Subway tunnel guided electromagnetic wave ... - IEEE Xplore

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IEEE TRANSACTIONS ON ANTENNAS AND PROPAGATION, VOL. 49, NO. 11, NOVEMBER 2001

Subway Tunnel Guided Electromagnetic Wave Propagation at Mobile Communications Frequencies Dirk Didascalou, Member, IEEE, Jürgen Maurer, Student Member, IEEE, and Werner Wiesbeck, Fellow, IEEE

Abstract—A measurement campaign has been carried out in the Berlin subway to characterize electromagnetic wave propagation in underground railroad tunnels. The received power levels at 945 and 1853.4 MHz are used to evaluate the attenuation and the fading characteristics in a curved arched-shaped tunnel. The measurements are compared to ray-optical modeling results, which are based on ray density normalization. It is shown that the geometry of a tunnel, especially the cross-sectional shape and the course, is of major impact on the propagation behavior and thus on the accuracy of the modeling, while the material parameters of the building materials have less impact. Index Terms—Geometrical optics, measurements, mobile communications, ray launching, ray tracing, subway, tunnels, wave propagation.

I. INTRODUCTION

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O characterize electromagnetic wave propagation in underground railroad tunnels in the GSM900 and GSM1800 frequency bands, a measurement campaign has been carried out in the Berlin subway. Two tunnels of different shape, length, and building materials are investigated. Furthermore, different transmitting antenna positions are analyzed. The received power levels at 945 and 1853.4 MHz are used to evaluate the attenuation and the fading characteristics of the different constellations and environments. It is shown from the comparison of experimental results with simulations that the generally nonflat boundary of subway tunnels has a major impact on the propagation behavior. It is also shown that the use of standard analytical probability density functions to characterize the fast fading in subway tunnels is very restrictive. The tendency of accumulation of energy on the outer sides of curves is observed in both measurements and simulation results. This paper is organized as follows. The simulation approach is briefly introduced in Section II, which is followed by the description of the measurement equipment, the procedure, and the geometry of the examined tunnels in Section III. The major part of the paper (Section IV) is devoted to the comparison of experimental and theoretical results. First, the achievable accuracy of the modeling is determined in Section IV-A using the simplest geometry: a straight rectangular tunnel section. Then, the performance of the modeling in a more complex scenario, a curved arched-shaped tunnel, is quantized in Section IV-B. The influence of the curvature, i.e., the arched-shaped cross-section and the longitudinal bends, is evaluated in Section IV-C and Manuscript received September 29, 2000; revised January 17, 2001. The authors are with the Institut für Höchstfrequenztechnik und Elektronik (IHE), Universität Karlsruhe (TH), 76128 Karlsruhe, Germany (e-mail: [email protected]). Publisher Item Identifier S 0018-926X(01)07645-1.

-D. Afterwards, the usefulness of analytical probability density functions in the description of the fast fading is investigated in Section IV-E. Finally, Section IV-F deals with the distribution of power in curves. II. THE SIMULATION APPROACH The difficulties of wave propagation modeling in tunnels are due to the predominant nonflat geometry of the tunnels’ boundaries, i.e., arched-shaped cross-sections and curves. Conventional ray-tracing techniques, based on ray launching [1], imaging [2]–[5], or a combination of both [6], [7], have in common that they can only treat reflections at plane boundaries. The reason for this is the so-called multiple ray problem [8], where adjacent rays are too closely spaced to be considered as independent [9]. The multiple ray problem can be overcome as indicated in [10]–[13]—at least considering exclusively planar geometries. To handle realistic curved geometries, the concept of ray density normalization (RDN) was introduced recently. Consequently, a ray-optical modeling approach, based on stochastic ray launching with ray density normalization, is used for all simulations. The method is intensively treated in [14] and [8]. It allows the simulation of wave propagation of high-frequency electromagnetic waves in arbitrarily shaped tunnels. The geometry of the tunnel cross sections, the course of the tunnels, and building materials, as well as the positions, velocities, and directional patterns of the transmitting and receiving antennas, are taken into account by the simulation approach. III. MEASUREMENT SETUP AND PROCEDURE A. Measurement Equipment The measurements were performed using a Ballmann STX-GSM 2 GSM900 test transmitter, a Rhode & Schwarz SME 23 GSM1800 test transmitter, and two Rhode & Schwarz extended test receivers ESVD for digital mobile radio networks. The transmitters generated two harmonic signals at MHz and MHz, respectively. The intermediate frequency (IF) measurement bandwidth was 10 kHz. For the GSM900 band, a log-periodic (LogPer) vertically polarized transmitting antenna with 12 dBi gain was used (Kathrein K73226), whereas for the GSM1800 band, a wide-band Yagi antenna with 17 dBi gain (Jaybeam J7360) was employed. Both are standard antennas for the deployment in tunnel environments. As receiving antennas, two 4-monopoles were chosen due to their omnidirectional antenna patterns. The battery-driven receivers were mounted on a lorry, which was manually pulled through the tunnels

0018–926X/01$10.00 © 2001 IEEE

DIDASCALOU et al.: SUBWAY TUNNEL GUIDED ELECTROMAGNETIC WAVE PROPAGATION

Fig. 1.

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Measurement setup with transmitting antennas and receiving equipment mounted on a lorry with an optical pulse generator.

at an average speed of 1.5 m/s. The measurements were recorded approximately every 30 cm, where each measured value corresponds to the averaged received signal during a 10-ms time interval. The actual measurement location was retrieved with a pulse-generator coupled to a wheel of the lorry (see Fig. 1). Each measurement was run and recorded twice in order to determine the time variance of the transmission channel. Furthermore, the two corresponding measurements were compared and aligned to each other to ensure a reasonable precision in the absolute location of the measured values. This was necessary due to the imprecise performance of the pulse generator, which provided an impulse approximately every 17.9 cm with a precision of 0.5 cm. The positions of the transmitting antennas were varied for each measurement. The receiving monopoles were fixed on the lorry at a height of m above the rails. The measured path loss has been deduced from the ratio of the measured received power to the input power of the transmitting antennas, including the antennas’ characteristics. The attenuation of the connecting cables was taken into account, and an additional 1.5 dB loss was assumed for any kind of mismatch in both the receiving and the transmitting branches. B. Measurement Environment Two different tunnels are investigated: 1) a short, straight, rectangular, wide-profile single-lane tunnel section (part of subway U5 between Friedrichsfelde and Tierpark), built in the early 1970s; 2) a curved arched, single-lane tunnel (subway U8 between Karl–Bonhoeffer–Nervenklinik and Rathaus Reinickendorf), built in the late 1980s. The width of the rectangular tunnel section is 3.8 m, its height m, and its length m. The main building material is reinforced concrete, the side walls are covered by a variety of cables (e.g., power supply and phone lines) and mountings. The rail sleepers lie on gravel. The roughness of the cm and the roughness of the floor walls was estimated to cm. to

The cross-section of the arched tunnel is constituted by a circular shape of radius m with an elevated floor 1.2 m above the lowest point of the circle (see Fig. 3). A schematic plot of the tunnel’s course is shown in Fig. 2. It consists of nine different sections and can roughly be described by a first straight part, followed by a left bend with large radius of curvature and a right bend with smaller radius of curvature. The total length m and the maximum measured of the tunnel is m. At distances m from the distance is transmitter, the receiver and the transmitter no longer have a dim from rect line-of-sight (LOS). At a distance of the transmitter, an open connection (fire exit) exists for security reasons between the actual and a second tube, which runs in parallel, extending over an area of approximately 25 m (see Fig. 2). Fig. 3 depicts the view into the tunnel from the station Karl–Bonhoeffer–Nervenlinik, with the transmitters situated at the beginning of the tube. It is apparent from Fig. 3 that the walls are not smooth but that they have a periodic structure due to the special construction by screwed prefabricated elements. Consequently, the occurring (large scale) height variations of the tunnel walls are not resulting from a statistically rough surface in a strict sense, but rather from a periodically rough surface.1 Nevertheless, the concept of rough surface scattering can be applied in an approximate way by adapting the mean roughness of the walls with growing distances: at small distances from the transmitter, where most rays impinge under oblique incidence (i.e., with small incident angles) onto the walls, a mean roughness cm is assumed, corresponding to the estimated of roughness of the walls. At larger distances, where most rays impinge under near-grazing incidence onto the walls, the mean roughness—and thus the attenuation—is increased (up cm, approximately half of the height variations of to the different levels of the prefabricated elements) to reflect the shadowing behavior of the special wall structure. This approach influences the overall path loss significantly. 1A periodically rough surface generally results in scattering patterns with specific preferential directions.

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Fig. 2. Schematic course plot of the arched shaped tunnel (U8), with a total length of l

1079 m.

(a)

Fig. 3. View into the arch-shaped tunnel (U8) of Fig. 2 from Karl–Bonhoeffer–Nervenlinik (d = 0 m).

For both tunnels, the parameters of the building materials in ). The the simulation correspond to dry concrete ( roughness of the walls is taken into account by the modified Fresnel reflection coefficients.

IV. RESULTS In both tunnels, several transmitting antenna constellations were measured at the two frequencies. First, the short straight tunnel section (U5) is considered. In this rectangular geometry, image theory, as a ray-optical reference solution, can be used to determine the achievable accuracy by simulations. Thereafter, the measurements in the curved tunnel with arched cross-section (U8) are used in exemplary analyses. A. Achievable Accuracy in The Rectangular Straight Tunnel (U5) Fig. 4 depicts the measured and predicted path loss in the straight rectangular tunnel (U5) for two different constellations. For Fig. 4(a), the transmitting GSM900 antenna was situated m, 0.88 m to the left of the tunnel at a height of center. For the scenario in Fig. 4(b), the transmitting GSM1800 m, 0.04 m to the antenna was situated at a height of right of the center. The predicted path loss was calculated by image theory at 200 receiver locations for up to ten reflections

(b) Fig. 4. Comparisons of measurements and predictions in the straight rectangular-shaped tunnel section (U5) with different transmitter positions at f = 945 MHz and f = 1853:4 MHz. Running rms window length for the measurement: 1 m (whereas for the prediction, no rms generation is performed due to a reception-sphere spacing of 0.5 m). (a) GSM900 and (b) GSM1800.

per ray. The simulation time was a few minutes on a standard HP workstation. To quantify the agreement of predictions and and standard deviations of measurements, mean values the difference (in dB) between the measured and the predicted losses are determined. The values are obtained either by a direct “raw” comparison, indicated by the subscript , or after a previous running root mean square (rms) generation (see Secand leading to and tion IV-E), indicated by the subscript . The imperfect match of the measurements and predictions is due to the irregular structure of the tunnel, modeled as being


=

Fig. 5. Comparison of measurement and simulation at f 945 MHz. Running rms window length: 40 (right transmitting antenna in Fig. 3).

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Fig. 6. Comparison of measurement and simulation at f = 1853:4 MHz. Running rms window length: 60 (left transmitting antenna in Fig. 3).

straight and rectangular. The mean values and standard deviations obtained in this grossly simplified scenario serve as benchmarks for the following comparisons. In the remainder of this paper, the curved tunnel of Figs. 2 and 3 is examined. B. Path Loss in the Curved Arch-Shaped Tunnel (U8) In the curved arch-shaped tunnel, several transmitter locations were deployed. Figs. 5 and 6 depict the comparisons for the configuration shown in Fig. 3. The GSM900 antenna was situated at a height of m, 0.98 m to the right of the tunnel’s center (right transmitting antenna in Fig. 3). The GSM1800 antenna was positioned at m, 0.93 m to the left of the center (left transmitting antenna in Fig. 3). The receiving antennas were aligned accordingly with the GSM900 monopole on the right side and the GSM1800 monopole on the left side of the lorry. The path loss was simulated by the RDN-based ray-tracing method. One hundred fifty million rays were traced with up to 40 reflections. The calculation time for the 1600 receivers was about 40 h on a standard HP workstation. The good agreement of the measured and the predicted path loss validates the RDN modeling approach. dB in Fig. 5 and The small mean errors ( dB in Fig. 6) and standard deviations ( dB in Fig. 5 dB in Fig. 6) emphasize the good performance of and the model, especially bearing in mind the imprecise assignment of the absolute measurement location (see Section III-A). C. Influence of Curves on the Simulation Accuracy To determine the influence of the curves on the propagation behavior, the same measurements as depicted in Fig. 6 (sceMHz) are compared with the simulanario at tions, where the bend of the tunnel is approximated by a straight line. This is a commonly made approximation for tunnels with slight bends [4]. Compared to the simulation of the actual curved course in Fig. 6, one can clearly distinguish the deviation of the prediction from the measurement in Fig. 7. For distances m, the deviation becomes noticeable, which is the region where the left bend of the tunnel starts. Although the ram, dius of curvature of the left bend is as large as

Fig. 7. Comparison of measurement and simulation of Fig. 6 but assuming a fictitious straight tunnel course for the simulation.

the deviation is rather significant. The predicted mean level is increased by 7 dB and the standard deviation is almost doubled. This example shows the importance of an adequate modeling of a tunnel’s curvature, made possible by the RDN-based techniques [14], [8]. D. Influence of the Cross-Sectional Shape on the Simulation Accuracy It is commonly assumed that the actual shape of the crosssection is of minor influence on the propagation behavior in a tunnel, as long as its actual cross-sectional area is preserved [15], [16]. Fig. 8 shows comparisons of the GSM1800 scenario in Fig. 3 on the first 100 m with different cross-sectional shapes used for the simulations. In addition to the arched cross sec2.675 m tion, a pure circular cross section with radius m and height and a rectangular cross-section of width m are applied, all covering the same area. The mean errors and standard deviations are calculated on the first 100 m. Again, it turns out that the correct modeling of the tunnel’s cross-section affects the accuracy of the modeling results significantly.

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Fig. 8. Comparison of measurement and simulation with arched, circular, and 0:0 dB, = 3:2 dB; circular: rectangular cross-section. Arched: = 1:5 dB, = 6:3 dB; rectangular: = 1:8 dB, = 6:8 dB. Parameters according to Fig. 6. f = 1853:4 MHz. Running rms window length: 1 m (replot of Fig. 6 on the first 100 m).

=

Fig. 9. LMS best fit pdfs for the measurement of Fig. 6. RMS window length: 60 .

E. Fast-Fading Characteristics An interesting question is whether the fast fading in a tunnel can be characterized by a standard probability density function (pdf). The fast fading envelope is obtained by normalizing the received signal to its local rms value. Usually, a window length of at least 40 wavelengths is chosen for the rms determination in a mobile environment [17], [18]. The value of 40 is used in the following comparisons, although the value itself is not very critical. The resulting fading envelope is compared to the following classical distribution functions: Gaussian (normal), lognormal, Nakagami, Rayleigh, Rician, and Weibull [19], [20]. To determine the parameters of the respective distributions, a least mean square (LMS)-based parameter fitting can be used [21]. The LMS optimization is based on a simplex method [22]. As an example, Fig. 9 shows the results of the LMS optimization for the DCS1800 measurement2 of Fig. 6. 2Generally, a sampling of at least =2 is required for a nonambiguous fast fading characterization. This requirement is clearly violated by the performed measurements. Nevertheless, for all GSM900 and GSM1800 measurements, the obtained fading characteristics led to similar results.

Fig. 10. Chi-square best fit pdfs for the measurement of Fig. 6. RMS window length: 60 .

The best fits for all measurements are achieved using Rician distributions at both frequencies, which is congruent with the literature [23]. Nevertheless, except for the Rayleigh distribution, all other densities lead to similar results, as indicated by Fig. 9. The interesting area of the curves, however, is in the lower range corresponding to very low received signal levels, the so-called deep fades. In this region, none of the curves obtained by the LMS optimization leads to satisfactory results. Another way to determine the parameters of the various densities is given by a recursive application of the chi-square goodness-of-fit test [24], [18]. The chi-square test is particularly suited for a fitting in the area of low received values due to its sensitivity in regions of low probability. Fig. 10 shows the results for the pdfs obtained by a simplex optimization with the chi-square criterion. The fitted curves approximate the measurement for low received values more closely for the chi-square fitting compared to the LMS fitting (Fig. 10 compared to Fig. 9). However, an overall match could not be achieved by either of the analytical densities. Consequently, a complete characterization of the fast-fading characteristics in a tunnel by standard analytical density functions appears to be impossible. In contrast, the pdf extracted from the prediction in Fig. 6 approaches the mea. The corresurement more closely over the entire range of sponding predicted curves are drawn in the two figures, marked by black diamonds (and “ray tracing”). F. Distribution of the Propagating Power in Curves In the curved subway tunnel, a rapid decrease of the received power level at the inner side of a curve is observed. The measurement in the GSM900 band plotted in Fig. 5 was performed over the total length of the subway tunnel. As already indicated, the receiving monopole was situated on the right side of the tunnel axis referring to Fig. 3. Therefore, following the tunnel’s course depicted in Fig. 2, the receiver was on the outer side in the left curve and, consequently, on the inner side in the following right curve at the end of the tunnel. The averaged measured path loss is plotted in Fig. 11. At 850 to 950 m from the transmitter, the curve is dropping by almost 8 dB. This is the area of the right bend, with the receiver situated at the inner side of the curve.


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fading in tunnels cannot be characterized by standard analytical probability density functions over the entire range of values. The densities derived from propagation modeling provide a superior fit. The tendency of accumulation of energy on the outer sides of curves—also known as whispering gallery effect [27]—is observed in both measurements and simulation results. ACKNOWLEDGMENT The authors would like to thank E-Plus, Germany, and Mannesmann Mobilfunk, Germany, for the provision of the measurement equipment and the Berlin Subway Carrier (BVG) for their support and assistance during the measurement campaign. Fig. 11. Mean propagating power through the curved tunnel calculated by ray-tracing, compared to the averaged measurement of Fig. 5 at f 945 MHz (rms window length: 200 ).

=

In the same figure, the mean path loss predicted by ray-tracing is indicated by the dotted line. The mean path loss is obtained by summing the powers of the multipath components at the receiver instead of the respective complex voltages (also termed power-sum) [25]. Furthermore, the entire cross-section is used as the area of analysis, which speeds up the simulation time considerably [26]. Although the overall propagation slope is predicted very well, the defocusing effect can obviously not be predicted by this integral method. To detect such a shift of energy, the area of analysis is split. Instead of working on the total cross-section of the tunnel, the method is now applied separately on the left and the right halves of the cross-section. The power flux in the right half, shown by the curve with the black diamonds in Fig. 11, follows the measurement quite closely. Furthermore, the power flux in the left half is drawn in the figure. On the first 350 m, where the tunnel is approximately straight, the energy is equally distributed on both sides of the tunnel. In the left curve (between 350 and 800 m), the energy is focused on the right half of the tunnel. In the following right bend, the energy is shifted from the inner (right) side of the curve to the outer (left) side of the curve. The break-even point is at about 900 m from the transmitter, after which most of the energy is gathered in the left tunnel half. This result again indicates the effect of curves on the propagation behavior, namely, the focusing of energy on the outer side of curves, and the requirement for an appropriate modeling approach. V. CONCLUSION Comparing measurements and simulations of electromagnetic-wave propagation in the Berlin subway, it is shown that the geometry of tunnels, especially the cross-sectional shape and curves, has a major impact on the propagation behavior. To obtain accurate path-loss predictions, it is mandatory to describe the special geometry of tunnels in propagation modeling adequately. It is proven that even only slight bends increase the overall attenuation in a tunnel significantly. Thus a simple straight-line approximation for a curved tunnel’s course is clearly insufficient. It is also shown that the fast

REFERENCES [1] Y. P. Zhang, Y. Hwang, and R. G. Kouyoumjian, “Ray-optical prediction of radio-wave propagation characteristics in tunnel environments—Part II: Analysis and measurements,” IEEE Trans. Antennas Propagat., vol. 46, pp. 1337–1345, Sept. 1998. [2] P. Mariage, “Etude théorique et expérimentale de la propagation des ondes hyperfréquences en milieu confiné ou urbain,” Ph.D. dissertation (in French), Université de Lille, France, 1992. [3] B. Rembold, “Simulation of radio transmission in a tunnel” (in German), Frequenz, vol. 47, no. 11/12, pp. 270–275, 1993. [4] T. Klemenschits, “Mobile communications in tunnels,” Ph.D. dissertation, Universität Wien, Austria, 1993. [5] P. Mariage, M. Lienard, and P. Degauque, “Theoretical and experimental approach of the propagation of high frequency waves in road tunnels,” IEEE Trans. Antennas Propagat., vol. 42, pp. 75–81, Jan. 1994. [6] S.-H. Chen and S.-K. Jeng, “An SBR/image approach for indoor radio propagation in a corridor,” IEICE Trans. Electron., vol. E78-C, no. 8, pp. 1058–1062, 1995. , “SBR image approach for radio wave propagation in tunnels with [7] and without traffic,” IEEE Trans. Veh. Technol., vol. 45, pp. 570–578, May 1996. [8] D. Didascalou, T. M. Schäfer, F. Weinmann, and W. Wiesbeck, “Ray density normalization for ray-optical wave propagation modeling in arbitrarily shaped tunnels,” IEEE Trans. Antennas Propagat., vol. 48, pp. 1316– 1325, Sept. 2000. [9] G. A. Deschamps, “Ray techniques in electromagnetics,” Proc. IEEE, vol. 60, pp. 1022–1035, Sept. 1972. [10] W. Honcharenko, H. L. Bertoni, J. L. Dailing, J. Qian, and H. D. Yee, “Mechanisms governing UHF propagation on single floors in modern office buildings,” IEEE Trans. Veh. Technol., vol. 41, pp. 496–504, July 1992. [11] S. Y. Seidl and T. S. Rappaport, “Site-specific propagation prediction for wireless in-building personal communication system design,” IEEE Trans. Veh. Technol., vol. 43, pp. 879–891, July 1994. [12] D. J. Cichon, T. Zwick, and J. Lähteenmäki, “Ray optical indoor modeling in multi-floored buildings: Simulations and measurements,” in Proc. IEEE Antennas Propagation Society Int. Symp. (AP-S’95), Newport Beach, CA, June 1995, pp. 522–525. [13] H. Suzuki and A. S. Mohan, “Ray tube tracing method for predicting indoor channel characteristics map,” Electron. Lett., vol. 33, no. 17, pp. 1495–1496, 1997. [14] D. Didascalou. (2000) Ray-optical wave propagation modeling in arbitrarily shaped tunnels. Ph.D. dissertation, Universität Karlsruhe (TH), Germany. [Online] http://www.ubka.uni-karlsruhe.de/cgi-bin/psview?document=2000/elektrotechnik/2 [15] Y. Yamaguchi, T. Abe, T. Sekiguchi, and J. Chiba, “Attenuation constants of UHF radio waves in arched tunnels,” IEEE Trans. Microwave Theory Tech., vol. MTT-33, no. 8, pp. 714–718, 1985. [16] Y. P. Zhang and Y. Hwang, “Characterization of UHF radio propagation channels in tunnel environments for microcellular and personal communications,” IEEE Trans. Antennas Propagat., vol. 47, no. 1, pp. 283–296, 1998. [17] W. C. Y. Lee, Mobile Communications Engineering: McGraw-Hill, 1982. [18] R. Steele, Ed., Mobile Radio Communications. London, U.K.: Pentech, 1992.

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[19] “Probability distributions relevant to radiowave propagation modeling,” International Telecommunications Union (ITU), Geneva, ITU-R Rec. PN.1057, 1994. [20] J. G. Proakis, Digital Communications, 2nd ed. New York: McGrawHill, 1989. [21] R. Kattenbach and T. Englert, “Auswertung statistischer Eigenschaften von Impulsantworten zeitvarianter Indoor-Funkkanäle” (in German), Kleinheubacher Berichte, vol. 39, pp. 321–332, 1995. [22] J. A. Nelder and R. Mead, “A simplex method for function minimization,” Comput. J., vol. 7, pp. 308–313, 1964/1965. [23] M. Lienard and P. Degauque, “Propagation in wide tunnels at 2 GHz: A statistical analysis,” IEEE Trans. Veh. Technol., vol. 47, pp. 1322–1328, July 1998. [24] A. Papoulis, Probability, Random Variables and Stochastic Processes, 2nd ed. New York: McGraw-Hill, 1984. [25] N. Geng and W. Wiesbeck, Planungsmethoden für die Mobilkommunikation, Funknetzplanung unter realen physikalischen Ausbreitungsbedingungen (in German). Berlin, Germany: Springer, 1998. [26] J. S. Lamminmäki and J. J. A. Lempiäinen, “Radio propagation characteristics in curved tunnels,” Proc. Inst. Elect. Eng. Microwaves, Antennas and Propagat., vol. 145, no. 4, pp. 327–331, 1998. [27] J. R. Wait, “Electromagnetic whispering gallery modes in a dielectric rod,” Radio Sci., vol. 2, no. 9, pp. 1005–1007, 1967.

Dirk Didascalou (M’96) was born in Hamburg, Germany, in 1969. He received the Dipl.-Ing. (M.S.E.E.) and Dr.-Ing. (Ph.D.) degrees in electrical engineering from the Universität Karlsruhe (TH), Germany, in 1996 and 2000, respectively. He took part in the joint Electronic Engineering Degree Scheme within Europe: Paris–Southampton–Karlsruhe (TRIPARTITE). From 1996 to 2000, he was with the Institut für Höchstfrequenztechnik und Elektronik (IHE) at the Universität Karlsruhe (TH) as a Research Assistant. His research activities were focused on millimeter-wave propagation, mobile-to-mobile communications, mobile broadband links, and wave propagation in tunnels. He also participated as an expert in the European COST 259. Since 2000, he has been with Siemens Mobile Phones in Munich, Germany, where he coordinates the standardization activities of Siemens Mobile Phones in the Services and System Aspects (SA) Technical Specification Group of 3GPP, the international standardization organization for UMTS and GSM. For the Carl Cranz Series on scientific education, he served as a lecturer of em-wave propagation and radio network planning.

Jürgen Maurer (S’99) was born in Mannheim, Germany, in 1972. He received the Dipl.-Ing. (M.S.E.E.) degree in electrical engineering from the Universität Karlsruhe (TH), Germany, in 1999. In 1997, he spent six months as an Intern at the Alaska SAR Facility (ASF) working on digital image processing and the calibration of ASF’s SAR processor. Since 1999, he has been with the Institut für Höchstfrequenztechnik und Elektronik (IHE) at the Universität Karlsruhe (TH) as a Research Assistant. His research activities are presently focused on millimeter-wave propagation modeling for fixed wireless access systems and mobile-to-mobile communications. He is participating as an Expert in the European COST259.

Werner Wiesbeck (SM’87–F’94) received the Dipl.-Ing. (M.S.E.E.) and Dr.-Ing. (Ph.D.E.E.) degrees from the Technical University Munich, Germany, in 1969 and 1972, respectively. From 1972 to 1983, he was with AEG-Telefunken in various positions, including Head of R&D of the Microwave Division in Flensburg and Marketing Director Receiver and Direction Finder Division, Ulm. During this period, he had product responsibility for millimeter-wave radars, receivers, direction finders, and electronic warfare systems. Since 1983, he has been Director of the Institut für Höchstfrequenztechnik und Elektronik (IHE) at the Universität Karlsruhe (TH), Germany. Research topics include radar, remote sensing, wave propagation, and antennas. In 1989 and 1994, respectively, he spent a six-month sabbatical at the Jet Propulsion Laboratory, Pasadena. He has been General Chairman of the 1988 Heinrich Hertz Centenial Symposium and the 1993 Conference on Microwaves and Optics (MIOP’93). He has been a member of scientific committees of many conferences. For the Carl Cranz Series for Scientific Education, he serves as a Permanent Lecturer for Radar System Engineering and for Wave Propagation. He is a member of an Advisory Committee of the EU-Joint Research Centre (Ispra/Italy). He is an Advisor to the German Research Council (DFG), the Federal German Ministry for Research, and industry in Germany. Dr. Wiesback is President of the IEEE GRS-S (2000–2001), a member of the IEEE GRS-S AdCom (1992–2001), past Chairman of the GRS-S Awards Committee (1994–1998), past Executive Vice President of the IEEE GRS-S (1998–1999), past Associate Editor of the IEEE TRANSACTIONS ON ANTENNAS AND PROPAGATION (1996–1999), and past Treasurer of the IEEE German Section.