MIMO-OFDM Channel Estimation with Minimum Differential Feedback for Time-Correlated Rayleigh Block-Fading Channels

  IJPTT-book-cover
 
International Journal of P2P Network Trends and Technology (IJPTT)          
 
© 2014 by IJPTT Journal
Volume - 4 Issue - 5
Year of Publication : 2014
Authors : Rasala Ashok , M. Shiva Prasad , M. Shashidhar

MLA

Rasala Ashok , M. Shiva Prasad , M. Shashidhar ."MIMO-OFDM Channel Estimation with Minimum Differential Feedback for Time-Correlated Rayleigh Block-Fading Channels". International Journal of P2P Network Trends and Technology (IJPTT), V4(5):17-21 Sep - Oct 2014, ISSN:2249-2615, www.ijpttjournal.org, Published by Seventh Sense Research Group.

Abstract

In Multi-Input Multi-Output (MIMO) based cognitive radio (CR) systems, with the increasing demand for data rate and reliability in Wireless communicationsand devices, several issues become very important like bandwidth efficiency, quality of service and radio coverage. We first derive the closed-form expression of the minimum differential feedback rate to achieve the maximum erdodic capacity in the presence of channel estimation errors and quantization distortion at the receiver. With the feedback-channel transmission rate constraint, in the periodic feedback system, we further investigate the relationship of the ergodic capacity and the differential feedback interval, First formulate the pilot design as a new optimization problem. Instead ofminimizing the mean-square error (MSE) of the least-squares (LS) channel estimator, we minimize an upper bound which isrelated to this MSE. We then propose an efficient scheme tosolve the optimization problem. This reliability is in the context of the channel estimationin our case. With the MIMO concept we improve the bitrate and BER of theoverall system.Simulation results show that thepilot index sequences obtained by the proposed method exhibitsignificantly better performance than those obtained by existing pilot design methods.

References

[1] D. J. Love, R. W. Heath, V. K. N. Lau, etc. ”An Overview of limited feedback in wireless Communication Systems”, IEEE Journal on Selected Areas in Communications, vol. 26, no. 8, pp. 1341–1365, Oct. 2008.
[2] D. J. Love, R. W. Heath. Jr, W. Santipach, M. L. Honing, ”What is the value of feedback for mimo channels? ” IEEECommunications Magazine, vol. 42, no. 10, pp. 54–59, Oct. 2004.
[3] W. C. Jakes, ”Microwave mobile communications,” New York: Wiley, 1974.
[4] K. Huang, B. Mondal, R. W. Heath. Jr, J. G. Andrews, ”Markov models for limited feedback MIMO systems,” in IEEE Proc. ICASSP. 2006, Toulouse, France, May 2006.
[5] T. Eriksson, and T. Ottosson, ”Compression of feedback For adaptive transmission and scheduling”, in IEEE Proceedings, pp. 2314–2321, Dec. 2007.
[6] F. C. C., “Spectrum policy task force,” Rep. ET Docket, vol. no. 02-135,November 2002.
[7] J. Mitola III and G. Q. Maguire, “Cognitive radio: making softwareradios more personal,” IEEE Personal Commun., vol. 6, no. 4, pp. 13-18, Sep. 1999.
[8] H. A. Mahmoud, T. Yucek, and H. Arslan, “OFDM for cognitive radio:merits and challenges,” IEEE Wireless Commun., pp. 6-14, Apr. 2009.
[9] B. Farhang-Boroujeny and R. Kempter, “Multicarrier communicationtechniques for spectrum sensing and communication in cognitive radios,”IEEE Commun. Mag., pp. 80-85, Apr. 2008.
[10] S. Haykin, “Cognitive radio: brain-empowered wireless communications,”IEEE J. Sel. Areas Commun., vol. 23, no. 2, Feb. 2005.
[11] R. Negi and J. Cioffi, “Pilot tone selection for channel estimation in amobile OFDM system,” IEEE Trans. Consumer Electron., vol. 44, pp.1112-1128, Aug. 1998.
[12] J. Liu, S. Feng, and H. Wang, “Comb-type pilot aided channel estimationin non-contiguous OFDM systems for cognitive radio,” in Proc.IEEE Int. Conf. on Wireless Communications, Networking and MobileComputing (WiCom), Beijing, China, 2009, pp. 1-4.
[13] I. Rashad, I. Budiarjo, and H. Nikookar, “Efficient pilot pattern forOFDM-based cognitive radio channel estimation–part 1,” in Proc. 14thIEEE Symp. onCommun. and Vehicular Technology in the Benelux,2007.
[14] I. Budiarjo, I. Rashad, and H. Nikookar, “Efficient pilot pattern forOFDM-based cognitive radio channel estimation–part 2,” in Proc. 14thIEEE Symp. onCommun. and Vehicular Technology in the Benelux,2007.
[15] T. M. Duman and A. Ghrayeb, Coding for MIMO communication Systems.west Sussex PO 19 8SQ, England: John Wiley and Sons, Ltd, 2007.
[16] An Efficient Pilot Design Method for OFDM-Based Cognitive Radio Systems Die Hu, Lianghua He, and Xiaodong Wang, Fellow, ieee transactions on wireless communications, accepted for publication

Keywords
Channel state information, MIMO, pilot design, channel estimation, Rayleigh block-fading channels.