Modeling of Cooperative MIMO Channels in UrbanAreas

Carsten Jandura1, Martin Kaeske2, Jens Voigt3 and Gerhard P. Fettweis4

1,4Vodafone Chair Mobile Communication Systems, Technical University of Dresden, Germany{carsten.jandura, fettweis}@ifn.et.tu-dresden.de,

2 Ilmenau University of Technology, Martin.Kaeske@tu-ilmenau.de3Actix GmbH, Dresden, Jens.Voigt@actix.com

Abstract—Multiple-Input Multiple-Output (MIMO) technol-ogy is ready for deployment in commercial cellular networks inthe very near future. Therefore, the need of incorporating thistechnology into radio network planning and optimization toolsrises dramatically for network operators. In this contribution weshow results of the validation of advanced ray tracing simulationswith channel sounding measurements in the 2.53 GHz frequencyband. These measurements were carried out inside the EASY-Cproject with the objective to learn more about coordinatedmultipoint (CoMP) transmission in a real world testbed. Wecompare the results of the ray tracing simulations with processedchannel sounding measurements at specific points in an urbanenvironment As result we can conclude that carefully performedGeometrical Optics based ray-tracing simulations are a suitableprediction model to reflect main characteristics of these scenarios.A further objective of these experiments is to get insight into thephysical structure of the radio channel.

I. INTRODUCTION

The increasing demand for data transmission in cellularnetworks leads to the specification of the 3GPP LTE standard.Within these mobile communication system a new physicallayer with the multiple access scheme orthogonal frequencydivision multiplexing (OFDM) in the downlink, single carrierfrequency division multiple access (SC-FDMA) in the uplinkand the capacity increasing MIMO technology was specified.The target data rates for this system are up to 300 MBit/s usingfour antennas at transmit and receive side [1]. The problem oflow signal to interference and noise ratio (SINR) at the celledges with a bad user experience in terms of data through-put still remains. One transmission strategy, called CoMP isdiscussed as the way to get rid of this phenomenon. Withinthe German research project EASY-C [2] these communicationstrategies are studied at link and system level. One part of theproject is the channel modeling and verification for cooperat-ing base stations and the comparison with measured channelimpulse responses inside a large scale testbed. These resultsare important for the radio and -fixed network planning of nextgeneration mobile communication networks. This paper showsthe influence of the network design of the possible cooperatingareas and compare simulation results with measurement datacollected in the EASY-C testbed in downtown Dresden.

II. MODELING APPROACH

We simulate the single-input single-output (SISO) channelimpulse response using a ray launching algorithm operatingin a 3D environment model as a deterministic channel model.A high resolution building model is placed on top of a digitalelevation model (DEM) and transmit (TX) antennas were setto the real world positions. The algorithm regards a bundleof rays, emanating from a transmitter source using a transmitangle interval of 1◦ that are all traced along until their fieldstrength falls below a defined threshold. For every launchedray the nearest obstacle in the current propagation directionis determined. Once a ray hits an obstacle the ray launchingalgorithm includes the radio wave propagation effects specularreflection and diffraction in its ongoing calculation based onthe algorithms of Geometrical Optics and the Uniform Theoryof Diffraction. Furthermore a diffuse scattering model [3]considers effects on rough surfaces. This algorithm calculatesthe properties of the electromagnetic field, the complex po-larimetric amplitudes, direction of departure (DOD), directionof arrival (DOA), and time delay of arrival (TDOA) for everytransmitter–receiver combination. Receivers are modeled byhorizontal square planes with a lateral size arx of severalmeters. The electrical beam pattern of the transmit and receiverantennas are included in the ray tracing algorithm. The directresult of the ray launching algorithm is the time–invariant(one sample point) complex polarimetric impulse response ofa SISO radio channel. It can be described as:

hSISO(τ) =∑

k

akq,p exp

(−j2πcτk

λ

)δ (τ − τk) ·

δ(θTx − θTx

k

)· δ(φTx − φTx

k

)·

δ(θRx − θRx

k

)· δ(φRx − φRx

k

)(1)

with k as path index between transmitter and the receiver,τk as propagation delay and ak

q,p as complex–polarimetricattenuation coefficient on path k, the indices q, p are denotingthe polarization, co- or cross polarized. λ as the carrier wavelength and c as the velocity of light. In order to extend theray tracing result towards a MIMO channel impulse responsematrix, the antenna type has to be taken into account [4].

III. SIMULATION RESULTS

IV. MEASUREMENTS

The verification of the ray launching simulation results isbased on a channel sounding measurement campaign carriedout in August 2008 in Dresden [5] as part of the EASY–Cproject. Three commercially used base station sites whereequipped with commercial +18 dBi base station (BS) antennas(Kathrein 80010541) with two cross-polarized ports ±45◦ in astandard tree-fold sectorization. The map in Figure 1 shows thedeployment and measurement scenario around Dresden mainstation. The antenna heights or BS1, BS2 and BS3 where54m, 34m and 51m respectively. The area is typical urbancharacterized by streets surrounded by buildings of 30 m to50 m height. All sector antennas at one site have been fed like asingle cross-polarized array with six ports. The measurementswere taken with the RUSK HyEff channel sounder [6], [7]at 2.53 GHz using a multi-tone test signal with 21.25 MHzbandwidth. 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 ratesand recording times have been chosen to fulfill the channelsampling theorem. Measurements with the same equipmentbut at other frequencies and with other antennas have beenreported in [6], [7], [8], [9], [10]. A carrier frequency of

Table IMEASUREMENT PARAMETERS FOR MEASUREMENT CAMPAIGN

Parameter SettingCenter Frequency 2.53 GHzBandwidth (B) 21.25 MHzTransmit Power 44 dBmTime Windows 12.8 µsCarrier (N) 273BS / Sectors 3 / 3Antennas (Tx) X-POLAntennas (Rx) PUCA 8Vertical beam pattern yesInter Site Distance 750 mMeasurement Route 8800 mAverage Rx Velocity 4.2 m/sSnapshots per Route ≈ 450.000

2.53 GHz and a bandwidth of 20 MHz are typical values sfor the deployment of the 3G Long Term Evolution (3G-LTE)in Europe. For other measurement and simulation parametersrefer to Table I.

V. ANALYSIS FOR SELECTED POINTS

One target of our research is the verification of theused ray launching model with the collected drive test data.Therefore we compared the channel impulse response onselected of measurement points with the corresponding sim-ulation results. The measurement points were processed bythe RIMAX [11] estimation framework to resolve the channelparameter. Due to the high computational effort a couple ofpoints ar choose for this comparison. About 500 snapshots permeasurement point were evaluated to get an statistic on thepropagation conditions. For one example we want to show theachieved results. Figure 3 shows the estimation result from theperspective of the receive (RX) antenna, which is located inthe origin. The direct path, which is depict as the red cluster of

Start/Stop Measurement

Measurement Track

Testbed Siteswith Antenna Azimut{60°,180°,300°}

9

8

7

6

9

3

2

1

9

39

29

28

27

2629

24

22

21

19

18

17

16

19

14

1312

11

19

29

13a

BS3

BS1

BS2

Figure 1. Map of the measurement area in downtown Dresden. The blue lineshows the measurement route. Black triangles are the start and stop points ofeach measurement track. Base Stations with sector orientations are given asred ellipses.

Figure 2. Receive and Transmit antenna of measurement setup

points is situated on a circle of reflection. These reflections canbe interpreted as scatterers situated nearby the RX-antenna.Furthermore we find stronger reflection of about 10 dB abovethe noise level on this circle and some fare away and backscatterers.

Figure 4 shows the same geographical position from theray launching perspective. With a geographic informationsystem (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 at190◦ and side reflections with 700 m at 220◦.

VI. CONCLUSION:

Within this work we compared ray tracing results CoMPchannels, based on a ray launching approach. The resultsof these simulations were compared to channel sounding

−3000 −2000 −1000 0 1000 2000 3000−3000

−2000

−1000

0

1000

2000

3000

distance [m]

dist

ance

[m]

5

10

15

20

25

30

position of Rxantenna

far scatterers

direct path

ring of scatterers around Rx antenna

Figure 3. Scatterplot of estimated rays impinging the receiver in cartesiancoordinates. The colorbar on the right side shows the raypower in dBnormalized to the noise power.

Figure 4. RPS ray analysis for the discussed measurement result

measurement done in the same area for a set of selectedpoints.

VII. ACKNOWLEDGEMENT:

The authors wish to thank the German Ministry ofEducation and Research (BMBF) for financial support inthe national collaborative project EASY-C. Furthermore wethank our partners Actix, Alcatel-Lucent, Deutsche Telekom,Ericsson, HHI, Kathrein, Qualcomm, TU Dresden andVodafone for financial support of the campaign in Dresden.Many thanks to C. Schneider and G. Sommerkorn (all fromTU Ilmenau) and S. Warzügel (MEDAV) for assistance duringthe measurements.

REFERENCES

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