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Proceedings of Czech and Slovak Technical Universities

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June 2003, Volume 12, Number 2

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M. Strupl, P. Sovka [references] [full-text]
Analysis and Simulation of Frost's Beamformer

Sensor arrays are often used for a signal separation from noises using the information about the direction of arrival. The aim of this paper is to analyze Frost's beamformer with respect to the speech preprocessing for the hearing impaired people. The frequency response of the system including the background noise attenuation are derived as functions of the direction of arrival. The derivation supposes a uniform linear array of sensors and plane waves. It is shown that the number of possible configurations can be decreased by using some symmetries. The impact of the used algorithm constraint on the frequency response and subsequently on the directional noise suppression is derived analytically.

  1. WERNER, S., APOLINARIO, J., Laakso, T. MultipleantennaCDMA mobile reception using constrainednormalized adaptive algorithms. In ProceedingsSBT/IEEE International Telecommunications SymposiumITS'98, Sao Paulo (Brazil), 1998, pp. 354-358.
  2. FROST, O. L. An algorithm for linearly constrainedadaptive array processing. In Proceedings of IEEE,1972, vol. 60, no. 8, p. 926-934.
  3. GRIFFITHS, L. J., JIM, C.W. An alternative approachto linearly constrained adaptive beamforming. IEEETransactions on Anntenas and Propagation, 1982, vol.AP-30, p. 27-34.
  4. JOHO, M., MOSCHYTZ, G. S. On the design of thetarget-signal filter in adaptive beamforming. In Proceedingsof IEEE International Symposium on Circuitsand Systems, 1998, vol. 5, p. 166-169.
  5. FAHRANG-BOROUJENY, B. Adaptive Filters, Theoryand Applications. Wiley and Sons, 1996.
  6. STRUPL, M. Analysis and simulation of Frost beamformeralgorithm. Master's thesis, FEE CTU in Prague,2002.
  7. WIDROW, B., DUVALL, K. M., GOOCH, R. P., NEUMAN,W. C. Signal cancelation phenomena in adaptiveantenas: causes and cures. IEEE Transactions on Antenasand Propagation, 1982, vol. AP-30, no. 3, p. 469-478.
  8. GANNOT, S.,BRUSHTEIN, D., WEINSTEIN, E.Beamforming for multichannel speech enhancement.In Proceedings of IWAENC'99, 1999, p. 96-99.
  9. LASENBY, J., FITZGERALD, W. J. A Bayesianapproach to high resolution beamforming. In IEEProceedings-F, Radar and Signal Processing, 1991,vol. 138, no. 6.

P. Kostka, Z. Skvor [references] [full-text]
Microwave-Circuit Optimization with Parallel Enhanced Fast Messy Genetic Algorithm (pefmGA)

Fast messy genetic optimization is found suitable for complex microwave circuit design. Increase in computation speed is achieved using several ordinary computers connected to a network. Calculations are running on background so that computers can be used for other purposes at the same time. Dynamic change of bounds, search space segmentation and gradient incorporation have significantly improved convergence rate. The new method has found global minimum in each run, while classic methods failed for some starting points.

  1. KNJAZEW, D. Application of the Fast Messy Genetic Algorithm to Permutation and Scheduling Problems. Illigal Report 2000022, University of Illinois, May 2000.
  2. SKVOR, Z. CAD pro vf. techniku. Czech Technical University, Prague, 1998.
  3. GOLDBERG, E., DEB, K., KARGUPTA, H., HARIK, G. Rapid, Accurate Optimization of Difficult Problems Using Fast Messy Genetic Algorithms. Illigal Report 93004, University of Illinois, February 1993.
  4. GOLDBERG, D.E. Genetic algorithms in search, optimization and machine learning, Addison Wesley Publishing Company, January 1989.
  5. DEB, K. Binary and Floating-point Function Optimization using Messy Genetic Algorithms. Illigal Report No. 91004.
  6. The search for Extraterrestrial Intelligence,
  7. HOFFMANN, K., SOKOL, V. Analysis of 3D Vertical Strip on Microstrip Line. In Proceedings of the European Microwave Conference, Vol. 2, pp. 569-572, Milan 2002.
  8. PRESS, H.W., TEUKOLSKY, S.A., VETTERLING, W.T., FLANNERY, B.T. Numerical recepies in C. Cambridge University Press, ISBN 0-511-43108-5.

L. Pauk, Z. Skvor [references] [full-text]
FDTD Stability: Critical Time Increment

A new approach suitable for determination of the maximal stable time increment for the Finite-Difference Time-Domain (FDTD) algorithm in common curvilinear coordinates, for general mesh shapes and certain types of boundaries is presented. The maximal time increment corresponds to a characteristic value of a Helmholz equation that is solved by a finite-difference (FD) method. If this method uses exactly the same discretization as the given FDTD method (same mesh, boundary conditions, order of precision etc.), the maximal stable time increment is obtained from the highest characteristic value. The FD system is solved by an iterative method, which uses only slightly altered original FDTD formulae. The Courant condition yields a stable time increment, but in certain cases the maximum increment is slightly greater [2].

  1. TAFLOVE, A. Computational electrodynamics - the finite-difference time-domain method. Artech House, Boston, London, 1995.
  2. PAUK, L., SKVOR, Z. Stability of FDTD in curvilinear coordinates. In: EUROCON 2001. Bratislava, IEEE, 2001, p. 314-317, vol. 2.
  3. DAVIES, J. B. , MUILWYK, A. Numerical solution of uniform hollow waveguides with boundaries of arbitrary shape. Proc. IEE (London), 1966, vol. 133, pp. 277-284.
  4. CHEN, Y., MITRA, R., HARMS, P. Finite-difference time-domain algorithm for solving Maxwell's equations in rotationally symmetric geometries. IEEE Trans. on MTT, 1996, vol. 44, no. 6.
  5. ANGOT, A. Complements de mathematique a l'usage des ingenieurs de l'electrotechnique et des telecommunications. MASSON et Cie (Editions de la Reuve d'Optique, Paris, 1952.
  6. YEE, K. S. Numerical solution of initial boundary value problems involving Maxwell's equations in isotropic media. IEEE Trans. Antenna Propagat,1966, vol. AP-14.
  7. NAVARO, E. A., WU, CH., CHUNG, P.,Y., JOHN L. Some considerations about the Finite Difference Time Domain Method in General Curvilinear Coordinates. IEEE Microwave and Guided Wave Letters, 1994, vol.4, no.12.
  8. XIAO, F., YABE, H. Numerical dispersion relation for FDTD method in general curvilinear coordinates. IEEE Microwave and Guided Wave Letters,1997, vol.7, no.2.

Q. H. Pham, P. Sovka [references] [full-text]
A Family of Coherence-Based Multi-Microphone Speech Enhancement Systems

This contribution addresses the problem of additive noise reduction in speech picked up by a microphone in a noisy environment. Two systems belonging to the family of coherence-based noise cancellers are presented. Suggested systems have the modular structure using 2 or 4 microphones and suppress non-stationary noises in the range of 4 to 17 dB depending on the chosen structure and noise characteristics. The common properties are acceptable noise suppression, low speech distortion and residual noise.

  1. BOLL, S.F. Suppression of acoustic noise in speech using spectral subtraction. IEEE Trans. on Acoustics, Speech, and Signal Processing, 1979, vol.ASSP-27, no.2, p. 113-120.
  2. POLLAK, P., SOVKA, P. Spectral subtraction and speech/pause detection. Internal research report #R95-1, CTU-Faculty of Electrical Engineering, Prague, 1995.
  3. DAVIDEK, V., SOVKA, P., SIKA, J. Real-time implementation of spectral subtraction algorithm for suppression of acoustic noise in speech. In Proceedings of the 4th European Conference on Speech Communication and Technology, EUROSPEECH '95, Madrid, pp. 141-144, September 1995.
  4. VASEGHI, S.V: Advaced signal processing and digital noise reduction. Wiley Teubner, New York, 1997.
  5. KANG, G.S., FRANSEN L.J. Quality improvement of LPC-processed noisy speech by using spectral subtraction. IEEE Trans. on Acoustics, Speech and Signal Processing, 1977, vol. ASSP-37, no.6, pp. 939-942.
  6. LIMM,J.S.: Speech enhancement. Prentice-Hall, New Jersey, 1983.
  7. BEROUTI, M., SCHWARTZ, R., MAKHOUL, J. Enhancement of speech corrupted by acoustic noise. In Proc. of IEEE Conf. on Acoustics, Speech and Signal Processing, 1979, pp. 208-211.
  8. CAPPE, O. Elimination of the musical noise phenomenon with the Ephraim and Malah noise suppressor. IEEE, 1994, pp.345-349.
  9. DORBECKER, M.: Speech enhancement using small microphone arrays with optimized directivity. IWAENC 97, 1997, pp. 100-103.
  10. MASA, P. Mereni zpozdeni mezi signaly. Doktorska disertacni prace, FEL CVUT, Praha, 2002.
  11. SIMMER, K. U., KUCZYNSKI, P., WASILJEFF, A. Time delay compensation for adaptive multi-channel speech enhancement systems. In Proceedings URSI ISSSE, Paris, 1992.
  12. PHAM, Q. H. Optimization and Implementation of Multi-channel Speech Enhancement Methods. Ph.D. thesis, FEE-CTU in Prague, 2002.
  13. BENDAT, J., S., PIERSOL, A. Engineering applications of correlation and spectral analysis. John Wiley & Sons, Inc., New York, 1980.
  14. BOUQUIN, R., L. Enhancement of noisy speech signals. Application to mobile radio communication. Speech Communication, 1996, vol. 18, pp. 3-19.
  15. MAHMOUDI, D., DRYGAJLO, A. Combined Wiener and coherence filtering in wavelet domain for microphone array speech enhancement. In Proc. Of Int. Conf. On Acoustics and Speech Processing ICAASSP'98, Seatle 1998, pp. 385-388.
  16. RODRIGUEZ, G., J., at al. Coherence-based sub-band decomposition for robust speech and speaker recognition in noisy and reverberant rooms. In Proc. Of the ASA Int. Conf. On Acoustics ICA'01, Roma 2001.
  17. DORBECKER, M., ERNST, S. Combination of two-channel spectral subtraction and adaptive Wiener post filtering for noise reduction and deverberation. IWAENC 97, 1997.
  18. MEYER, J., SIMMER, K. U., KAMMEYER, K. D. Comparison of one- and two-channel noise estimation techniques. IWAENC 97, 1997.
  19. EPHRAIM, Y., MALAH, D. Speech enhancement using a minimum mean-square error short-time spectral amplitude estimator. IEEE Trans. on Acoustics, Speech and Signal Processing, 1984, vol. ASSP-32, no. 6, p.1109-1121.
  20. AKBARI, A. A., BOUQUIN, R. L. J., BOUQUIN, G. Speech enhancement using a Wiener filtering under signal presence uncertainty. EUSIPCO 96, Trieste, September 1996.
  21. SOVKA, P., POLLAK, P. The Study of Speech/Pause Detectors for Speech Enhancements Methods. In Proceedings of the 4th European Conference on Speech Communication and Technology - EUROSPEECH'95, Madrid 1995, pp.1575-1578.
  22. MARZINZIK, M., KOLLMEIER, B. Speech pause detection for noise spectrum estimation by tracking power envelope dynamics. IEEE trans. On Speech and Audio Processing, 2002, vol.10, no.2, pp. 109-118.

B. Taha Ahmed, M. Calvo Ramon, L. de Haro Ariet [references] [full-text]
FDSS Downlink Capacity in Urban Zone Near Digital Video Broadcasting Installations

The FDSS macrocell downlink capacity is evaluated for macrocells that operate at the same frequency of the Digital TV station (DTV) and that are nearby the DTV installations. It has been founded that the cell capacity is not affected when the distance between the DTV installations and the macrocell is more than 25 km. For lower distance, the effect is high and the downlink vanishes at a distance less than 2.1 km.

  1. KALEH, G. Frequency Diversity Spread Spectrum Communications to Counter Bandlimited Gaussian Interference. IEEE Transactions on Communications. 1996, vol. 44, no. 7, p. 886 - 893.
  2. ETS 300 744. Digital Video Broadcasting. March 1997.
  3. CALVO-RAMON, M. Third Generation IMT-2000 (UMTS) Mobile Communication Systems. Fundacion Airtel Vodafone, 2002. In Spanish.
  4. HOLMA, H., TOSKLA, A. WCDMA for UMTS. New York: John Wiley and Sons, 2000.
  5. LEE, J. S., MILLER, L. E. CDMA Systems Engineering Handbook. London: Artech House, 1998.

B. Taha Ahmed, M. Calvo Ramon, L. de Haro Ariet [references] [full-text]
A New Quasi-Optimum Power Control Scheme for Downlink in W-CDMA Macro Cellular System

The downlink power control problem in W-CDMA is studied using a new proposed model. The downlink cell capacity is given for the old model given by Gejji and our new model. A capacity increase of 16 % for the special case = 0 (no orthogonality between users) and a generalization of the old model in terms of the propagation exponent and orthogonality factor is introduced.

  1. LEE, W. C. Y. Overview of cellular CDMA. IEEE Transactions on Vehicular Technology, 1991, vol. 40, no. 5, p. 291-302.
  2. GILHOUSEN, K. S. et al, WEAVER, L. A., WHEATELY, C. E. On the capacity of a cellular CDMA system. IEEE Transactions on Ve-hicular Technology, 1991, vol. 40, no. 5, p. 303-312.
  3. GEJJI, R. R. Forward-link power control in CDMA cellular systems. IEEE Transactions on Vehicular Technology, 1992, vol. 41, no. 11, p. 532-536.
  4. KIM, J. E., JUNG, H. M., HWANG, S. H., HONG, D. S., KANG, C. E. An analysis of forward link power allocation and user capacity for 3GPP system. IEICE Transactions on Communications, 2002, vol. E85-B, no. 4, p. 835-839.
  5. TAM, W. M., LAU, F. C. M. Analysis of power control and its im-perfections in CDMA cellular systems. IEEE Transactions on Vehi-cular Technology, 1999, vol. 48, no. 9, p. 1706-1717.
  6. CALVO-RAMON, M. 3rd Generation IMT-2000 (UMTS) Mobile Communication Systems. Fundacion Airtel Vodafone, 2002.
  7. HOLMA, H., TOSKLA, A. WCDMA for UMTS. New York: John Wiley and Sons, 2000.

S. Goga, J. Polec, K. Kotuliakova [references] [full-text]
Throughput Analysis of an Adaptation Rule in the HARQ Environment

In this paper we analyze the adaptation rule, which estimates the channel state and switches between hybrid ARQ (automatic-repeat-request) and pure ARQ. Convolutional code was chosen as FEC (forward-error-correction) in hybrid ARQ part and go-back-N ARQ scheme is used in both cases. The adaptation rule is based on counting ACKs and NAKs and its throughput analysis is made.

  1. YAO, Y.D. An Effective Go-Back-N ARQ Scheme for Variable-Error Rate Channels. IEEE Trans. Commun., 1995, vol.43, no.1, pp. 20-23.
  2. KOSUT, P. Analyza priepustnosti adaptivnych Go-Back-N schem. PhD thesis, Slovak University of Technology Bratislava, 2001.
  3. CHOI, S., SHIN, K.G. A Class of Adaptive Hybrid ARQ Schemes for Wireless Links. IEEE Trans. on Vehicular Techn., 2001, vol.50, no.3, pp. 777-790.
  4. WICKER, S. Error Control Systems for Digital Communications and Storage. Prentice Hall, 1995.
  5. POLEC, J., KARLUBIKOVA, T., Stochasticke modely v telekomunikaciach 1. FABER 1999, Bratislava.