-16:68–71Google Scholar
  16. 16.
    Tjhung TT, Loo C, Secord NP (1992) BER performance of DQPSK in slow Rician fading. Electron Lett 28:1763–1765Google Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  1. 1.GNITCHyderabadIndia
  2. 2.KCEANizamabadIndia

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