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Proceedings of Czech and Slovak Technical Universities

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December 2004, Volume 13, Number 4

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R. Landqvist, A. Mohammed [references] [full-text] [Download Citations]
Simulation of Wireless Digital Communication Systems

Due to the explosive demands for high speed wireless services, such as wireless Internet, email and cellular video conferencing, digital wireless communications has become one of the most exciting research topics in electrical and electronic engineering field. The never-ending demand for such personal and multimedia services, however, demands technologies operating at higher data rates and broader bandwidths. In addition, the complexity of wireless communication and signal processing systems has grown considerably during the past decade. Therefore, powerful computer­aided techniques are required for the process of modeling, designing, analyzing and evaluating the performance of digital wireless communication systems. In this paper we discuss the basic propagation mechanisms affecting the performance of wireless communication systems, and present a simple, powerful and efficient way to simulate digital wireless communication systems using Matlab. The simulated results are compared with the theoretical analysis to validate the simulator. The simulator is useful in evaluating the performance of wireless multimedia services and the associated signal processing structures and algorithms for current and next generation wireless mobile communication systems.

  1. MOHAMMED, A. Advances in signal processing for mobile communication systems. Editorial for a Special Issue of Wiley's International Journal of Adaptive Control and Signal Processing, 2002, vol. 16, no. 8, p. 539-540.
  2. NORDBERG, J., MOHAMMED, A., NORDHOLM, S., CLAES-SON, I. Fractionally spaced spatial adaptive equalization. For S-UMTS mobile terminals. Invited Paper, Special Issue of Wiley's International Journal of Adaptive Control and Signal Processing, 2002, vol. 16, no. 8, p. 541-555.
  3. ERTEL,R.B., CARDIERI, P., SOWERBY, K.W., RAPPAPORT, T.S., REED, J.H. Overview of spatial channel models for antenna array communication systems. IEEE Personal Communications, 1998, vol. 5, no. 1, p. 10-22.
  4. CHRYSSOMALLIS, M. Simulation of mobile fading channels. IEEE Antennas and Propagation Magazine, 2002, vol. 44, no. 6, p. 172-183.
  5. PATZOLD. Mobile Fading Channels. Wiley, 2002.
  6. CLARKE, R. H. A statistical theory of mobile-radio reception. Bell System Technical Journal, 1968, vol. 47, p. 957-1000.
  7. NORDBERG, J., DAM, H. H. Evaluation of different Rayleigh fading channel simulators. Tech. Rep., ATRI, Curtin University, 2001.
  8. JAKES, W.C. Microwave mobile communication. IEEE Press, 1994.
  9. DUEL-HALLEN, A., FULGHUM, T.L., MOLNAR, K.J. The Jakes fading model for antenna arrays incorporating azimuth spread. IEEE Trans. on Vehicular Technology, 2002, vol. 51, no. 5, p. 968-977.
  10. RICE, S. O. Mathematical analysis of random noise. Bell System Technical Journal, 1944, vol. 23, p. 282-332.
  11. RICE, S. O. Mathematical analysis of random noise. Bell System Technical Journal, 1945, vol. 24, p. 46-156.
  12. CHEN, X. F., CHUNG, K. S. Generation of noise sources for a digital frequency selective fading simulator. In Proceedings of the Fourth International Symposium on Signal Processing and its Appli-cations (ISSPA), 1996, vol. 2, p. 463-466.
  13. FUNG, V., RAPPAPORT, T.S., THOMA B. Bit error simulation for pi/4-DQPSK mobile radio communications using two-ray and measurement-based impulse response models. IEEE Journal on Selected Areas in Communications, 1993, vol. 11, no. 3, p. 393-405.
  14. SUZUKI, H. A statistical model for urban radio propagation. IEEE Transactions on Communications, 1977, vol. 25, no. 7, p. 673-680.
  15. PATZOLD, M., KILLAT, U., LAUE, F., LI, Y. On the statistical properties of deterministic simulation models for mobile fading channels. IEEE Transactions on Vehicular Technology, 1998, vol. 47, no. 1, p. 254-269.
  16. LANDQVIST, R., MOHAMMED, A. An efficient and effective pilot space-time adaptive algorithm for mobile communication systems. Radioengineering, to appear April 2005.
  17. LANDQVIST, R., MOHAMMED, A. An adaptive block-based eigenvector equalization for time-varying multipath fading channels. Submitted to Radioengineering.
  18. HAYKIN, S. Digital Communications. J. Wiley & Sons, Inc., 1988.
  19. PROAKIS, J. G. Digital Communications. 3rd ed. McGraw-Hill, '95.
  20. PECHAC, P., LEDL P., MAZANEK, M. Modeling and measurement of dynamic vegetation effects at 38 GHz. Symposium Proceedings - URSI-F 2004 [CD-ROM]. Milton: URSI, 2004, p. 147-155.
  21. PARSONS, J.D. The Mobile Propagation Radio Channel. 2nd ed., J. Wiley & Sons, London, 2000.
  22. MOHAMMED, A., SAMAWI, S. Measurement trails of the Bluetooth link in indoor office environments. Mathematical Modelling of Wave Phenomena Conference, 3-8 November 2002, Vaxjo, Sweden, p. 295-303.

S. Takahashi, A. Kato, K. Sato, M. Fujise [references] [full-text] [Download Citations]
Distance Dependence of Path Loss for Millimeter Wave Inter-Vehicle Communications

Millimeter-wave path loss between two cars was measured to obtain the general applicable distance for inter-vehicle communication systems in real environments. An abrupt and substantial increase in path loss due to interruption, curves, and different-lane traveling has been a major concern in inter-vehicle communications. The path loss measurements were carried out using 60-GHz CW radiowaves and standard horn antennas on metropolitan highways and regular roads. Because the propagation loss is traffic-dependent, the highways were classified into uncrowded and crowded highways, and the regular roads were classified into uncrowded and crowded roads. The path loss for the highways exhibited 2nd-power-law attenuation and that for the regular roads exhibited 1st-power-law attenuation with an increase in inter-vehicle distance. Additional losses of 15 dB for the highways and 5 dB for the regular roads were observed when the inter-vehicle distance was more than approximately 30 m. Thus, we were able to demonstrate millimeter-wave inter-vehicle communications at an inter-vehicle distance of more than 100 m.

  1. IIDA, T. Wireless communications R&D in the science and technology policy in Japan. IEICE Trans. Electron. March 2002, vol. E85-C, no. 3, pp. 419-427.
  2. VERDONE, R. Performance evaluation of R-ALOHA for inter-vehicle communications at millimeter waves. In IEEE International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC '96). Oct. 1996, vol. 2, pp. 658-662.
  3. VERDONE, R. Multihop R-ALOHA for intervehicle communications at millimeter waves. IEEE Trans. on Vehicul. Technol., Nov. 1997, vol. 46, no. 4, pp. 992-1005.
  4. OHYAMA, T., NAKABAYASHI, S., SHIRAKI, Y., TOKUDA, K. A study of real-time and autonomous decentralized DSRC system for inter-vehicle communications. In IEEE International Conference on Intelligent Transportation Systems, 2000, pp. 190-195.
  5. MAURER, J., SCHAFER, T. M., WIESBECK, W. A realistic description of the environment for inter-vehicle wave propagation modelling. In IEEE Vehicular Technology Conference Fall (VTC 2001-Fall), 2001, vol. 3, pp. 1437-1441.
  6. MIZUTANI, K., KOHNO, R. Analysis of multipath fading due to two-ray fading and vertical fluctuation of the vehicles in ITS inter-vehicle communications. In IEEE International Conference on Intelligent Transportation Systems, 2002, pp. 318-323.
  7. KATO, A., SATO, K., FUJISE, M., KAWAKAMI, S. Propagation characteristics of 60-GHz millimeter waves for ITS inter-vehicle communications. IEICE Trans. Commun., Sept. 2001, vol. E84-B, no. 9, pp. 2530-2539.

T. Kratochvil, M. Slanina [references] [full-text] [Download Citations]
The DVB Channel Coding Application Using the DSP Development Board MDS TM-13 IREF

The paper deals with the implementation of the channel coding according to DVB standard on DSP development board MDS TM-13 IREF and PC. The board is based on Philips Nexperia media processor and integrates hardware video ADC and DAC. The program libraries features used for MPEG based video compression are outlined and then the algorithms of channel decoding (FEC protection against errors) are presented including the flowchart diagrams. The paper presents the partial hardware implementation of the simulation system that covers selected phenomena of DVB baseband processing and it is used for real time interactive demonstration of error protection influence on transmitted digital video in laboratory and education.

  1. KRATOCHVIL, T. Utilization of Matlab for Digital Image Transmission Simulation Using the DVB Error Correction Codes. Radioengineering, 2003, vol. 12, no. 4.
  2. MDS TM-13 IREF Datasheet. Momentum Data System, Inc.,, 2002.
  3. Data Book, PNX1300 Series Media Processor. Philips Semiconductor Inc.,, 2002.
  4. RICHARDSON, I. E. G. Video Codec Design, Developing Image and Video Compression system. John Wiley & Sons, Ltd., 2002.
  5. IADK 1.0 SP 1 Release notes. Philips Semiconductor Inc., 2002.
  6. RIEMERS, U. Digital Video Broadcasting, The Family of International Standards for Digital Television (second edition). Springer, 2004.
  7. SLANINA, M. Implementation of Image Transmission and Channel Coding FEC in Area DVB. M.Sc. student project, FEEC BUT, Brno, 2004 (in Czech).
  8. WICKER, S. B., BHARGAVA, V. G. Reed Solomon Codes and Their Applications. IEEE Press, 1994.
  9. JOHANNESSON, R., ZIGANGIROV, K. S. Fundamentals of Convolution Coding. IEEE Press, 1999.

N. Kostov [references] [full-text] [Download Citations]
Convolutional/Single Parity Check Turbo Codes for Wireless Multimedia Communications

Error correction codes are widely used in digital communications to improve the Quality of Service. The Quality of Service is typically expressed in terms of maximum acceptable frame error rate and bit error rate. The key implementation issues for most powerful error correction codes are the complexity and overall encoding/decoding latency. In this paper, short-frame turbo product codes for real-time wireless multimedia communications are proposed. Performance of the proposed turbo codes is studied through simulations on an additive white Gaussian noise (AWGN) channel. The obtained results indicate that the performance of these codes is quite exceptional given their decoding complexity.

  1. BERROU, C., GLAVIEUX, A., THITIMASJSHIMA, P. NearShannon limit error-correcting coding and decoding: Turbo-codes. InProceedings of IEEE International Conference on Communications,Geneva (Switzerland), 1993, p. 1064-1070.
  2. BENEDETTO, S., MONTORSI, G. Unveiling turbo codes: Someresults on parallel concatenated coding schemes. IEEE Transactionson Information Theory, 1996, vol. 42, no. 2, p. 409-428.
  3. HAGENAUER, J., OFFER, E., PAPKE, L. Iterative decoding ofbinary block and convolutional codes. IEEE Transactions on InformationTheory, 1996, vol. 42, no. 2, p. 429-445.
  4. KOORAPATY, H., WANG, Y., BALACHANDRAN, K. Performanceof turbo codes with short frame sizes. In Proceedings ofIEEE Vehicular Technology Conference, Phoenix (USA), 1997, p.329-333.
  5. PYNDIAH, R. Near-optimum decoding of product codes: Blockturbo codes. IEEE Transactions on Communications, 1998, vol. 46,no. 8, p. 1003-1010.
  6. HAGENAUER, J., HOEHER, P. A Viterbi algorithm with softdecisionoutputs and its applications. In Proceedings of IEEE GlobalCommunications Conference. Dallas (USA), 1989, p. 47.1.1-47.1.7.
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  8. TAN, J., STUBER, G. New SISO decoding algorithms. IEEE Transactionson Communications, 2003, vol. 51, no. 6, p. 845-848.

M. Galabov [references] [full-text] [Download Citations]
Implementation of IMDCT Block of an MP3 Decoder through Optimization on the DCT Matrix

The paper describes an attempt to create an efficient dedicated MP3-decoder, according to the MPEG-1 Layer III standard. A new method of Inverse Modified Discrete Cosine Transform by optimization on the Discrete Cosine Transform (DCT) matrix is proposed and an assembler program for Digital Signal Processor is developed. In addition, a program to calculate DCT using Lee's algorithm for any matrix of the size 2M is created. The experimental results have proven that the decoder is able to stream and decode MP3 in real time.

  1. ISO/IEC 11172-3:1993 Information technology - Coding of moving pictures and associated audio for digital storage media at up to about 1,5 Mbit/s 1993.
  2. GADD, S., LENART, T. A hardware accelerated mp3 decoder with Bluetooth streaming capabilities. Master's thesis, Lund Institute of Technology, Sweden, 2001.
  3. LEE, B.G. A new algorithm to compute the discrete cosine transforms. IEEE Transactions on Acoustics, Speech and Signal Proces-sing. 1984, vol. 32, no. 6, p. 1243-1245.
  4. BRITANAK, V., RAO, K. R. A new fast algorithm for the unified forward and inverse mdct/mdst computation. Signal Processing. 2002, vol. 82,no. 3, p. 433-459.
  5. PAIK, W., HWANG, S. Design of a novel synthesis filter for real-time MPEG-2 audio decoder implementation on a DSP chip. IEEE Transaction on CE. 1999, vol. 45, no. 4, p. 1119-1129.

K. Fliegel [references] [full-text] [Download Citations]
Modeling and Measurement of Image Sensor Characteristics

The optical transfer function (OTF), as an objective measure of the quality of optical and electro-optical systems, is closely related to the point spread function (PSF) and other derived characteristics, such as the modulation transfer function (MTF) and the phase transfer function (PTF). The paper focused to the use a generalized OTF, which is primarily dedicated to the description of linear space invariant systems (LSI), for the purpose of sampled structures of image sensors (e.g. CCD, CMOS, CID), and to implement the derived results while utilizing the graphical user's interface (GUI) in Matlab. The model used considers the effects of the detector photo sensitive area, sampling process, as well as other CCD specific parameters, such as the charge transfer efficiency (CTE) or diffusion in order to derive the overall MTF shape. The paper also includes an experimental measurement in the real system and a comparison with the results of modeling.

  1. BOREMAN, G. D. Modulation transfer function in optical and electro-optical systems. SPIE PRESS, Bellingham (Washington), 2001.
  2. BARNARD, K. J., BOREMAN, G. D. Modulation transfer function of hexagonal staring focal plane arrays. Optical Engineering, 1991, vol. 30, no. 12, p. 1915-1919.
  3. HADAR, O., BOREMAN, G. D. Oversampling requirements for pixelated - imager systems. Optical Engineering, 1999, vol. 38, no. 5, p. 782-785.
  4. HOLST, G. C. CCD arrays, cameras and displays, SPIE PRESS, Bellingham (Washington), 1998.
  5. HOLST, G. C. Image quality: Does your detector match your optics? Photonics Spectra, 1999, vol. 33, no. 1, p. 144-146.
  6. GOODMAN, J. W. Introduction to Fourier Optics. McGraw-Hill, Boston, 1996.
  7. HUCK, F. O. et al. Electro-optical design for efficient visual com-munication. Optical Engineering, 1996, vol. 34, no. 1, p. 795-813.
  8. PARK, S. K. et al. Modulation-transfer-function analysis for sampled image systems. Applied Optics, 1984, vol. 23, no. 15, p. 2572-2582.
  9. FLIEGEL, K. Modeling of image sensor characteristics in Matlab. Master thesis, CTU FEE, Prague, 2004.

T. Karlubikova, J. Polec [references] [full-text] [Download Citations]
Extrapolation of Incomplete Image Data with Discrete Orthogonal Transforms

In image processing and transmission, interpolation and extrapolation are of great importance whenever missing pixels have to be filled in, and many methods have been proposed to solve this problem. In this paper we present a method for extrapolating the missing data with an existing set of basis functions of a selected orthogonal transform. The best extrapolation is found according to linear approximation theory as a weighted sum of basis functions, where coefficients of the sum are solutions of the derived matrix equation.

  1. CHAPMAN, M. The Karhunen-Loeve Transformation for GappyData. Colorado State University Dept. of Mathematics, 1999,
  2. KAUP, A. Object-Based Texture Coding of Moving Video inMPEG-4. IEEE Transactions on Circuits and Systems for VideoTechnology, 1999, vol. 9, no. 1.
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  4. KOLINGEROVA, I. Modified DAG Location for Delaunay Triangulation.In Computational Science - ICCS 2002, Part III, Amsterdam(Netherlands), LNCS 2331, Springer-Verlag, 2002, pp. 125-134.
  5. POLEC, J., PAVLOVICOVA, J. Generalised Interpolation of SegmentedImages Using Shape-Independent Orthogonal Transforms.In: 2001 International Conference on Image Processing ICIP 2001.Thessaloniki (Greece), 2001, pp. 888-890.
  6. VARGIC, R. Wavelet-Based Compression of Segmented Images. InProceedings EC-VIP-MC 2003. Zagreb (Croatia), 2003, pp.347-351.

D. Levicky, P. Foris [references] [full-text] [Download Citations]
Human Visual System Models in Digital Image Watermarking

In this paper some Human Visual System (HVS) models used in digital image watermarking are presented. Four different HVS models, which exploit various properties of human eye, are described. Two of them operate in transform domain of Discrete Cosine Transform (DCT) and Discrete Wavelet Transform (DWT). HVS model in DCT domain consists of Just Noticeable Difference thresholds for corresponding DCT basis functions corrected by luminance sensitivity and self- or neighborhood contrast masking. HVS model in DWT domain is based on different HVS sensitivity in various DWT subbands. The third presented HVS model is composed of contrast thresholds as a function of spatial frequency and eye's eccentricity. We present also a way of combining these three basic models to get better tradeoff between conflicting requirements of digital watermarks. The fourth HVS model is based on noise visibility in an image and is described by so called Noise Visibility Function (NVF). The possible ways of exploiting of the described HVS models in digital image watermarking are also briefly discussed.

  1. LEVICKY, D., FORIS, P., KLENOVICOVA, Z., SURIN, S.Sucasny stav a perspektivy vyuzitia digitalnych vodoznakov. InCofax - Telecommunications 2004, 10th International ScientificConference, 2004, p. 165 - 168.
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  6. WANG, Z., BOVIK, A. C. Foveation Scalable Video Coding withAutomathic Fixation Selection. IEEE Transactions on Image Processing,2003, vol. 12, no. 2, p. 1 - 12.
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  8. VOLOSHYNOVSKIY, S., HERRIGEL, A., BAUMGARTNER, N.,PUN, T. A Stochastic Approach to Content Adaptive Digital ImageWatermarking. In Proceedings of the Third International Workshopon Information Hiding, 1999, p.211-236.

J. Mihalik, V. Michalcin [references] [full-text] [Download Citations]
Texturing of Surface of 3D Human Head Model

The paper deals with an algorithm of texturing of the surface of 3D human head model. The proposed algorithm generates a texture consequently of several camera frames of the input video sequence. The texture values from the camera frames are mapped on the surface of the 3D human head model using perspective projection, scan line and 3D motion estimation. To decrease the number of camera frames a filling of empty places by a simple interpolation method has been done in the texture plane.

  1. Signal Processing: Image Communication. 2000, vol.15, no.4-5. (Tutorial Issue on MPEG-4 Standard).
  2. MIHALIK, J. Image Coding in Videocommunications. Kosice: Mercury - Smekal, 2001. ISBN 80-89061-47-8(in Slovak).
  3. MIHALIK, J., MICHALCIN, V. 3D Motion Estimation and Texturing of Human Head Model. Radioengineering, 2004, vol.13, no.1, p.26- 31, ISSN 1210-2512.
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R. Javurek [references] [full-text] [Download Citations]
Efficient Models for Objective Video Quality Assessment

Two models for objective assessment of compressed video quality and results from subjective and objective tests of several low bit-rate video coders are introduced in this paper. First model is based on mathematical measures that describe perception of video distortion by human eye. Second model for quality evaluation is based on human visual system (HVS) characteristics. Obtained quality values from both models have been compared with subjective results. Both models are computationally efficient and produce results that are correlated with subjective results.

  1. WINKLER, S. A perceptual distortion metric for digital color video.In Proc. SPIE, vol. 3644, pp. 175-184, San Jose (CA), 1999.
  2. VQEG: Final report from the Video Quality Experts Group on thevalidation of objective models of video quality assessment, 2000.
  3. WEBSTER, A. A., JONES, C. T., PINSON, M.H., VORAN, S. D.,WOLF, S. An objective video quality assessment system based onhuman perception. In SPIE Human Vision, Visual Processing anddigital display IV, vol. 1913, pp. 15-26, San Jose (CA), February1993.
  4. ITU-R Recommendation BT.500-11: Methodology for the subjectiveassessment of the quality of television pictures, InternationalTelecommunication Union, Geneva, Switzerland, 2002.
  5. LAMBRECHT, C. J. VAN DEN BRANDEN. Perceptual Modelsand Architectures for Video Coding Applications. Ph.D. thesis,Ecole Polytechnique Federale de Lausanne, Switzerland, 1996.
  6. WANG, Z., LU, L., BOVIK, A.C. Video quality assessment based onstructural distortion measurement, submitted to Signal Processing:Image Communication, special issue on "Objective video qualitymetrics", 2003.
  7. WATSON, A.B., HU, J., McGOWAN, J. F. III. DVQ: A digitalvideo quality metric based on human vision, Journal of ElectronicImaging, 2001, vol. 10, no. 1, pp. 20-29.
  8. DALY, S. The visible differences predictor: An algorithm for theassessment of image fidelity. In: A. B. Watson (ed.), Digital Imagesand Human Vision, pp. 179-206, MIT Press, 1993.

M. Turi Nagy, G. Rozinaj [references] [full-text] [Download Citations]
An Analysis/Synthesis System of Audio Signal with Utilization of an SN Model

An SN (sinusoids plus noise) model is a spectral model, in which the periodic components of the sound are represented by sinusoids with time-varying frequencies, amplitudes and phases. The remaining non-periodic components are represented by a filtered noise. The sinusoidal model utilizes physical properties of musical instruments and the noise model utilizes the human inability to perceive the exact spectral shape or the phase of stochastic signals. SN modeling can be applied in a compression, transformation, separation of sounds, etc. The designed system is based on methods used in the SN modeling. We have proposed a model that achieves good results in audio perception. Although many systems do not save phases of the sinusoids, they are important for better modelling of transients, for the computation of residual and last but not least for stereo signals, too. One of the fundamental properties of the proposed system is the ability of the signal reconstruction not only from the amplitude but from the phase point of view, as well.

  1. SPANIAS, A. Speech coding: A tutorial review. In Proceedings ofthe IEEE. 1994, vol. 82, no. 10. p. 1541-1582.
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  17. TURI NAGY M., ROZINAJ G., November2004.

M. Gamcova, S. Marchevsky, J. Gamec [references] [full-text] [Download Citations]
Higher Efficiency of Motion Estimation Methods

This paper presents a new motion estimation algorithm to improve the performance of the existing searching algorithms at a relative low computational cost. We try to amend the incorrect and/or inaccurate estimate of motion with higher precision by using adaptive weighted median filtering and its modifications. The median filter is well-known. A more general filter, called the Adaptively Weighted Median Filter (AWM), of which the median filter is a special case, is described. The submitted modifications conditionally use the AWM and full search algorithm (FSA). Simulation results show that the proposed technique can efficiently improve the motion estimation performance.

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  5. ALPARONE, L,. SANTURRI L. Weighted Median Refinement of Motion Vectors in H.263-Based Video Coding. In IEEE Packet Video Workshop. Forte Village, Cagliari (Italy), May 2000.
  6. ALPARONE, L., BARNI, M,. BARTOLINI, F., CAPPELINI, V. Adaptively Weighted Vector-Median Filters for Motion Fields Smooting. In Proceeding of IEEE International Conference on Acoustics Speech and Signal Processing ICASSP"96. Atlanta (Georgia, U.S.A.), 1996, p.2267-2270.
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J. Turan, L. Ovsenik, M. Benca, J. Turan jr. [references] [full-text] [Download Citations]
Implementation of CT and IHT Processors for Invariant Object Recognition System

This paper presents PDL or ASIC implementation of key modules of invariant object recognition system based on the combination of the Incremental Hough transform (IHT), correlation and rapid transform (RT). The invariant object recognition system was represented partially in C++ language for general-purpose processor on personal computer and partially described in VHDL code for implementation in PLD or ASIC.

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V. Ricny [references] [full-text] [Download Citations]
Laboratory of Digital Video and Television Technology

This short paper provides information on the technical instrumentation and application possibilities of the newly installed laboratory of digital video and television technology at the Department of Radio Electronics FEEC BTU in Brno . This laboratory can be used for laboratory education and research.

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E. Kadlecova, P. Fiala [references] [full-text] [Download Citations]
New Directions in Modeling the Lighting Systems

This paper presents information about new directions in the modeling of lighting systems, and an overview of methods for the modeling of lighting systems. The new R-FEM method is described, which is a combination of the Radiosity method and the Finite Elements Method. The paper contains modeling results and their verification by experimental measurements and by the Matlab simulation for this R-FEM method.

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