MIMO Wireless Communications

  • Abbas Mohammadi
  • Fadhel M. Ghannouchi
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 145)


The multiple input multiple output (MIMO) technique provides the higher bit rate and the better reliability in wireless systems. These advantages are achieved by designing appropriate apace-time codes that provide diversity improvement, spatial multiplexing gain, or a trade-off between diversity order and spatial multiplexing. This chapter provides an overoview on MIMO wireless system concept and its performance. Moreover, the MIMO channel models are discussed.


Channel State Information Multiple Input Multiple Output Multiple Input Single Output Alamouti Code Spatial Multiplex Gain 
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.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Carlson, A.B., Crilly, P.B., Rutledge, J.C.: Communication Systems: An Introduction to Signal and Noise in Electrical Communications, 4th edn. McGraw Hill (2001)Google Scholar
  2. 2.
    Oestges, C., Clerckx, B.: MIMO Wireless Communications: From Real World Propagation to Space Time Code Design. Academic Press (2007)Google Scholar
  3. 3.
    Pahlavan, K., Levesque, A.: Wireless Information Networks, 2nd edn. John Wiley and Sons (2005)Google Scholar
  4. 4.
    Paulraj, A., Nabar, R., Gore, D.: Introduction to Space-Time Wireless Communications. Cambridge University Press (2003)Google Scholar
  5. 5.
    Lee, W.C.Y.: Estimation of channel capacity in Rayleigh fading environment. IEEE Transactions on Vehicular Technology 39(3), 187–189 (1990)CrossRefGoogle Scholar
  6. 6.
    Mohammadi, A., Kumar, S.: Characterization of Adaptive Modulators in Fixed Wireless ATM Networks. IEEE/KICS Journal of Communications and Networks 6(2), 123–132 (2004)Google Scholar
  7. 7.
    Tsoulos, G.: MIMO System Technology for Wireless Communications. CRC Press (2006)Google Scholar
  8. 8.
    Gesbert, D., Shafi, M., Shiu, D., Smith, P.J., Naguib, A.: From Theory to Practice: An Overview of MIMO Space–Time Coded Wireless Systems. IEEE Journal on Selected Areas in Communications 21(3), 281–302 (2003)CrossRefGoogle Scholar
  9. 9.
    Zheng, L., Tse, D.N.C.: Diversity and multiplexing: a fundamental tradeoff in multiple antenna channels. IEEE Transactions on Information Theory 49, 1073–1096 (2003)zbMATHCrossRefGoogle Scholar
  10. 10.
    Alamouti, S.M.: A simple transmit diversity technique for wireless communications. IEEE Journal on Selected Areas in Communications 16(10), 1451–1458 (1998)CrossRefGoogle Scholar
  11. 11.
    Ebrahimzad, H., Mohammadi, A.: On Diversity-Multiplexing Tradeoff in MIMO channel at Finite SNR. IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences E93-A(11), 2057–2064 (2010)CrossRefGoogle Scholar
  12. 12.
    Tarokh, V., Seshadri, N., Calderbank, A.R.: Space-time Codes for High Data Rate Wireless Communication: Performance Criterion and Code Construction. IEEE Transactions on Information Theory 44(2), 744–765 (1998)MathSciNetzbMATHCrossRefGoogle Scholar
  13. 13.
    Gershman, A.B., Sidiropoulos, N.D.: Space-Time Processing for MIMO Communications. Wiley (2005)Google Scholar
  14. 14.
    Ebrahimzad, H., Mohammadi, A.: Diversity-Multiplexing Tradeoff in MIMO Systems with Finite SNR. In: European Conference on Wireless Technology, Munich, pp. 146–149 (October 2007)Google Scholar
  15. 15.
    Papoulis, A., Pillai, S.U.: Random Variable Variables and Stochastic Process, 4th edn. McGraw Hill (2002)Google Scholar
  16. 16.
    Almers, P., Bonek, E., Burr, A., Czink, N., Debbah, M., Degli-Esposti, V., Hofstetter, H., Kyosti, P., Laurenson, D., Matz, G., Molisch, A.F., Oestges, C., Ozcelik, H.: Survey of Channel and Radio Propagation Models for Wireless MIMO Systems. EURASIP Journal on Wireless Communications and Networking 2007, article ID 19070, 19 pages (2007)Google Scholar
  17. 17.
    Saleh, A.M., Valenzuela, R.A.: A statistical model for indoor multipath propagation. Journal on Selected Areas in Communications 5(2), 128–137 (1987)CrossRefGoogle Scholar
  18. 18.
    Rappaport, T.S.: Wireless Communications: Principles and Practice, 2nd edn. Prentice Hall (2002)Google Scholar
  19. 19.
    Wallace, J.W., Jensen, M.A.: Modeling the indoor MIMO wireless channel. IEEE Transactions on Antennas and Propagation 50(5), 591–599 (2002)CrossRefGoogle Scholar
  20. 20.
    Baum, D.S., Gore, D.A., Nabar, R.U., Panchanathan, S., Hari, K.V.S., Erceg, V., Paulraj, A.J.: Measurement and characterization of broadband MIMO fixed wireless channels at 2.5 GHz. In: Proceedings of the International Conference on Personal Wireless Communications (ICPWC 2000), India (December 2000)Google Scholar
  21. 21.
    Erceg, V., et al.: IEEE p802.16 – channel models for fixed wireless applications (ieee802.16.3c-01/29r4) (2001)Google Scholar
  22. 22.
    Correia, L.M.: COST 259 – Wireless flexible personalized communications. Wiley, London (2001)Google Scholar
  23. 23.
    Correia, L.M.: COST 273 – Towards mobile broadband multimedia networks. Elsevier, London (2006)Google Scholar
  24. 24.
    IEEE P802.16 e /D12, IEEE Standard for Local and metropolitan area networks Part 16: Air Interface for Fixed and Mobile Broadband Wireless Access Systems Amendment for Physical and Medium Access Control Layers for Combined Fixed and Mobile Operation in Licensed Bands (October 2005)Google Scholar
  25. 25.
    Flaviis, F.D., Jofre, L., Romeu, J., Grau, A.: Multiantenna Systems for MIMO Communications. Morgan & Craypool Publishers (2008)Google Scholar

Copyright information

© Springer-Verlag GmbH Berlin Heidelberg 2012

Authors and Affiliations

  1. 1.Electrical Engineering DepartmentAmirkabir UniversityTehranIran
  2. 2.Electrical and Computer EngineeringUniversity of CalgaryCalgaryCanada

Personalised recommendations