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Proceedings of Czech and Slovak Technical Universities

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September 2005, Volume 14, Number 3

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J. Dobes [references] [full-text] [Download Citations]
An Efficient Procedure for the Time-Domain Sensitivity Analysis

Standard tools for CAD have limited modes of the sensitivity analysis: PSPICE only contains a static mode and SPECTRE includes frequency-domain and static modes. However, many RF systems use symmetrical structures for enhancing the circuit properties. For such systems, the static sensitivities are zero on principle and hence the time-domain sensitivity analysis should be used. In the paper, a novel recurrent formula for the time/domain sensitivity analysis is derived which uses by-products of an efficient implicit integration algorithm. As the selected integration algorithm is more flexible than the Gear's one that is ordinary used, the sensitivity analysis is more efficient in comparison with the standard CAD tools. An implementation of the method is demonstrated using the analysis of a low-voltage four-quadrant RF multiplier. Nonstandard temperature sensitivity analyses are also tested in the static and dynamic modes.

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  6. SHEU, B. J., SCHARFETTER, D. L., KO, P. K., JENG, M.-C.BSIM: Berkeley short-channel IGFET model for MOS transistors.IEEE Journal of Solid-State Circuits, 1987, vol. 22, no. 8,p. 558 - 566.
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  9. LIU, W. MOSFET models for SPICE simulation including BSIM3v3and BSIM4. New York: John Wiley & Sons, 2001.
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J. Vcelak, J. Sykora [references] [full-text] [Download Citations]
Extended Transfer Bound Error Analysis for Parametric Channel withContinuous Valued Correlated Random Nuisance Parameter

In this paper, we address the extended use of transfer bound analysis of bit error rate (BER) properties. In conjunction with proper parameter modeling, we offer a method to resolve the problem of transfer bound applicability on a system with random and possibly correlated continuous value nuisance parameters. We introduce a new additional parameter space into the original error space and join them in a product matrix for an extended transfer function evaluation. Example applications with simple trellis code for Rayleigh fading channel and phase synchronization error are investigated to demonstrate the functionality of the proved principle. Computer simulation results are presented for two different codes and various fading scenarios, and comparisons are made among analytical and measured system error performances.

  1. VCELAK, J., SYKORA, J. Extended Transfer Bound Error Analysisin the Presence of Channel Random Nuisance Parameter. In Proc.IEEE Int. Symp. on Personal, Indoor and Mobile Radio Communications(PIMRC). Berlin(Germany), Sep 2005.
  2. VCELAK, J., SYKORA, J. Analytical Error Performance Analysisfor Reduced Complexity Detection of General Trellis Codewith Parametric Uncertainty. COST#273 [CD-ROM], TD-04-132.Gothenburg(Sweden), Jun 2004, p. 1 - 5.
  3. SYKORA, J. Theory of Digital Communication. Lecture notes, CTUFEE Prague. 2001.
  4. ZHANG, W. Finite State System in Mobile Communication. PhDThesis, University of South Australia. 1996.
  5. CHUGG, K., ANASTASOPOULOS, A., CHEN, X. Iterative detection,Adaptivity, Complexity Reduction and Applications. KluwerAcademic Publishers, 2001.
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  7. SCHLEGEL, CH. B., PEREZ, L. C. Trellis and Turbo Coding. JohnWiley & Sons, Inc., 2004.
  8. SIMONS, M., ALOUINI, M. Digital Communication over FadingChannels: A Unified Approach to Performance Analysis. John Wiley& Sons, 2000.
  9. SIMONS, M., ALOUINI, M. A Unified Approach to the PerformanceAnalysis of Digital Communication over Generalized FadingChannels. In IEEE Proceedings. Sep 1998, p. 1860 - 1877.
  10. NASSAR, C. R., SOLEYMANI, M. R. Application of QuantizationTheory to Data Detection in a Presence of Nuisance Parameters.IEEE Trans. on Communication. June 1999, vol. 47, no. 6.
  11. EPHRAIM, Y., MERHAV, N. Hidden Markov Processes. Trans. onInf. Theory. June 2002, vol. IT-48, no. 6, p. 1518 - 1568.
  12. TURIN, W., NOBELEN, R. Hidden Markov Modeling of Flat FadingChannel. IEEE Journal on Sel. Areas in Comm. Dec 1998, vol.16, no. 9, p. 1809 - 1817.
  13. KOMNINAKIS, CH., WESEL, R. D. Joint Iterative Channel Estimationand Decoding in Flat Correlated Rayleigh Fading Channel.Journal on Sel. Areas in Comm. Sep 2001, vol. 19, no. 9, p. 1706 -1717.

M. Knize, J. Sykora [references] [full-text] [Download Citations]
General Framework and Advanced Information Theoretical Results on Eigenmode MIMO Channel Inversion

This paper provides general and deep investigation of adaptation strategies based on the channel inversion policy regarding wide variety of channel modes. Our novel approach to the eigenmode space MIMO channel inversion policy relies on the eigenmode space reduction providing zero transmission outage probability regardless of the instantaneous channel fading realization. Very detailed survey of the features of channel capacity is provided in analytical closed form expressions supported by many particular numerical results (Alamouti scheme is included). The correlated MIMO channel is involved into our treatment as well. We also address the trade-off between the capacity and transmission outage probability. The novel results are developed in the general framework with exhaustive summary of well known SISO and SIMO results.

  1. PROAKIS, J., SHAMAI(SHITZ), S. Fading Channels: Informationtheoreticand Communication Aspects. IEEE Trans. Inform. Theory,1998, vol. 44, no. 6, p. 2619 - 2692.
  2. CAIRE, G., SHAMAI(SHITZ), S. On the Capacity of Some Channelswith Channel State Information. IEEE Trans. on Inform. Theory,1999, vol. 45, no. 6, p. 2007 - 2019.
  3. GOLDSMITH, A. J., VARAIYA, P. P. Capacity of Fading Channelswith Channel Side Information. IEEE Trans. Inform. Theory, 1997,vol. 43, no. 6, p. 1986 - 1992.
  4. CAIRE, G., TARICCO, G., BIGLIERI, E. Optimum Power ControlOver Fading Channels. IEEE Trans. Inform. Theory, 1999, vol. 45,no. 5, p. 1468 - 1489.
  5. ALOUINI, M. S., GOLDSMITH, A. J. Capacity of Rayleigh FadingChannels under Different Adaptive Transmission and Diversity-Combining Techniques. IEEE Trans. Veh. Technol., 1999, vol. 48,no. 4, p. 1165 - 1181.
  6. ALOUINI, M. S., GOLDSMITH, A. J. Adaptive Modulation overNakagami Fading Channels. Kluwer Journal on Wireless Communications,2000, vol. 13, p. 119 - 143.
  7. GOLDSMITH, A. J. The Capacity of Downlink Fading Channelswith Variable Rate and Power. IEEE Trans. Veh. Technol., 1997, vol.46, no. 6, p. 569 - 580.
  8. ALOUINI, M. S. Adaptive and Diversity Techniques for WirelessDigital Communications over Fading Channels. PhD thesis, Departmentof Electrical Engineering, California Institute of Technology,1998.
  9. CHUNG, S. T., GOLDSMITH, A. J. Degrees of Freedom in AdaptiveModulation: A United View. IEEE Trans. Commun., 2001, vol.49, no. 9, p. 1561 - 1571.
  10. GOLDSMITH, A. J., CHUA, S. G. Variable-Rate Variable-PowerMQAM for Fading Channels. IEEE Trans. Commun., 1997, vol. 45,no. 10, p. 1218 - 1230.
  11. HOLM, H. Adaptive Coded Modulation Performance and ChannelEstimation Tools for Flat Fading Channels. PhD thesis, Departmentof Telecommunications, Norwegian University of Science and Technology,2002.
  12. HAUSTEIN, T., von HELMOLT, C., JORSWIECK, E. Performanceof MIMO Systems with Channel Inversion. In IEEE VTC Spring,Birmingham, Alabama, USA, 2002.
  13. EKMAN, T. Prediction of Mobile Radio Channels - Modelling andDesign. PhD thesis, Uppsala University, Sweden, 2002.
  14. BALACHANDRAN, K., KADABA, S. T., NANDA, S. ChannelQuality Estimation and Rate Adaptation for Cellular Mobile Radio.IEEE J. Select. Areas Commun., 1999, vol. 17, no. 7, p. 1244 - 1256.
  15. GOECKEL, D. L. Adaptive Coding for Time-Varying Channels UsingOutdated Fading Estimates. IEEE Trans. Commun., 1999, vol.47, no. 6, p. 844 - 855.
  16. PEEL, C. B., HOCHWALD, B. M., SWINDLEHURST, A. L. AVector-Perturbation Technique for Near-Capacity Multiantenna MultiuserCommunication Part I: Channel Inversion and Regularization.IEEE Trans. Commun., 2005, vol. 53, no. 3, p. 195 - 202.
  17. HOCHWALD, B. M., PEEL, C. B., SWINDLEHURST, A. L. AVector-Perturbation Technique for Near-Capacity Multiantenna MultiuserCommunication Part II: Perturbation. IEEE Trans. Commun.,2005, vol. 53, no. 3, p. 537 - 544.
  18. KNIZE, M. Adaptive Spatial Diversity Digital Communication Systems.Master Thesis, Dept. of Radioelectronics, Faculty of ElectricalEngineering, Czech Technical University in Prague, Czech Republic,2003.
  19. KNIZE, M. Capacity versus Outage Trade-Off Inversion AdaptationBased on Reduced Eigenmode Space for MIMO Flat-FadingRayleigh Channel. In Poster 2005, CTU FEE, Prague, Czech Republic,2005.
  20. KNIZE, M., Sykora, J. Adaptation in MIMO Rayleigh Channel UsingSubspace Total Inversion with Zero Outage Probability. In COST273, TD-04-134, Goethenburg, Sweden, 2004.
  21. KNIZE, M., Sykora, J. Subspace Inversion Symbol Energy Adaptationin MIMO Rayleigh Channel with Zero Outage Probability. InIEEE VTC Fall 2004, Los Angeles, California, USA, 2004.
  22. ALAMOUTI, S. M. A Simple Transmit Diversity Technique forWireless Communications. IEEE J. Select. Areas Commun., 2004,vol. 16, no. 8, p. 1451 - 1458.
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  24. SHAO, J.W., ALOUINI, M. S., GOLDSMITH, A. J. Impact of FadingCorrelation and Unequal Branch Gain on the Capacity of DiversitySystem. In Proc. of IEEE VTC Fall 2004, Houston, Texas, USA,1999.
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  29. SHIN, H., LEE, J. H. Closed-Form Formulas for Ergodic Capacityof MIMO Rayleigh Fading Channels. In Proc. of IEEE InternationConf. on Communications, Seattle, Washington, USA, 2003, p. 2996- 3000.
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V. I. Djigan [references] [full-text] [Download Citations]
RLS Adaptive Filtering Algorithms Based on Parallel Computations

The paper presents a family of the sliding window RLS adaptive filtering algorithms with the regularization of adaptive filter correlation matrix. The algorithms are developed in forms, fitted to the implementation by means of parallel computations. The family includes RLS and fast RLS algorithms based on generalized matrix inversion lemma, fast RLS algorithms based on square root free inverse QR decomposition and linearly constrained RLS algorithms. The considered algorithms are mathematically identical to the appropriate algorithms with sequential computations. The computation procedures of the developed algorithms are presented. The results of the algorithm simulation are presented as well.

  1. SAYED, A. H. Fundamentals of Adaptive Filtering. Hoboken, NJ: John Wiley and Sons, Inc., 2003.
  2. BENESTY, J., HUANG, Y. (Eds.). Adaptive Signal Processing: Applications to Real-World Problems. New York: Springer-Verlag, 2003.
  3. DJIGAN, V. I. Multichannel RLS and fast RLS adaptive filtering algorithms. Successes of Modern Radioelectronics. 2004, no. 11, p. 48 - 77. (in Russian).
  4. PETRICHKOVICH Y. Y., SOLOKHINA, T. V. MULTICORE signal controllers - new Russian family of SoC. In Proceedings of 6-th International Conference on Digital Signal Processing and its Applications. Moscow (Russia), 2004, vol.1, p. 8 - 15. (in Russian).
  5. GAY, S. L. Dynamically regularized fast RLS with application to echo cancellation. In Proceedings of the International Conference on Acoustic Speech and Signal Processing. Atlanta (USA), 1996, p. 957 - 960.
  6. PAPAODYSSEYS, C. A robust, parallelizable, O(m), a posteriori recursive least squares algorithm for efficient adaptive filtering. IEEE Trans. Signal Processing, 1999, vol. 47, no. 9, p. 2552 - 2558.
  7. DJIGAN, V. I. Parallelizable sliding window regularized fast RLS algorithm for multichannel linearly constrained adaptive filtering. In Proceedings of the 10-th International Conference on Radars, Navigation and Communication (RLNC-2004). Voronezh (Russia), 2004, vol. 1, p. 132 - 142. (in Russian).
  8. DJIGAN, V. I. Multichannel fast RLS adaptive filtering algorithm for parallel implementation by means of four processors. In Proceed-ings of Bauman's Moscow State Technical University, 2005, no. 1, p. 83 - 99. (in Russian).
  9. DJIGAN, V. I. On parallel implementation of adaptive filtering algorithms. In Proceedings of the 8-th International Conference on Pattern Recognition and Information Processing (PRIP-2005). Minsk (Belarus), 2005, vol. 1, p. 101 - 104.
  10. DJIGAN, V. I. Fast RLS with parallel computations. In Proceedings of the IEEE 7-th Emerging Technologies Workshop: "Circuits and Systems for 4G Mobile Wireless Communications". S. Petersburg (Russia), 2005, p. 42 - 45.
  11. DJIGAN, V. I. Parallel multichannel fast RLS adaptive filtering algorithm based on inverse QR decomposition. In Proceedings of the Second IASTED International Multi-Conference on ACIT. Novosibirsk (Russia), 2005, vol. SIP, p. 170 - 175.
  12. DJIGAN, V. I. Parallel linearly-constrained recursive least squares for mulitchannel adaptive filtering. In Proceedings of St. Petersburg IEEE Chapters: International Conference "Radio - That Connects Time. 110 Years of Radio Invention". S. Petersburg (Russia), 2005, vol. 2, p. 134 -139.
  13. RESENDE, L. S., ROMANO, J. M. T., BELLANGER, M.G. A fast least-squares algorithm for linearly constrained adaptive filtering. IEEE Trans. Signal Processing, 1996, vol. 44, no. 5, p. 1168 - 1174.
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  19. GLENTIS, G.-O. A. On the duality between the fast transversal and the fast QRD adaptive least squares algorithms. IEEE Trans. Signal Processing. 1999, vol. 47, no. 8, p. 2317 - 2321.
  20. PROUDER, I. K. Fast time-series adaptive-filtering algorithm based on the QRD inverse-updates method. IEE Proceedings: Vision, Im-age and Signal Processing, 1994, vol. 141, no. 5, p. 325 - 333.

J. Sebesta, M. Kasal [references] [full-text] [Download Citations]
Effective DSP Methods of PSK Feedback Timing Synchronization

This paper deals with simplification and improvement of data timing synchronization algorithms. Timing error synchronizers are usually the most complicated subsystems in the demodulator, and limit the DSP technique used for the high-rate application. This article is focused on feedback timing estimators for PSK modulation schemes, and shows modifications of widely used algorithms, that are suitable for the DSP implementation, as well as reach better parameters of the detection process. The methods applied in the evaluation of a timing error detector, which is a crucial part of the synchronizer, are described in the last part.

  1. MENGALI, U., D'ANDREA, A. N. Synchronization Techniques forDigital Receivers. 1st ed. Plenum Press, 1997.
  2. MUELLER, K. H., MUELLER, M. Timing recovery in digital datareceivers. IEEE Transaction on Communication, 1976, vol. 24, no. 5,p. 516 -531.
  3. SEBESTA, J., SEBESTA, J. Universal DSP based system forcommunication with AMSAT experimental satellites. In Proceedingsof the 4th WSEAS International Conference on Applied Informaticsand Communications. Puerto de la Cruz (Spain/Tenerife), 2004, p.162/1 - 162/4.
  4. GARDNER, F. M. Demodulator reference recovery techniquessuited for digital implementation. ESA Final Report, 1988, ESTECContract No. 6847/86/NL/DG.
  5. D'ANDREA, A. N., MENGALI, U., MORELLI, M. Symbol timingestimation with CPM modulation. IEEE Transactions onCommunications, 1996, vol. 44, no. 10, p. 1362 - 1371.
  6. KORN, I., FONSEKA, J. P., XING, S. Optimal binarycommunication with nonequal probabilities. IEEE Transactions onCommunications, 2003, vol. 51, no. 9, p. 1435 - 1438.
  7. MORELANDE, M. R., ZOUBIR, A. M. Detection of phasemodulated signals in additive noise. IEEE Signal Processing Letters,2001, vol. 8, no. 7, p. 199 - 202.
  8. FERTNER, A., SOLVE, C. Symbol-rate timing recovery comprisingthe optimum signal-to-noise ratio in a digital subscriber loop. IEEETransactions on Communications, 1997, vol. 45, no. 8, p. 925 - 927.

J. Valsa [references] [full-text] [Download Citations]
Simulation of "Tsunami Waves" Propagating along Non-Linear Transmission Lines

The paper compares three methods for computer simulation of transients on transmission lines with losses and nonlinear behavior, namely distributed LC model, FDTD (Finite-Difference Time-Domain) method, and a new and very effective Method of Slices. The losses are responsible for attenuation and shape changes of the waves as function of time and distance from the source. Special behavior of the line due to voltage-dependent capacitance of the line is considered in detail. The non-linear nature of the line causes that the higher is the voltage the higher is the velocity of propagation. Then, the waves tend to tilt over so that their top moves faster than their base. As a result "tsunami waves" are created on the line. Fundamental algorithms are presented in Matlab language. Several typical situations are solved as an illustration of individual methods.

  1. SULLIVAN, D., M. Electromagnetic simulation using the FDTDmethod. IEEE Press Series on RF and Microwave Technology, NewYork, 2000.
  2. BENDA, O. Teoreticka elektrotechnika, Teoria vedeni (Theory ofElectrical Engineering - Theory of Transmission Lines, in Slovak).Bratislava: SVST, 1987.
  3. VALSA, J., SEDLACEK, J. Teoreticka elektrotechnika 2 (Theory ofElectrical Engineering 2, in Czech). Brno: VUTIUM University ofTechnology, 2000.
  4. VALSA, J. An attempt to simulate the wave propagation along anon-linear transmission line. In Proc. of the 26th International Conf.on Fundamentals of Electrotechnics and Circuit Theory IC-SPETO2003. Gliwice-Niedzica (Poland), 2003, vol. 2, p. 347-349.
  5. NOVOTNY, K. Mathematical modeling of the solitons in non-linearlumped networks. In Proc. of 10th International Scientific ConferenceRadioelektronika 2000, Bratislava (Slovakia), pp. P-27 - P-28.
  6. VALSA, J. Simulation of a non-linear loss-less infinite transmissionline. In Proc. of 15th International Scientific Conference Radioelektronika,Bratislava (Slovakia), 2004.
  7. VALSA, J., BRANCIK, L. Approximate formulae for numericalinversion of Laplace transforms. International Journal of NumericalModelling: Electronic Networks, Devices and Fields, 1998, vol.11,pp. 153-166.
  8. BRANCIK, L., VALSA, J. A fast computing method of numericalinversion of two-dimensional Laplace transforms using FFT. Signals,Control, Computers Conference SSCC'98, Durban (South Africa),1998, pp. 305-307.
  9. BRANCIK, L. Techniques of Time-Domain Simulation of TransmissionLines Based on Laplace Transformation Methods, Thesis forHabilitation, BUT Brno, 1999.

T. Dostal [references] [full-text] [Download Citations]
All-Pass Filters in Current Mode

Analogue first, second and high-order all-pass active filters in the current mode, with constant group delay and magnitude responses, are presented in this paper. These filters are based on a modification of the multi-loop feedback canonical structures using signal flow graphs. Implementations by multi-output transconductors, namely classical OTAs and novel CDTAs are given.

  1. CHEN, W. K. The Circuits and Filters Handbook. CRC Press, Florida, 1995.
  2. TOUMAZOU, C., LIDGEY, F. J., HAIGH, D. G. Analogue IC Design: The Current-Mode Approach. Peter Peregrinus Ltd., London, 1990.
  3. SUN, Y., FIDLER J. K. Current-mode OTA-C realization of arbitrary filter characteristics. Electronics Letters, 1996, vol. 32, no. 13, p. 1181 -1182.
  4. SUN, Y., FIDLER J. K. Current-mode multiple-loop filters using dual-output OTA's and grounded capacitors. International Journal of Circuit Theory and Application, 1997, vol. 25, no. 1, p. 69 - 80.
  5. ACAR, C., ANDAY, F., KUNTMAN, H. On the realization of OTA-C filters. International Journal of Circuit Theory and Application, 1993, vol. 21, no. 3, p. 331 - 341.
  6. DOSTAL, T. Filters with multi-loop feedback structure in current mode. Radioegineering, 2003, vol. 12, no. 3, p. 1-6.
  7. VRBA, K., CAJKA, J., MATEJICEK, L. New high-order allpass filters using TOTA elements. Journal of Electrical Engineering, 2003, vol. 52, no. 5-6, pp. 1 - 8.
  8. BIOLEK, D. CDTA - building block for CM analog signal processing, In Proceeding of European Conference on Circuit Theory and Design ECCCTD'03, Krakow (Poland), 2003, pp. III-397-400.
  9. GUBEK, T., BIOLEK, D. Allpass analog filters in current mode. Internet Journal Electronicsletters, 2004, No 2/12/2004,
  10. HAJEK, K., SEDLACEK, J. NAFID program as a powerful tool in filter education area. In Proceedings of the conference CIBLIS'97, Leicester (UK), 1997, p. PK-4 1-10.
  11. BIOLEK, D., KOLKA, Z., SVIEZENY, B. Teaching of electrical circuits using symbolic and semisymbolic programs. In Proceedings of the 11th Conference EAEEIE, Ulm (Germany), 2000, p. 26 - 30.