Modeling of Cooperative MIMO Channels in Urban Areas 1,4 Vodafone
Carsten Jandura1 , Martin Kaeske2 , Jens Voigt3 and Gerhard P. Fettweis4 Chair Mobile Communication Systems, Technical University of Dresden, Germany {carsten.jandura, fettweis}@ifn.et.tu-dresden.de, 2 Ilmenau University of Technology,
[email protected] 3 Actix GmbH, Dresden,
[email protected]
Abstract—Multiple-Input Multiple-Output (MIMO) technology is ready for deployment in commercial cellular networks in the very near future. Therefore, the need of incorporating this technology into radio network planning and optimization tools rises dramatically for network operators. In this contribution we show results of the validation of advanced ray tracing simulations with channel sounding measurements in the 2.53 GHz frequency band. These measurements were carried out inside the EASY-C project with the objective to learn more about coordinated multipoint (CoMP) transmission in a real world testbed. We compare the results of the ray tracing simulations with processed channel sounding measurements at specific points in an urban environment As result we can conclude that carefully performed Geometrical Optics based ray-tracing simulations are a suitable prediction model to reflect main characteristics of these scenarios. A further objective of these experiments is to get insight into the physical structure of the radio channel.
I. I NTRODUCTION
We simulate the single-input single-output (SISO) channel impulse response using a ray launching algorithm operating in a 3D environment model as a deterministic channel model. A high resolution building model is placed on top of a digital elevation model (DEM) and transmit (TX) antennas were set to the real world positions. The algorithm regards a bundle of rays, emanating from a transmitter source using a transmit angle interval of 1◦ that are all traced along until their field strength falls below a defined threshold. For every launched ray the nearest obstacle in the current propagation direction is determined. Once a ray hits an obstacle the ray launching algorithm includes the radio wave propagation effects specular reflection and diffraction in its ongoing calculation based on the algorithms of Geometrical Optics and the Uniform Theory of Diffraction. Furthermore a diffuse scattering model [3] considers effects on rough surfaces. This algorithm calculates the properties of the electromagnetic field, the complex polarimetric amplitudes, direction of departure (DOD), direction of arrival (DOA), and time delay of arrival (TDOA) for every transmitter–receiver combination. Receivers are modeled by horizontal square planes with a lateral size arx of several meters. The electrical beam pattern of the transmit and receiver antennas are included in the ray tracing algorithm. The direct result of the ray launching algorithm is the time–invariant (one sample point) complex polarimetric impulse response of a SISO radio channel. It can be described as: X −j2πcτk hSISO (τ ) = akq,p exp δ (τ − τk ) · λ k δ θTx − θkTx · δ φTx − φTx · k Rx Rx Rx Rx δ θ − θ k · δ φ − φk (1)
The increasing demand for data transmission in cellular networks leads to the specification of the 3GPP LTE standard. Within these mobile communication system a new physical layer with the multiple access scheme orthogonal frequency division multiplexing (OFDM) in the downlink, single carrier frequency division multiple access (SC-FDMA) in the uplink and the capacity increasing MIMO technology was specified. The target data rates for this system are up to 300 MBit/s using four antennas at transmit and receive side [1]. The problem of low signal to interference and noise ratio (SINR) at the cell edges with a bad user experience in terms of data throughput still remains. One transmission strategy, called CoMP is discussed as the way to get rid of this phenomenon. Within the German research project EASY-C [2] these communication strategies are studied at link and system level. One part of the project is the channel modeling and verification for cooperating base stations and the comparison with measured channel impulse responses inside a large scale testbed. These results are important for the radio and -fixed network planning of next generation mobile communication networks. This paper shows the influence of the network design of the possible cooperating areas and compare simulation results with measurement data collected in the EASY-C testbed in downtown Dresden.
with k as path index between transmitter and the receiver, τk as propagation delay and akq,p as complex–polarimetric attenuation coefficient on path k, the indices q, p are denoting the polarization, co- or cross polarized. λ as the carrier wave length and c as the velocity of light. In order to extend the ray tracing result towards a MIMO channel impulse response matrix, the antenna type has to be taken into account [4].
II. M ODELING A PPROACH
III. S IMULATION R ESULTS
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IV. M EASUREMENTS The verification of the ray launching simulation results is based on a channel sounding measurement campaign carried out in August 2008 in Dresden [5] as part of the EASY–C project. Three commercially used base station sites where equipped with commercial +18 dBi base station (BS) antennas (Kathrein 80010541) with two cross-polarized ports ±45◦ in a standard tree-fold sectorization. The map in Figure 1 shows the deployment and measurement scenario around Dresden main station. The antenna heights or BS1, BS2 and BS3 where 54m, 34m and 51m respectively. The area is typical urban characterized by streets surrounded by buildings of 30 m to 50 m height. All sector antennas at one site have been fed like a single cross-polarized array with six ports. The measurements were taken with the RUSK HyEff channel sounder [6], [7] at 2.53 GHz using a multi-tone test signal with 21.25 MHz bandwidth. The channel excitation duration was set to 12.8 µs. At the receiver, a polarized uniform circular array (PUCA) with 8 patch elements [7] has been used 2. Snapshot rates and recording times have been chosen to fulfill the channel sampling theorem. Measurements with the same equipment but at other frequencies and with other antennas have been reported in [6], [7], [8], [9], [10]. A carrier frequency of
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Figure 1. Map of the measurement area in downtown Dresden. The blue line shows the measurement route. Black triangles are the start and stop points of each measurement track. Base Stations with sector orientations are given as red ellipses.
Table I M EASUREMENT PARAMETERS FOR M EASUREMENT C AMPAIGN Parameter Center Frequency Bandwidth (B) Transmit Power Time Windows Carrier (N) BS / Sectors Antennas (Tx) Antennas (Rx) Vertical beam pattern Inter Site Distance Measurement Route Average Rx Velocity Snapshots per Route
Setting 2.53 GHz 21.25 MHz 44 dBm 12.8 µs 273 3/3 X-POL PUCA 8 yes 750 m 8800 m 4.2 m/s ≈ 450.000
2.53 GHz and a bandwidth of 20 MHz are typical values s for the deployment of the 3G Long Term Evolution (3G-LTE) in Europe. For other measurement and simulation parameters refer to Table I. V. A NALYSIS FOR S ELECTED P OINTS One target of our research is the verification of the used ray launching model with the collected drive test data. Therefore we compared the channel impulse response on selected of measurement points with the corresponding simulation results. The measurement points were processed by the RIMAX [11] estimation framework to resolve the channel parameter. Due to the high computational effort a couple of points ar choose for this comparison. About 500 snapshots per measurement point were evaluated to get an statistic on the propagation conditions. For one example we want to show the achieved results. Figure 3 shows the estimation result from the perspective of the receive (RX) antenna, which is located in the origin. The direct path, which is depict as the red cluster of
Figure 2.
Receive and Transmit antenna of measurement setup
points is situated on a circle of reflection. These reflections can be interpreted as scatterers situated nearby the RX-antenna. Furthermore we find stronger reflection of about 10 dB above the noise level on this circle and some fare away and back scatterers. Figure 4 shows the same geographical position from the ray launching perspective. With a geographic information system (GIS) tool we measured the following ray parameters. The direct ray with distance of 530 m and an angle of 14◦ , reflection 1 with 566 m at 21◦ , back reflection with 960 m at 190◦ and side reflections with 700 m at 220◦ . VI. C ONCLUSION : Within this work we compared ray tracing results CoMP channels, based on a ray launching approach. The results of these simulations were compared to channel sounding
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Figure 3. Scatterplot of estimated rays impinging the receiver in cartesian coordinates. The colorbar on the right side shows the raypower in dB normalized to the noise power.
Figure 4.
RPS ray analysis for the discussed measurement result
measurement done in the same area for a set of selected points. VII. ACKNOWLEDGEMENT: The authors wish to thank the German Ministry of Education and Research (BMBF) for financial support in the national collaborative project EASY-C. Furthermore we thank our partners Actix, Alcatel-Lucent, Deutsche Telekom, Ericsson, HHI, Kathrein, Qualcomm, TU Dresden and Vodafone for financial support of the campaign in Dresden. Many thanks to C. Schneider and G. Sommerkorn (all from TU Ilmenau) and S. Warzügel (MEDAV) for assistance during the measurements. R EFERENCES [1] 3GPP, 3GPP TR 25.814 v7.1.0: Technical Specification Group Radio Access Network (Release 7); Physical layer aspects for evolved Universal Terrestrial Radio Access (UTRA), 3rd Generation Partnership Project (3GPP), 9 2006. [2] The EASY-C Project. [Online]. Available: http://www.easy-c.com [3] V. Degli-Esposti, F. Fuschini, E. M. Vitucci, and G. Falciasecca, “Measurement and Modelling of Scattering From Buildings,” vol. 55, no. 1, pp. 143–153, Jan. 2007.
[4] J. Voigt, R. Fritzsche, and J. Schueler, “Optimal Antenna Type Selection in a Real SU-MIMO Network Planning scenario,” in Proc. IEEE 70th Vehicular Technology Conference Fall (VTC 2009-Fall), Sep. 20–23, 2009, pp. 1–5. [5] S. Jaeckel, L. Thiele, A. Brylka, L. Jiang, V. Jungnickel, C. Jandura, and J. Heft, “Intercell Interference Measured in Urban Areas,” in Communications, 2009. ICC ’09. IEEE International Conference on, June 2009, pp. 1–6. [6] R. Thomä, D. Hampicke, A. Richter, A. Schneider, G. Sommerkorn, U. Trautwein, and W. Wirnitzer, “Identification of time-variant directional mobile radio channels,” IEEE Trans. on IM, vol. 49, no. 2, pp. 357–364, 2000. [7] R. Thomä, D. Hampicke, A. Richter, G. Sommerkorn, and U. Trautwein, “MIMO Vector Channel Sounder Measurement for Smart Antenna System Evaluation,” Europ. Trans. Telecommun., vol. 12, no. 5, pp. 427– 438, 2001. [8] V. Jungnickel, V. Pohl, and H. Nguyen, “High capacity antennas for MIMO radio systems,” Proc. WPMC ’02, vol. 2, pp. 407–411, 2002. [9] M. Landmann, K. Sivasondhivat, J. Takada, and R. Thomä, “Polarisation behaviour of discrete multipath and diffuse scattering in urban environments at 4.5 GHz,” EURASIP JWCN, vol. 2007, no. 1, pp. 60–71, 2007. [10] V. Jungnickel, S. J. amd L. Thiele, U. Krueger, A. Brylka, and C. Helmolt, “Capacity measurements in a multicell mimo system,” Proc. IEEE Globecom ’06, 2006. [11] A. Richter, “On the estimation of radio channel parameters: Models and algorithms (RIMAX),” Ph.D. dissertation, Teschniche Universität Ilmenau, 2005.
