Location via proxy:   [ UP ]  
[Report a bug]   [Manage cookies]                
skip to main content
research-article

Error rates of the maximum-likelihood detector for arbitrary constellations: convex/concave behavior and applications

Published: 01 April 2010 Publication History

Abstract

Motivated by a recent surge of interest in convex optimization techniques, convexity/concavity properties of error rates of the maximum likelihood detector operating in the AWGN channel are studied and extended to frequency-flat slow-fading channels. Generic conditions are identified under which the symbol error rate (SER) is convex/concave for arbitrary multi-dimensional constellations. In particular, the SER is convex in SNR for any one- and two-dimensional constellation, and also in higher dimensions at high SNR. Pairwise error probability and bit error rate are shown to be convex at high SNR, for arbitrary constellations and bit mapping. Universal bounds for the SER first and second derivatives are obtained, which hold for arbitrary constellations and are tight for some of them. Applications of the results are discussed, which include optimum power allocation in spatial multiplexing systems, optimum power/time sharing to decrease or increase (jamming problem) error rate, an implication for fading channels ("fading is never good in low dimensions") and optimization of a unitary-precoded OFDM system. For example, the error rate bounds of a unitary-precoded OFDM system with QPSK modulation, which reveal the best and worst precoding, are extended to arbitrary constellations, which may also include coding. The reported results also apply to the interference channel under Gaussian approximation, to the bit error rate when it can be expressed or approximated as a nonnegative linear combination of individual symbol error rates, and to coded systems.

References

[1]
S. Boyd and L. Vandenberghe, Convex Optimization. Cambridge, U.K.: Cambridge University Press, 2004.
[2]
A. Ben-Tal and A. Nemirovski, Lectrures on Modern Convex Optimization. Philadelphia, PA: MPS-SIAM Series on Optimiz., 2001.
[3]
N. Prasad and M. K. Varanasi, "Analysis of decision feedback detection for MIMO Rayleigh-fading channels and the optimization of power and rate allocations," IEEE Trans. Inf. Theory, vol. 50, Jun. 2004.
[4]
J. Choi, "Nulling and cancellation detector for MIMO channels and its application to multistage receiver for coded signals: Performance and optimization," IEEE Trans. Wireless Commun., vol. 5, no. 5, pp. 1207-1216, May 2006.
[5]
V. Kostina and S. Loyka, "On optimum power allocation for the V-BLAST," IEEE Trans. Commun., vol. 56, pp. 999-1012, Jun. 2008.
[6]
V. Kostina and S. Loyka, "Optimum power and rate allocation for coded V-BLAST," in Proc. IEEE Int. Conf. Commun. (ICC-09), Dresden, Germany, Jun. 2009.
[7]
M. Azizoglu, "Convexity properties in binary detection problems," IEEE Trans. Inf. Theory, vol. 42, pp. 1316-1321, Jul. 1996.
[8]
A. M. Wyglinski, F. Labeau, and P. Kabal, "Bit loading with BER-constraint for multicarrier systems," IEEE Trans. Wireless Commun., vol. 4, no. 4, pp. 1383-1387, Jul. 2005.
[9]
Y.-P. Lin and S.-M. Phoong, "BER minimized OFDM systems with channel independent precoders," IEEE Trans. Signal Process., vol. 51, pp. 2369-2380, Sep. 2003.
[10]
C. C. Yeh and J. R. Barry, "Adaptive minimum BIT-Error rate equalization for binary signaling," IEEE Trans. Commun., vol. 48, no. 7, pp. 1226-1235, Jul. 2000.
[11]
X. Wang, W. S. Lu, and A. Antoniou, "Constrained minimum-BER multiuser detection," IEEE Trans. Signal Process., vol. 48, pp. 2903-2909, Oct. 2000.
[12]
D. P. Palomar, J. M. Cioffi, and M. A. Lagunas, "Joint Tx-Rx beamforming design for multicarrier MIMO channels: A unified framework for convex optimization," IEEE Trans. Signal Process., vol. 51, pp. 2381-2401, Sep. 2003.
[13]
J. G. Proakis, Digital Communications. Boston, MA: McGraw-Hill, 2001.
[14]
M. K. Simon and M.-S. Alouini, Digital Communication over Fading Channels. New York: Wiley, 2005.
[15]
J. M. Wozencraft and I. M. Jacobs, Principles of Communication Engineering. New York: Wiley, 1965.
[16]
J. R. Barry, E. A. Lee, and D. G. Messerschmitt, Digital Communications. Boston, MA: Kluwer Academic, 2004.
[17]
S. Benedetto and E. Biglieri, Principles of Digital Transmission With Wireless Applications. New York: Kluwer Academic, 1999.
[18]
K. Cho and D. Yoon, "On the general BER expression of one- and two-dimensional amplitude modulations," IEEE Trans. Commun., vol. 50, no. 7, pp. 1074-1080, Jul. 2002.
[19]
L. Szczecinski, S. Aissa, C. Gonzalez, and M. Bacic, "Exact evaluation of bit- and symbol-error rates for arbitrary 2-D modulation and nonuniform signaling in AWGN channel," IEEE Trans. Commun., vol. 54, no. 6, pp. 1049-1056, Jun. 2006.
[20]
Z. Wang and G. B. Giannakis, "A simple and general parameterization quantifying performance in fading channels," IEEE Trans. Commun., vol. 51, no. 8, pp. 1389-1398, Aug. 2003.
[21]
S. Verdu, Multiuser Detection. Cambridge, U.K.: Cambridge University Press, 1998.
[22]
T. W. Anderson, An Introduction to Multivariate Analysis, 3rd ed. New York: Wiley, 2003.
[23]
I. S. Gradshteyn and I. M. Ryzhik, Tables of Integrals, Series and Products. San Diego, CA: Academic, 2000.
[24]
P. O. Borjesson and C. E. W. Sundberg, "Simple approximations of the error function Q(x) for communications applications," IEEE Trans. Commun., vol. 27, no. 3, pp. 639-643, Mar. 1979.
[25]
R. T. Rockafellar, Convex Analysis. Princeton, NJ: Princeton Univ. Press, 1970.
[26]
P. Balaban and J. Salz, "Optimum diversity combining and equalization in digital data transmission with applications to cellular mobile radio--Part I: Theoretical considerations," IEEE Trans. Commun., vol. 40, no. 5, pp. 885-894, May 1992.
[27]
J. M. Cioffi et al., "MMSE decision-feedback equalizers and coding--Part I: Equalization results," IEEE Trans. Commun., vol. 43, no. 10, pp. 2582-2594, Oct. 1995.
[28]
J. E. Smee and N. C. Beaulieu, "Error-rate evaluation of linear equalization and decision feedback equalization with error propagation," IEEE Trans. Commun., vol. 46, no. 5, pp. 656-665, May 1998.
[29]
Conti et al., "Log-concavity property of the error probability with application to local bounds for wireless communications," IEEE Trans. Inf. Theory, vol. 55, no. 6, pp. 2766-2775, Jun. 2009.
[30]
J. Lu et al., "M-PSK andM-QAMBER computation using signal-space concepts," IEEE Trans. Commun., vol. 47, no. 2, pp. 181-184, Feb. 1999.
[31]
X. Dong, N. C. Beaulieu, and P. H. Wittke, "Error probabilities of two dimensional M-ary signaling in fading," IEEE Trans. Commun., vol. 47, no. 3, pp. 352-355, Mar. 1999.
[32]
P. K. Vitthaladevuni and M. S. Alouini, "A recursive algorithm for the exact BER computation of generalized hierarchical QAM constellations," IEEE Trans. Inf. Theory, vol. 49, no. 1, pp. 297-307, Jan. 2003.
[33]
J. Lassing et al., "Computation of the exact bit-error rate of coherent M-ary PSK with gray code bit mapping," IEEE Trans. Commun., vol. 51, no. 11, pp. 1758-1760, Nov. 2003.
[34]
L. L. Yang and L. Hanzo, "A recursive algorithm for the error probability evaluation of M-QAM," IEEE Commun. Lett., vol. 4, pp. 304-306, Oct. 2000.
[35]
M. Bagnoli and T. Bergstrom, "Log-concave probability and its applications," Econom. Theory, vol. 26, pp. 445-469, 2005.
[36]
A. Baricz, "A functional inequality for the survival function of the gamma distribution," J. Inequal. Pure and Appl. Math., vol. 9, no. 1, pp. 1-5, 2008.
[37]
G. Taricco and E. Biglieri, "Exact pairwise error probability of space-time codes," IEEE Trans. Inf. Theory, vol. 48, no. 2, pp. 510-513, Feb. 2002.
[38]
Y. C. Jenq, "Does a larger intersymbol interference result in a higher probability of error?," IEEE Trans. Commun., vol. 28, no. 9, pp. 1771-1773, Sep. 1980.
[39]
F. E. Glave, "An upper bound on the probability of error due to intersymbol interference for correlated digital signals," IEEE Trans. Inf. Theory, vol. 18, no. 3, pp. 356-363, May 1972.
[40]
K. Yao and R. M. Tobin, "Moment space upper and lower error bounds for digital systems with intersymbol interference," IEEE Trans. Inf. Theory, vol. 22, no. 1, pp. 65-74, Jan. 1976.
[41]
L. Goldfeld, V. Lyandres, and D. Wulich, "Minimum BER power loading for OFDM in fading channel," IEEE Trans. Commun., vol. 50, no. 11, pp. 1729-1733, Nov. 2002.
[42]
T. M. Cover and J. A. Thomas, Elements of Information Theory. New York: Wiley, 1991.
[43]
D. P. Palomar and Y. Jiang, "MIMO transceiver design via majorization theory," Found. Trends Commun. Inf. Theory, vol. 3, no. 4-5, pp. 331-551, 2006.
[44]
I. Sason and S. Shamai, "Performance analysis of linear codes under maximum-likelihood decoding: A tutorial," Found. Trends Commun. Inf. Theory, vol. 3, no. 1/2, pp. 1-222, 2006.

Cited By

View all
  • (2022)Efficient jamming attack against MIMO transceiverDigital Signal Processing10.1016/j.dsp.2022.103593127:COnline publication date: 1-Jul-2022
  • (2016)Maximization of average number of correctly received symbols over multiple channels in the presence of idle periodsDigital Signal Processing10.1016/j.dsp.2016.03.00954:C(95-118)Online publication date: 1-Jul-2016
  • (undefined)Maximization of correct decision probability via channel switching over Rayleigh fading channels2016 IEEE Wireless Communications and Networking Conference10.1109/WCNC.2016.7564995(1-6)
  1. Error rates of the maximum-likelihood detector for arbitrary constellations: convex/concave behavior and applications

      Recommendations

      Comments

      Information & Contributors

      Information

      Published In

      cover image IEEE Transactions on Information Theory
      IEEE Transactions on Information Theory  Volume 56, Issue 4
      April 2010
      574 pages

      Publisher

      IEEE Press

      Publication History

      Published: 01 April 2010
      Revised: 06 November 2009
      Received: 07 December 2007

      Author Tags

      1. Convexity/concavity
      2. OFDM
      3. convexity/concavity
      4. error rate
      5. jamming
      6. maximum-likelihood detection
      7. optimum transmission

      Qualifiers

      • Research-article

      Contributors

      Other Metrics

      Bibliometrics & Citations

      Bibliometrics

      Article Metrics

      • Downloads (Last 12 months)0
      • Downloads (Last 6 weeks)0
      Reflects downloads up to 20 Jan 2025

      Other Metrics

      Citations

      Cited By

      View all
      • (2022)Efficient jamming attack against MIMO transceiverDigital Signal Processing10.1016/j.dsp.2022.103593127:COnline publication date: 1-Jul-2022
      • (2016)Maximization of average number of correctly received symbols over multiple channels in the presence of idle periodsDigital Signal Processing10.1016/j.dsp.2016.03.00954:C(95-118)Online publication date: 1-Jul-2016
      • (undefined)Maximization of correct decision probability via channel switching over Rayleigh fading channels2016 IEEE Wireless Communications and Networking Conference10.1109/WCNC.2016.7564995(1-6)

      View Options

      View options

      Media

      Figures

      Other

      Tables

      Share

      Share

      Share this Publication link

      Share on social media