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Subspace based estimation of the signal to interference ratio for TDMA cellular systems

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Abstract

The Signal‐to‐Interference Ratio (SIR) has been highlighted in the literature to be a most efficient criterion for several methods aiming at reducing the effects of cochannel interference, e.g., diversity reception, dynamic channel allocation and power control. In this paper we address the problem of how to obtain fast and accurate measurements of this parameter in a practical context. We develop a general SIR estimation technique for narrow‐band cellular systems that is based on a signal subspace approach using the sample covariance matrix of the received signal. Simulation results using the frame structure in the GSM system show that the SIR can be estimated to within an error of 0.3 dB after only 200 ms, or within an error of 0.1 dB after only 0.6 seconds.

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References

  1. A.H. Abdallah and Y.H. Hu, Parallel VLSI computing array implementation for signal subspace updating algorithm, IEEE Transactions on ASSP 37 (May 1989) 742‐748.

    Article  Google Scholar 

  2. M.D. Austin and G.L. Stüber, In-service signal quality estimation for TDMA cellular systems, Wireless Personal Communications 2(3) (1995) 245‐254.

    Article  Google Scholar 

  3. R. Beck and H. Panzer, Strategies for handover and dynamic channel allocation in micro-cellular mobile radio cellular systems, in: Proc. IEEE 39th Vehicular Technology Conference, San Francisco, CA (May 1989) pp. 742‐748.

  4. A.L. Brandäo, L.B. Lopez and D.C. McLernon, Cochannel interference estimation for M-ary PSK modulated signals, Wireless Personal Communications 1(1) (1994) 23‐32.

    Article  Google Scholar 

  5. A.L. Brandäo, L.B. Lopez and D.C. McLernon, Quality assessment for pre-detection diversity switching, in: Proc. PIMRC' 95, Toronto, Canada (September 1995) pp. 577‐581.

  6. G.J. Foschini and Z. Miljanic, A simple distributed autonomous power control algorithm and its convergence, IEEE Transactions on Vehicular Technology 42(4) (November 1993) 641‐646.

    Article  Google Scholar 

  7. G.H. Golub and C.F. Van Loan, Matrix Computations (Johns Hopkins University Press, Baltimore, MD, 2nd ed., 1989).

    MATH  Google Scholar 

  8. S.A. Grandhi, J. Zander and R. Yates, Constrained power control, Wireless Personal Communications 1(4) (1995) 257‐270.

    Article  Google Scholar 

  9. M. Gudmundson, Correlation model for shadow fading in mobile radio systems, Electronic Letters 27(23) (November 1991) 2145‐ 2146.

    Article  Google Scholar 

  10. W. Jakes, Microwave Mobile Communications (Wiley, New York, 1974).

    Google Scholar 

  11. I. Karasalo, Estimating the covariance matrix by signal subspace averaging, IEEE Transactions on ASSP 34(1) (February 1986) 8‐ 12.

    Article  MathSciNet  Google Scholar 

  12. S. Kozono, Co-channel interference measurement method for mobile communication, IEEE Transactions on Vehicular Technology 36 (1987) 7‐13.

    Article  Google Scholar 

  13. J. Proakis, Digital Communications (McGraw-Hill, 2nd ed., 1989).

  14. M. Wax and T. Kailath, Detection of signals by information theoretic criteria, IEEE Transactions on ASSP 33(2) (April 1985) 387‐392.

    Article  MathSciNet  Google Scholar 

  15. G. Xu and T. Kailath, A fast algorithm for signal subspace decomposition and its performance analysis, in: Proc. ICASSP' 91 Conf. (May 1991) pp. 3069‐3072.

  16. R.D. Yates, A framework for uplink power control in cellular radio systems, IEEE Journal on Selected Areas in Communications 13(7) (September 1995).

  17. S. Yoshida, A. Hirai, G.L. Tan, H. Zhou and T. Takeuchi, In-service monitoring of multipath delay-spread and C/I for QPSK signal, in: Proc. IEEE 42nd Vehicular Technology Conference, Denver, CO (April 1992) pp. 592‐595.

  18. J. Zander, Performance of optimum transmitter power control in cellular radio systems, IEEE Transactions on Vehicular Technology 41(1) (February 1992).

  19. J. Zander, Distributed cochannel interference control in cellular radio systems, IEEE Transactions on Vehicular Technology 41(3) (August 1992).

  20. L.C. Zhao, P.R. Krishnaiah and Z.D. Bai, On detection of the number of signals in presence of white noise, Journal of Multivariate Analysis 20(1) (1986) 1‐25.

    Article  MATH  MathSciNet  Google Scholar 

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Authors and Affiliations

  1. Radio Communication Systems, Department of Signals, Sensors and Systems, Royal Institute of Technology, S‐100 44, Stockholm, Sweden

    Michael Andersin

  2. Wireless Information Network Laboratory (WINLAB), Rutgers University, P.O. Box 909, Piscataway, NJ, 08855‐0909, USA

    Narayan B. Mandayam & Roy D. Yates

Authors
  1. Michael Andersin
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  2. Narayan B. Mandayam
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  3. Roy D. Yates
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Andersin, M., Mandayam, N.B. & Yates, R.D. Subspace based estimation of the signal to interference ratio for TDMA cellular systems. Wireless Networks 4, 241–247 (1998). https://doi.org/10.1023/A:1019160207631

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  • DOI: https://doi.org/10.1023/A:1019160207631

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