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Radioengineering

Radioeng

Proceedings of Czech and Slovak Technical Universities

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April 2005, Volume 14, Number 1

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J. Halamek, I. Viscor, M. Kasal, M. Villa [references] [full-text]
Static and Dynamic Nonlinearity of A/D Converters

The dynamic range of broadband digital system is mostly limited by harmonics and spurious arising from ADC nonlinearity. The nonlinearity may be described in several ways. The distinction between static and dynamic contributions has strong theoretical motivations but it is difficult to independently measure these contributions. A more practical approach is based upon analysis of the complex spectrum, which is well defined, easily measured, and may be used to optimize the ADC working point and to somehow characterize both static and dynamic nonlinearity. To minimize harmonics and spurious components we need a sufficient level of input noise (dither), which destroys the periodicity at multistage pipelined ADC, combined with a careful analysis of the different sources of nonlinearity.

  1. IEEE 1241-2000. Standard for Terminology and Tests Methods for Analog to Digital Converters. 2001.
  2. European Project DYNAD-SMT4-CT98-2214. Methods and Draft Standards for the Dynamic Characterization and Testing of Analog to Digital Converters, http://www.fe.up.pt/~hsm/dynad
  3. SCHOUKNES, J. A Critical note on histogram testing of data acquisition channels. IEEE Transactions on Instrumentation and Measurement, 1995, vol. 44, no. 4, p.860-863.
  4. HUMMELS, D.M. Linearization of ADCs and DACs for all-digital-wide-bandwidth receivers. In 4th IMECO TC-4 Workshop ADC Modelling and Testing, Bordeaux (France), 1999, p. 145-151.
  5. MONTEIRO, C. L., ARPAIA, P., SERRA, A. C. A comprehensive phase-spectrum approach to meterological characterization of hysteretic ADCs. IEEE Transactions on Instrumentation and Measurement, 2002, vol. 51, no. 4, p.756-763.
  6. HILTON, H. E. A 10-MHz analog-to-digital converter with 110-dB linearity. Hewlett-Packard Journal, Oct. 1993, p. 105-112.
  7. ACUNTO, S., ARPAIA, P., HUMMELS, D. M., IRONS, F. H. A new bidimensional histogram for the dynamic characterization of ADCs. IEEE Transactions on Instrumentation and Measurement, 2003, vol. 52, no. 1, p.38-45.
  8. ARPAIA, P., DAPONTE, P., MICHAELI, L. An analytical a-priori approach to phase plane modelling of SAR A/D Converters. IEEE Transactions on Instrumentation and Measurement, 1998, vol. 47, p.849-857.
  9. JANIK, J. M. Estimation of A/D converter nonlinearities from complex spectrum. In Proceedings of 8th IWADC 2003, Perugia (Italy), 2003, p. 205-208.
  10. ADAMO, F, ATTIVISSIMO, F., GIAGUINTO, N. Measuring dynamic nonlinearity of A/D converters via spectral methods. In: Proceedings of 8th IWADC 2003, Perugia (Italy), 2003, p.167-170.
  11. ARPAIA, P., SERRA, A. C., DAPONTE, P., MONTEIRO, C. L. A critical note to IEEE 1057-94 standard on hysteretic ADC dynamic testing. IEEE Transactions on Instrumentation and Measurement, 2001, vol. 50, no. 4, p.941-947.
  12. VISCOR. I., HALAMEK, J. Close-in spurs in digital receiver. In Proceedings of 8th IWADC 2003, Perugia (Italy), 2003, p. 125-128.
  13. BRANNON, B., CLONINGER, C. H. Redefining the role of ADC in wireless. Applied Microwave & Wireless, March 2001, p. 94-105
  14. LUNDIN, H., SKOGLUND, M., HANDEL, P. Minimal total harmonic distortion post-correction of ADCs. In Proceedings of 8th IWADC 2003, Perugia (Italy), 2003, 113-116.
  15. VITO, L.D., MICHAELI, L., RAPUANO, S. Non-linearity correction of ADC in software radio systems. In Proceedings of 13th IMECO TC-4 and 9th IWADC, Athens (Greece), 2004, p.887-891.
  16. VISCOR, I., HALAMEK, J. Acquisition system with low jitter. In Proceedings of 7th IWADC 2002, Praha (Czech Republic), 2002, p. 83-86.
  17. HALAMEK, J., VISCOR, I., KASAL, M., VILLA, M., COFRANCESCO, P. Harmonic distortion and statistical analysis. In Proceedings of 7th IWADC 2002, Praha (Czech Republic), 2002, p. 91-94.

M. Vondrasek, P. Pollak [references] [full-text]
Methods for Speech SNR Estimation: Evaluation Tool and Analysis of VAD Dependency

The dynamic range of broadband digital system is mostly limited by harmonics and spurious arising from ADC nonlinearity. The nonlinearity may be described in several ways. The distinction between static and dynamic contributions has strong theoretical motivations but it is difficult to independently measure these contributions. A more practical approach is based upon analysis of the complex spectrum, which is well defined, easily measured, and may be used to optimize the ADC working point and to somehow characterize both static and dynamic nonlinearity. To minimize harmonics and spurious components we need a sufficient level of input noise (dither), which destroys the periodicity at multistage pipelined ADC, combined with a careful analysis of the different sources of nonlinearity.

  1. HAIGH J. A., MASON. S. A voice activity detector based on cepstralanalysis. In Eurospeech 93. Berlin (Germany), 1993.
  2. JELINEK, T. Differential Cepstral Detector of Voice Activity. Diplomatheses CTU-FEE, 2004 (in Czech).
  3. JUNQUA, J.-C., HATON, J.-P. Robustness in Automatic Speech Processing.Kluwer Academic Publishers, 1996.
  4. KORTHAUER, A. Robust estimation of SNR of noisy speech signals forthe quality evaluation of speech databases. In Proc. Robust Methods forSpeech Recognition in Adverse Conditions. Tampere (Finland), 1999.
  5. MARTIN, R. An efficient algorithm to estimate the instantaneous SNRof speech signals. In Eurospeech 93. Berlin (Germany), 1993, pp. 1093- 1096.
  6. POLLAK, P. Efficent and reliable measurements and simulation of noisyspeech background. In EUSIPCO 2002. Toulouse (France), 2002.
  7. POLLAK, P. Estimation methods of speech signal-to-noise ratio. AcousticSheets, c.7, 2001 (in Czech).
  8. RIS, Ch., DUPONT, S. Assessing local noise level estimation methods:Application to noise robust ASR. Speech Communication, 2001,pp. 141-158.
  9. VONDRASEK, M. Estimation of Speech SNR in Signal from Noisy Environment.Diploma theses CTU-FEE, 2004 (in Czech).
  10. BAGWELL, Ch. SoX - Sound eXchange. http://www.sox.com: - Soxsoftware WEB page.

N . Leonis, G. Katsoulis, A. Amditis, N. Uzunoglu [references] [full-text]
Estimation of Spread Spectrum Signal Parameters Utilizing Wavelet Transform Analysis

This paper investigates the application of wavelet transform (WT) to the extraction of particular features of direct sequence spread spectrum signals. The WT is exploited to the point that not only its capabilities but also its limitations are exposed to achieve the specific task of identifying spread spectrum signal parameters. The capabilities focus on the detection of the chipping sequence, while the limitations refer primarily to the advent of direct sequence CDMA signals. In the latter case no progress has yet been made to distinguish the different chipping sequences by the WT, whose resultant effect on the carrier appears as a single-phase change.

  1. PETERSON, R. L., ZIEMER, R. E., BORTH, D. E. Introduction to Spread Spectrum Communications. Englewood Cliffs, NJ: Prentice-Hall, 1995.
  2. LEE, J. S., MILLER, L. E. CDMA Systems Engineering Handbook. Boston: Artech House Publishers, 1998.
  3. SIMON, M., OMURA, J., SCHOLTZ, R., LEVITT, B. Spread Spec-trum Communications Handbook. New York: McGraw-Hill, 1994.
  4. SKOLNIC, M. I. Introduction to Radar Systems. 2nd ed. New York: McGraw-Hill, 1980.
  5. SKOLNIC, M. I. Radar Handbook. 2nd ed. New York: McGraw-Hill, 1990.
  6. VITERBI, A. J. Principles of Spread Spectrum Communications. Massachusets: Addison-Wesley, 1995.
  7. MALLAT, S. A Wavelet: Tour of Signal Processing. 2nd ed. San Diego: Academic Press, 1999.
  8. BURRUS, S. et. al. Introduction to Wavelets and Wavelet Trans-forms: A Primer. New Jersey: Prentice Hall, 1998.
  9. RAO, R. M., BOPARDIKAR, A. S. Wavelet Transforms: Introduc-tion to Theory and Applications. Massachusetts: Addison Wesley, 1998.
  10. BHOURI, N. H., COCHRAN, D. Multiresolution time - frequency techniques for spread spectrum demodulation and jamming, signals, systems and computers. In Record of the Twenty-Sixth Asilomar Conference. 1992, p. 105 - 107.
  11. MISITI, M., MISITI, Y., OPPENHEIM, G., POGGI, J. M. Wavelet Toolbox For Use with Matlab. Natick, MA: The Mathworks, Inc., 1997.
  12. HAYKIN, S., Communication Systems. 3rd ed. New York: John Wi-ley & Sons, Inc. 1994.
  13. HO, K. C., PROKOPIW, W., CHAN, Y. T. Modulation identifica-tion of digital signals by the wavelet transform, radar, sonar and navigation. IEE Proceedings. 2000, vol. 147, no. 4 , p. 169 - 176.
  14. STRANG, G., NGUYEN, T. Wavelets and Filter Banks. Wellesley MA: Wellesley-Cambridge Press, 1997.
  15. PROAKIS, J. G., SALEHI, M. Communication Systems Engineering. New Jersey: Prentice-Hall International Editions, 1995.
  16. SCHLEDER, D. C. Introduction to Electronic Warfare. Norwood, MA: Artech House, 1986.
  17. PROAKIS, J. G., MANOLAKIS, D. G. Digital Signal Processing, Principles, Algorithms and Applications. 3rd ed. New Jersey: Prentice-Hall, 1998.
  18. PROAKIS, J. G. Digital Signal Processing Using Matlab. Boston: PWS Publishing Company, 1998.
  19. PROAKIS, J. G. Digital Communications. 3rd ed. New York: McGraw-Hill, 1995.
  20. PROAKIS, J. G., SALEHI, M. Contemporary Communication Sys-tems Using Matlab. Boston: PWS Publishing Company, 1998.
  21. AKANSU, A. N., HADDAD, R. A. Multiresolutional Signal Decom-position. 2nd ed. San Diego: Academic Press, 2001.

R . Landquist, A. Mohammed [references] [full-text]
An Adaptive Block-Based Eigenvector Equalization for Time-Varying Multipath Fading Channels

In this paper we present an adaptive Block-Based EigenVector Algorithm (BBEVA) for blind equalization of time-varying multipath fading channels. In addition we assess the performance of the new algorithm for different configurations and compare the results with the least mean squares (LMS) algorithm. The new algorithm is evaluated in terms of intersymbol interference (ISI) suppression, mean squared error (MSE) and by examining the signal constellation at the output of the equalizer. Simulation results show that the BBEVA performs better than the non-blind LMS algorithm.

  1. LANDQVIST, R., MOHAMMED, A. Simulation of wireless digitalcommunication systems. Radio Engineering Journal, Special Issue:"Digital Signal Processing and Transmission of Multimedia", December2004, vol. 13, no. 4, p. 1-7.
  2. QUERSHI, S. Adaptive equalization. IEEE Proceedings, 1985, vol.73, no. 9, p. 1349-1387.
  3. NORDBERG, J., MOHAMMED, A., NORDHOLM, S., CLAESSON,I. Fractionally spaced spatial adaptive equalization. For SUMTSmobile terminals. Invited Paper, Special Issue of Wiley's InternationalJournal of Adaptive Control and Signal Processing,2002, vol. 16, no. 8, p. 541-555.
  4. LANDQVIST, R., MOHAMMED, A. An efficient and effective pilotspace-time adaptive algorithm for mobile communication systems.Radio Engineering Journal, 2005, vol. 14, no. 1, p. 29-31.
  5. MOHAMMED, A. Advances in signal processing for mobilecommunication systems. Editorial for a Special Issue of Wiley's InternationalJournal of Adaptive Control and Signal Processing,2002, vol. 16, no. 8, p. 539-540.
  6. GODARD, D.N. Self-recovering equalization and carrier tracking intwo dimensional data communication systems. IEEE Transactions onCommunications, 1980, vol. 28, no. 11, p. 1867-1875.
  7. SATO, Y. A method for self-recovering equalization for multilevelamplitude modulation systems. IEEE Transactions on Communications,1975, vol. 23, no. 6, p. 679-682.
  8. JELONNEK, B., KAMMAYER, K. A closed-form solution to blindequalization. Elsevier Signal Processing, 1994, vol. 36, no. 3, p. 251-259.
  9. JELONNEK, B., BOSS, D., KAMMAYER, K. Generalizedeigenvector algorithm for blind equalization. Elsevier SignalProcessing, 1997, vol. 61, no. 3, p. 237-264.
  10. GUSTAFSSON, R., MOHAMMED, A. A block based eigenvectorequalization for time-varying channels. In Proceedings of the Wireless2002 conference, Calgary (Canada), 2002.

J. A. Romo, I. F. Anitzine, F. P. Fontan, P. Marino [references] [full-text]
Analysis of Rain Rate Spatial Cross-Correlation Coefficients in the Basque Country Area

This paper reports on a study on the spatial characteristics of rain rates recorded in the Basque region in northern Spain. To perform this study a network of eighty raingauges spread throughout the region has been used. Statistical parameters such as the spatial cross-correlation coefficient and the space-time cross-correlation coefficient were calculated and their evolution with separation distance studied. It is hoped that information reported could be useful in better understanding characteristics of rain and in developing countermeasures for terrestrial and satellite radio networks operating at frequencies above 10 GHz.

  1. ENJAMIO, C. VILAR, E., FONTAN, F. P., REDANO, A. Rainfall rate spatial distribution at local scale: Rain cell analysis in the Mediterranean region. In Open Symposium on Propagation and Remote Sensing. URSI. Garmisch-Partenkirchen (Germany), February 12 to 15, 2002.
  2. BARBALISCIA, F., RAVAIOLI, G., PARABONI, A. Characteris-tics of the spatial statistical dependence of rainfall rates over large areas. IEEE Transactions on Antennas and Propagation. 1992, vol. 40, no. 1, p. 8 - 12.
  3. FUKUCHI, H. Correlation properties of rainfall rates in the United Kingdom. IEE Proceedings, 1998, vol. 135, no. 2, p. 83 - 88.
  4. GARCIA, P., ZAMBUDIO, N., BENARROCH, A. Joint rainfall rate statistics for pairs of sites in Spanish regions. In COST Action 280 "Propagation Impairment Mitigation for Millimetre Wave Radio Systems", PM3-005, 1st International Workshop, July 2002.
  5. ORDANO, L. Assessment of correlation properties of rainfall inten-sity measured in Italy. 5th International Conference on Antennas and Propagation, ICAP'87, March 1987, p. 334 - 337.

R . Landquist, A. Mohammed [references] [full-text]
An Efficient and Effective Pilot Space-Time Adaptive Algorithm for Mobile Communication Systems

In this paper we present a new adaptive space-time algorithm for mitigating the effects of CCI and ISI and minimizing the probability of error in mobile communication systems, and evaluate its performance for different mobile velocities. The proposed algorithm is computationally efficient and provides better performance than the conventional RLS algorithm.

  1. NG, B.C., CHEN, J.-T., PAULRAJ, A. Space-time processing for fast fading channels with co-channel interference. In Proc. of IEEE Vehicular Technology Conference, 1996, vol. 3, p. 1491 - 1495.
  2. WINTERS, J.H., SALY, J., GITLIN, R.D. The impact of antenna diversity on the capacity of wireless communications systems. IEEE Transactions on Communications, 1994, vol. 42, no. 2/3/4, p. 1740-1751.
  3. WINTERS, J.H. Signal acquisition and tracking with adaptive arrays in the digital mobile radio system IS-54 with flat fading. IEEE Transactions on Vehicular Technology, 1993, vol. 42, no. 4, p. 337-348.
  4. RUPP, M., SAVED, A.H. On the convergence of blind adaptive equalizers for constant modulus signals. IEEE Transactions on Communications, 2000, vol. 48, no. 5, p. 798-803.
  5. LIBERTI, J.C., RAPPAPORT, T.S. Smart Antennas for Wireless Communications - IS-95 and Third Generation CDMA Applications, Prentice-Hall, 1999.
  6. HAYKIN, S. Adaptive Filter Theory, Prentice-Hall, 2002.

M. Grabner, U.-C. Fiebig, V. Kvicera [references] [full-text]
Generator of Time Series of Rain Attenuation: Results of Parameter Extraction

Rain attenuation has a significant impact on the availability of millimeter wave communication systems. In order to dynamically simulate such radio systems, several generators of artificial time series of rain attenuation have been developed. This paper briefly describes the DLR channel model and presents the results of model parameter extraction from time series measured on terrestrial microwave paths in the Czech Republic.

  1. FIEBIG, U.-C., CASTANET, L., LEMORTON, J., MATRICCIANI, E., PEREZ-FONTAN, F., RIVA, C., WATSON, R. Review of propagation channel modelling. In Proceedings of 2nd International workshop of COST280 Action. May 2003, p. 153 - 164.
  2. CASTANET, L., LEMORTON, J., LACOSTE, F., RIVA, C., MATRICCIANI, E., FIEBIG, U.-C., VAN DE KAMP, M., MARTELLUCCI, A. Development and validation of time series synthesizers for Ka-band satellite communication systems. In Proceedings of 10th Ka-Band Utilization Conference. Vicenza (Italy), October 2004.
  3. FIEBIG, U.-C. Modelling rain fading with a time-series generator considering seasonal and diurnal variations. In Proceedings of the 8th Ka-Band Utilization Conference. Baveno/Strese (Italy), 2002.
  4. FIEBIG, U.-C. Satellite channel modelling for rain fading. In Pro-ceedings of AAIA International Communications Satellite System Conference. Yokohama (Japan), 2003.

J. Zdansky [references] [full-text]
Detection of Acoustic Change-Points in Audio Streams and Signal Segmentation

This contribution proposes an efficient method for the detection of relevant changes in continuous stream of sound. The detected change-points can then serve for the segmentation of long audio recordings into shorter and more or less homogenous sections. First, we discuss the task of a single change-point detection using the Bayes decision theory. We show that it leads to a quite simple and computationally efficient solution based on the Bayesian Information Criterion. Next, we extend this approach to formulate the algorithm for the detection of multiple change-points. Finally, the proposed algorithm is applied for the segmentation of broadcast news audio-streams into parts belonging to different speakers or different acoustic conditions. Such segmentation is necessary as the first step in the automatic speech-to-text transcription of TV or radio news.

  1. ZDANSKY, J., DAVID, P., NOUZA, J. An improved preprocessor for the automatic transcription of broadcast news audio stream. In Proceedings of 8th International Conference on Spoken Language Processing ICSLP 2004. JeJu (South Korea), 2004.
  2. KASS, R., RAFTERY, A. Bayes factors. Journal of the American Statistical Association, 1995, p. 773-795.
  3. KASS, R., TIERNEY, L., KADANE, J. Asymptotics in Bayesian computation. Bayesian statistics 3. Oxford University Press, 1988, pp. 261 - 278.
  4. VANDECATSEYE, A. et al. The COST278 pan-European broadcast news database. In Proceedings of 4thInternational Conference on Language Resources and Evaluation LREC 2004. Lisbon (Portugal), 2004.
  5. CHICKERING, D. M., HECKERMAN, D. Efficient approximations for the marginal likelihood of Bayesian networks with hidden variables. Technical report MSR-TR-96-08. Microsoft Research, 1996.

D. Levicky, S. Surin [references] [full-text]
Codebook Code Division Multiple Access Image Steganography

In this paper, a new modification of spread spectrum image steganography (SSIS) is presented. The proposed modification of SSIS hides and recovers a message of substantial length within digital image while maintaining the original image size and dynamic range. An embedded message can be in the form of text, image, or any other digital signal. Our method is based on CDMA SSIS technique. To increase the information capacity of the stego channel and decrease a distortion of a cover image, a new modification of CDMA using a codebook (in the following referred to as Codebook CDMA (CCDMA)) is suggested.

  1. MARVEL, L. M., BONCELET, CH. G., RETTER, CH. T. Spread spectrum image steganography. IEEE Trans. On Image Processing, vol. 8, no. 8, Aug. 1999, p.1075 - 1083.
  2. LEVICKY, D., FORIS, P., KLENOVICOVA, Z., SURIN, S. Sucasny stav a perspektivy vyulitia digitalnych vodoznakov. In Co-fax - Telecommuniations 2004, 10th International Scientific Conference, 2004, p. 165 - 168.
  3. LEVICKY, D., FORIS, P. Human visual system models in digital image watermarking, Radioengineering, vol. 13, no. 4, p. 38-43.
  4. HERNANDEZ, J. A., AMADO, M., PEREZ-GONZALEZ, F. DCT-domain watermarking techniques for still images: Detector per-formance analysis and a new structure. IEEE Trans. Image Processing, vol. 9, no. 1, Jan. 2000, p. 55 - 68.
  5. SKLAR, B. Digital Communications: Fundamentals and Applica-tions. Prentice Hall, 2001.
  6. MOSHAVI, S. Multi-user detection for DS-CDMA communications. IEEE Comm. Magazine, Oct. 1996, p. 124 - 136.

B. Taha-Ahmed, M. Calvo-Ramon, L. D. Haro-Ariet [references] [full-text]
Intelligent FDSS Overlay on GSM System (Uplink Analysis)

The overlay of an intelligent frequency diversity spread spectrum system (FDSS) on the (GSM) system is studied. The uplink capacity of both systems is given using a model of 36 hexagonal macrocells. Performance of GSM and FDSS users is investigated. An original GSM system with 48 users/macrocell can be substituted by a mixed system, which has GSM system capacity of 48 users/macrocell and FDSS system capacity of 128 users/macrocell.

  1. GRIECO, D. M., SCHILLING, D. L. The capacity of broadband CDMA overlaying a GSM cellular system. In Proceedings of the Vehicular Technology Conference VTC 94. 1994, p. 31-35.
  2. KOOREVARR, P., RUPRECHT, J. Frequency overlay of GSM and cellular B-CDMA. IEEE Transactions on Vehicular Technology, 1999, vol. 48, no. 3, p. 696 - 707.
  3. ZHOU, J., YAMAMOTO, U., ONOZATO, Y. Impact of interference suppression techniques on spectrum overlaid systems of TDMA/W-CDMA and N-CDMA/W-CDMA. IEICE Transactions on Communication, 2001, vol. E84-B(3).
  4. PAPPORTH, E., KALEH, G. K. A CDMA overlay system using fre-quency diversity spread spectrum. IEEE Transactions on Vehicular Technology, 1999, vol. 48, no. 2, p. 397 - 404.
  5. HERNANDO, J. M., FONTAN, F. P. Introduction to Mobile Com-munications Engineering. Norwood: Artech House, 1999.

B. Taha-Ahmed, M. Calvo-Ramon, L. D. Haro-Ariet [references] [full-text]
Impact of Ultra Wide Band (UWB) on Macrocell Downlink of DCS-1800 and GSM-900 Systems

The effect of UWB interference on the DCS-1800 and GSM-900 downlink is studied for different UWB power density. For high UWB power density (-70 dBm/MHz), the effect of UWB signals is very high when the distance between UWB transmitter and DCS-1800 receiver is less than 1 m. For low UWB power density (-100 dBm/MHz), the effect of the UWB signals is quasi null even if the distance between the UWB transmitter and the DCS-1800 receiver is 0.5 m. It is found that the spectrum mask proposed by the FCC for indoor application (-53 dBm/MHz in the DCS-1800 band and -41 dBm/MHz in the GSM-900 band) is very high to be tolerated by the two mobile systems and we have to propose another spectrum mask with lower UWB power density.

  1. HAMALAINEN, M., HOVINEN, V., TESI, R., IINATI, J., LATAVA-AHO, M. On the UWB system coexistance with GSM900, UMTS/WCDMA, and GPS. IEEE Journal on Selected Areas in Communications, 2002, vol. 20, no. 9, p. 1712 - 1721.
  2. HAMALAINEN, M., TESI, R., IINATI, J. UWB co-existence with IEEE802.11a and UMTS in modified Saleh-Valenzuela channel. In Proceedings of the Conference on Ultra Wideband Systems, 2004. 2004, p. 45 - 49.
  3. GIULIANO, R., MAZZENGA, F., VATALARO, F. On the interfe-rence between UMTS and UWB systems. In Proceedings of the Conference on Ultra Wideband Systems 2003. 2003, p. 339 - 343.
  4. HAMALAINEN, M., HOVINEN, V., IINATI, J., LATAVA-AHO, M. In-band interference power caused by different kinds of UWB signals at UMTS/WCDMA frequency bands. In Proceedings of the 2001 IEEE Radio and Wireless Conference, RAWCON 2001. 2001, p. 97 - 100.
  5. HAMALAINEN, M., HOVINEN, V., IINATI, J., LATAVA-AHO, M. In-band interference of three kind of UWB signals in GPS L1 band and GSM900 uplink band. In Proceedings of the 12th International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC 2001. 2001, p. D 76 - 80.