Skip to main content
SpringerLink
Log in

Estimation of Performance Measures from Simulation

  • Chapter
Simulation of Communication Systems

  • 955 Accesses

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 259.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 329.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 329.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. M. C. Jeruchim and R. J. Wolfe, Estimation of the signal-to-noise ratio (SNR) in communication simulation, in Conference Record, IEEE Global Telecommunications Conference (Globecom), Dallas, Texas (November 1989).

    Google Scholar 

  2. W. H. Tranter and M. D. Turner, Signal-to-noise ratio estimation in digital computer simulation of low-pass and bandpass systems with applications to analog and digital communications, Final Report—Vol. III, Contract NAS 9-14848, University of Missouri-Rolla Technical Report CSR-77-6 (July 1977).

    Google Scholar 

  3. M. D. Turner, W. H. Tranter, and T. W. Eggleston, The estimation of signal-to-noise ratios in digital computer simulation of low-pass and bandpass systems, presented at 1977 IEEE Midcon Conference (November 1977).

    Google Scholar 

  4. N. L. Johnson and S. Kotz, Continuous Univariate Distributions, Vol. 2, Houghton-Mifflin, Boston (1970).

    MATH  Google Scholar 

  5. R. M. Gagliardi and C. M. Thomas, PCM data reliability monitoring through estimation of signal-to-noise ratio, IEEE Trans. Commun. Tech. COM-16(3), 479–486 (1968).

    Google Scholar 

  6. A. Papoulis, Signal Analysis, McGraw-Hill, New York (1977).

    MATH  Google Scholar 

  7. J. P. C. Kleijnen, Statistical Techniques in Simulation, Part I, Dekker, New York (1974).

    MATH  Google Scholar 

  8. A. E. Newcombe and S. Pasupathy, Error rate monitoring for digital communications, Proc. IEEE 70(8), 805–828 (1982).

    Google Scholar 

  9. J. B. Scholz, Error performance monitoring of digital communications systems, Aust. Telecomm. Res. J. 25(2), 1–26 (1991).

    Google Scholar 

  10. J. B. Scholz and B. R. Davis, Error probability estimator structures based on analysis of the receiver decision variable, IEEE Trans. Commun. 43(8), 2311–2315 (1995).

    Article  Google Scholar 

  11. N. Celandroni, E. Ferro, and F. Potorti, Quality estimation of PSK modulated signals, IEEE Commun. Mag. 35(7), 50–55 (1997).

    Article  Google Scholar 

  12. J. M. Hammersley and D. C. Handscomb, Monte Carlo Methods, Chapman and Hall, New York (1964).

    MATH  Google Scholar 

  13. M. Fisz, Probability and Mathematical Statistics, 3rd ed., Wiley, New York (1963).

    MATH  Google Scholar 

  14. A. M. Mood, Introduction to the Theory of Statistics, McGraw-Hill, New York (1950).

    MATH  Google Scholar 

  15. V. K. Rohatgi, Statistical Inference, Wiley, New York (1984).

    MATH  Google Scholar 

  16. H. Cramer, Mathematical Methods of Statistics, Princeton University Press, Princeton, New Jersey (1946).

    MATH  Google Scholar 

  17. M. Abramowitz and I. A. Stegun, Handbook of Mathematical Functions with Formulas, Graphs, and Mathematical Tables, U.S. Department of Commerce, National Bureau of Standards, Washington, D.C. (1964).

    MATH  Google Scholar 

  18. E. S. Pearson and H. O. Hartley, Biometrika Tables for Statisticians, Vol. I, Cambridge University Press, Cambridge (1954).

    MATH  Google Scholar 

  19. M. C. Jeruchim, Techniques for estimating the bit error rate in the simulation of digital communication systems, IEEE J. Selec. Areas Commun. SAC-2(1), 153–170 (1984).

    Google Scholar 

  20. B. R. Davis, The effect of correlation on probability of error estimates in Monte Carlo simulations, J. Elect Electron. Eng. Aust. 8(4), 222–230 (1988).

    Google Scholar 

  21. W. Turin, Digital Transmission Systems: Performance Analysis and Modeling, McGraw-Hill, New York (1998).

    Google Scholar 

  22. M. D. Knowles and A. I. Drukarev, Bit error rate estimation for channels with memory, IEEE Trans. Commun. 36(6), 767–769 (1988).

    Article  Google Scholar 

  23. M. Kendall and A. Stuart, The Advanced Theory of Statistics, Vol. 2, 4th ed., Charles Griffin, London (1979).

    MATH  Google Scholar 

  24. L. N. Kanal and A. R. K. Sastry, Models for channels with memory and their applications to error control, Proc. IEEE 66(7), 724–744 (1978).

    Article  MathSciNet  Google Scholar 

  25. M. Zorzi, Outage and error events in bursty channels, IEEE Trans. Commun. 46(3), 349–356 (1998).

    Article  Google Scholar 

  26. P. M. Crespo, R. M. Pelz, J. P. Cosmas, and J. Garcia-Frias, Results of channel profiles for DECT, IEEE Trans. Commun. 44(8), 913–917 (1996).

    Article  Google Scholar 

  27. S. B. Weinstein, Estimation of small probabilities by linearization of the tail of a probability distribution function, IEEE Trans. Commun. Technol. COM-19(6), 1149–1155 (1971).

    Google Scholar 

  28. M. G. Kendall and A. Stuart, The Advanced Theory of Statistics, 3rd ed., Vol. 2, Hafner, New York (1961).

    Google Scholar 

  29. D. J. Gooding, Performance monitoring techniques for digital receivers based on extrapolation of error rate, IEEE Trans. Commun. Technol. COM-16(3), 380–387 (1968).

    Google Scholar 

  30. P. Balaban, Statistical evaluation of the error rate of the fiberguide repeater using importance sampling, Bell Syst. Tech. J. 55(6), 745–766 (1976).

    MathSciNet  Google Scholar 

  31. K. S. Shanmugan and P. Balaban, A modified Monte Carlo simulation technique for the evaluation of error rate in digital communication systems, IEEE Trans. Commun. 28(11), 1916–1924 (1980).

    Google Scholar 

  32. B. R. Davis, An improved importance sampling method for digital communication system simulations, IEEE Trans. Commun. COM-34(7), 715–719 (1986).

    Google Scholar 

  33. P. M. Hahn and M. C. Jeruchim, Developments in the theory and application of importance sampling, IEEE Trans. Commun. COM-35(7), 706–714 (1987).

    Google Scholar 

  34. D. Lu and K. Yao, Improved importance sampling technique for efficient simulation of digital communication systems, IEEE J. Select. Areas Commun. 6(1), 67–75 (1988).

    Article  Google Scholar 

  35. M. C. Jeruchim, P. M. Hahn, K. P. Smyntek, and R. T. Ray, An experimental investigation of conventional and efficient importance sampling, IEEE Trans. Commun. 37(6), 578–587 (1989).

    Article  Google Scholar 

  36. J. S. Sadowsky and J. A. Bucklew, On large deviations theory and asymptotically efficient Monte Carlo estimation, IEEE Trans. Inform. Theory 36(3), 579–588 (1990).

    Article  MathSciNet  MATH  Google Scholar 

  37. R. J. Wolfe, M. C. Jeruchim, and P. M. Hahn, On optimum and suboptimum biasing procedued for importance sampling in communication simulation, IEEE Trans. Commun. 38(5), 639–647 (1990).

    Article  Google Scholar 

  38. J. S. Sadowsky, A new method for Viterbi decoder simulation using importance sampling, IEEE Trans. Commun. 38(9), 1341–1351 (1990).

    Article  Google Scholar 

  39. J. S. Sadowsky and R. K. Bahr, Direct-sequence spread spectrum multiple access communication with random signature sequences: A large deviation analysis, IEEE Trans. Inform. Theory 37(3), 514–527 (1991).

    Article  Google Scholar 

  40. K. Ben Letaief and J. S. Sadowsky, Computing bit-error probabilities for avalanche photodiode receivers by large deviations theory, IEEE Trans. Inform. Theory 38(3), 514–527 (1992).

    Google Scholar 

  41. H.-J. Schlebusch, On the asymptotic efficiency of importance sampling techniques, IEEE Trans. Inform. Theory 39(2), 710–715 (1993).

    Article  MATH  Google Scholar 

  42. J.-C. Chen, D. Lu, J. S. Sadowsky, and K. Yao, On importance sampling in digital communications—Part I: Fundamentals, IEEE J. Select. Areas Commun. 11(3), 286–299 (1993).

    Google Scholar 

  43. J.-C. Chen and J. S. Sadowsky, On importance sampling in digital communications—Part II: Trellis-coded modulation, IEEE J. Select. Areas Commun. 11(3), 300–308 (1993).

    Google Scholar 

  44. W. A. Al-Qaq, M. Devetsikiotis, and J. K. Townsend, Importance sampling methodologies for simulation of communication systems with time-varying channels and adaptive equalizers, IEEE J. Select. Areas Commun. 11(3), 317–327 (1993).

    Article  Google Scholar 

  45. M. Devetsikiotis and J. K. Townsend, An algorithmic approach to the optimization of importance sampling parameters in digital communication simulation, IEEE Trans. Commun. 41(10), 1464–1473 (1993).

    Article  MATH  Google Scholar 

  46. P. J. Smith, M. Shafi, and H. Gao, Quick simulation: A review of importance sampling techniques in communications systems, IEEE J. Select. Areas Commun. 15(4), 597–613 (1997).

    Article  Google Scholar 

  47. J. A. Bucklew, Large Deviations Techniques in Decision, Simulation, and Estimation, Wiley, New York (1990).

    Google Scholar 

  48. A. Schwartz and A. Weiss, Large Deviations for Performance Analysis: Queues, Communications, and Computing, Chapman & Hall, London (1995).

    Google Scholar 

  49. W. A. Al-Qaq, M. Devetsikiotis, and J. K. Townsend, Stochastic gradient optimization of importance sampling for the efficient simulation of digital communication systems, IEEE Trans. Commun. 43(12), 2975–2985 (1995).

    Article  Google Scholar 

  50. W. A. Al-Qaq and J. K. Townsend, A stochastic importance sampling methodology for the efficient simulation of adaptive systems in frequency nonselective Rayleigh fading, IEEE J. Select. Areas Commun. 15(4), 614–625 (1997).

    Article  Google Scholar 

  51. Z. Haraszti and J. K. Townsend, The theory of direct probability redistribution and its application to rare event simulation, in Proc. International Conference on Communications ICC’98, IEEE, Piscataway, New Jersey (1998).

    Google Scholar 

  52. J. K. Townsend, Z. Haraszti, J. A. Freebersyser, and M. Devetsikiotis, Simulation of rare events in communications networks, IEEE Commun. Mag. 36(8), 36–41 (1998).

    Article  Google Scholar 

  53. M. Villen-Altamirano et al., Enhancement of the accelerated simulation method RESTART by considering multiple thresholds, in Proc 14th International Teletraffic Congress, ITC 14, Juan-les-Pains, France (1994), Vol, 1a, pp. 797–810.

    Google Scholar 

  54. P. Shahabuddin, P. Glasserman, and P. Heidelberger, Splitting for rare event simulation: Analysis of simple cases. In 1996 Winter Simulation Conference, Coronado, California (1996), pp. 302–306.

    Google Scholar 

  55. V K. Prabhu, Error rate considerations for digital phase-modulation systems, IEEE Trans. Commun. Technol. COM-17(1), 33–42, (1969).

    Google Scholar 

  56. I. Korn, Digital Communications, Van Nostrand Reinhold, New York (1985).

    MATH  Google Scholar 

  57. V K. Prabhu, Error rate considerations for coherent phase-shift keyed systems with co-channel interference, Bell Syst. Tech. J. 48(3), 743–767 (1969).

    MATH  Google Scholar 

  58. M. C. Jeruchim and F. E. Lilley, Spacing limitations of geostationary satellites using multilevel coherent PSK signals, IEEE Trans. Commun. COM-20(5), 1021–1026 (1972).

    Google Scholar 

  59. M. I. Irshid and I. S. Salous, Bit error probability for coherent M-ary PSK systems, IEEE Trans. Commun. 39(3), 349–352 (1991).

    Article  Google Scholar 

  60. M. Vanderaar, J. Budinger, and P. Wagner, Least reliable bits coding (LRBC) for high data rate satellite communications, in AIAA 14th International Communications Satellite Systems Conference, Washington, D.C. (1992) pp. 507–514.

    Google Scholar 

  61. H. L. Berger and T. J. Kolze, Bit error rate performance of coded 8PSK, in AIAA 16th International Communications Satellite Systems Conference, Washington, D.C. (1996).

    Google Scholar 

  62. D. J. Torrieri, The information-bit error rate for block codes, IEEE Trans. Commun. COM-32(4), 474–476 (1984).

    Google Scholar 

  63. A. J. Viterbi, Convolutional codes and their performance in communications systems, IEEE Trans. Commun. Technol. COM-19(5), 751–772 (1971).

    MathSciNet  Google Scholar 

  64. A. J. Viterbi and J. K. Omura, Principles of Digital Communications and Coding, McGraw-Hill, New York (1979).

    Google Scholar 

  65. M. C. Jeruchim, On the coding gain for degraded channels, IEEE Trans. Commun. COM-34(5), 492–496 (1986).

    Google Scholar 

  66. J. R. Yee and E. J. Weldon, Evaluation of the performance of error-correcting codes on a Gilbert channel, IEEE Trans. Commun. 43(8), 2316–2323 (1995).

    Article  MATH  Google Scholar 

  67. M. Zorzi and R. R. Rao, On the statistics of block errors in bursty channels, IEEE Trans. Commun. 45(6), 651–659 (1997).

    Article  Google Scholar 

  68. A. Seyoum and N. C. Beaulieu, Semianalytical simulation for estimation of block-error rates on fading channels, IEEE Trans. Commun. 46(7), 916–920 (1998).

    Article  Google Scholar 

  69. M. Pent, L. LoPresti, G. D’Aria, and G. DeLuca, Semianalytic BER estimation by simulation for nonlinear bandpass channels, IEEE J. Select. Areas Commun. 6(1), 34–41 (1988).

    Article  Google Scholar 

  70. M. L. Steinberger, P. Balaban, and K. S. Shanmugan, On the effects of uplink noise, in Conference Record: International Conference on Communications (ICC’ 81), IEEE, New York (1981).

    Google Scholar 

Download references

Rights and permissions

Reprints and permissions

Copyright information

© 2002 Kluwer Academic Publishers

About this chapter

Cite this chapter

(2002). Estimation of Performance Measures from Simulation. In: Simulation of Communication Systems. Information Technology: Transmission, Processing, and Storage. Springer, Boston, MA. https://doi.org/10.1007/0-306-46971-5_11

Download citation

  • DOI: https://doi.org/10.1007/0-306-46971-5_11

  • Publisher Name: Springer, Boston, MA

  • Print ISBN: 978-0-306-46267-2

  • Online ISBN: 978-0-306-46971-8

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics

Search

Navigation