IEEE ANTENNAS AND WIRELESS PROPAGATION LETTERS, VOL. 13, 2014 1047

Deterministic and Experimental Indoor mmWChannel Modeling

Maria-Teresa Martinez-Ingles, Davy P. Gaillot, Juan Pascual-Garcia, Jose-Maria Molina-Garcia-Pardo,Martine Lienard, and José-Víctor Rodríguez

Abstract—This letter presents an extensive multidimensionalanalysis of line-of-sight (LOS) experimental data and simula-tions at 60 GHz over a 9-GHz bandwidth. Numerical versions ofthe measured multiple-input–multiple-output (MIMO) channeltransfer functions were obtained with a ray-tracing engine thatincludes single-order diffuse scattering. The received power, RMSdelay spread (DS), and maximum excess delay (MED) computedfrom both measured and simulated data indicate that diffusescattering improves ray-tracing-based modeling. Moreover, themultipath components (MPCs) extracted from both sets of datausing the high-resolution estimator RiMAX were statistically com-pared. The analysis of the results shows that even a raw descriptionof the environment can be used to predict millimeter-wave (mmW)propagation with ray tracing.

Index Terms—Channel modeling, millimeter-wave (mmW), raytracing, RiMAX.

I. INTRODUCTION

F UTURE wireless communications systems have envi-sioned the millimeter-wave (mmW) frequency band as a

promising response to overcome the Gbps barrier [1]. To thisend, two wireless medium access controls and physical layershave been proposed by IEEE, one for personal area networks(802.15.3c [2]) and another for wireless LAN (802.11ad [3]).In [2], it is mentioned that significant efforts were carried out todevelop models as realistic as possible. However, the numberof available measurements and related data in the 57–64-GHzrange, from which the model was based, was insufficient tofully characterize the underlying environments. Some recentpapers, such as [4], present clustering results for a double-di-rectional 60-GHz multiple-input–multiple-output (MIMO)channel model. The authors of [5] provide a deep review offrequency-domain measurement results selected from majorresearch teams.

Manuscript received March 07, 2014; revised April 24, 2014 and April24, 2014; accepted May 24, 2014. Date of publication May 29, 2014; dateof current version June 11, 2014. This work was supported by MINECO,Spain, under Grant TEC2010-20841-C04-03, the European FEDER funds,and STSM under Grant COST IC-1004. (Corresponding author: Jose-MariaMolina-Garcia-Pardo.)M.-T. Martinez-Inglés, J. Pascual-Garcia, J.-M. Molina-Garcia-Pardo,

and J.-V. Rodríguez are with the Departamento Tecnologías de la Informa-ción y las Comunicaciones, Universidad Politécnica de Cartagena, Murcia30202, Spain (e-mail: mteresa.martinez@upct.es; juan.pascual@upct.es;josemaria.molina@upct.es; jvictor.rodriguez@upct.es).D. P. Gaillot and M. Lienard are with the IEMN/TELICE, Electronics De-

partment, University of Lille 1, 59655 Villeneuve d’Ascq, France (e-mail: davy.gaillot@univ-lille1.fr; martine.lienard@univ-lille1.fr).Color versions of one or more of the figures in this letter are available online

at http://ieeexplore.ieee.org.Digital Object Identifier 10.1109/LAWP.2014.2327054

On the other hand, deterministic field prediction methods arewidely used for estimating essential radio channel characteris-tics [6], [7]. Nonetheless, as far as the authors are concerned, acomprehensive comparison of ray tracing simulations includingdiffuse scattering with measurements in the mmW frequencyband is clearly missing. Only in [8] can such an approach befound, where the authors developed a point cloud-based full dif-fuse propagation prediction method. However, the overall fieldis only described as fully diffuse backscattered from the pointcloud measured by a laser device.In this letter, an extensive measurement campaign has been

carried out to measure the MIMO channel transfer functionsat 60 GHz in an office. The transmitting array was movedover 20 line-of-sight (LOS) positions, whereas the receivingarray stayed at the same position. Additionally, all MIMOchannels were simulated by using a ray-tracing engine thatimplements single-order diffuse scattering [9] from which thereceived power, RMS delay spread (DS), and excess delay werecompared to the measured channels. Also, and for the sake ofcomparison, the high-resolution algorithm RiMAX [10] wasapplied to both data (experiment and simulation) to extract thegeometrical parameters of the multipath components (MPCs).Finally, the arrival and departure angular spreads were com-puted to compare the measured and simulated MPCs.

II. SCENARIO AND MEASUREMENTS/SIMULATIONS

A. Scenario

The measurement scenario is a laboratory located on thefirst floor of the Universidad Politécnica de Cartagena researchbuilding (Spain). The 4.5 7 2.5-m laboratory is furnishedwith several closets, shelves, desktops, and chairs. In addition,the laboratory is equipped with several computers and elec-tronic devices. The walls are typical plasterboard walls, andthe floor and ceiling are made of concrete. In Fig. 1, a top viewof the measured scenario is depicted, as well as the measuredpositions. Twenty separate transmitter (Tx) locations and onereceiver position (Rx) were considered for this study.For all positions, a 0.5-m and 1-m distance was selected be-

tween each Tx row and column, respectively. All distances weremeasured with a laser to obtain the most accurate precision pos-sible. It is noteworthy that an LOS existed for all positions.

B. Measurements

The measurements were conducted using a Rohde &Schwartz ZVA67 vector network analyzer (VNA). The mea-sured frequency range was 57–66 GHz using 4096 frequencypoints. A 10-Hz intermediate frequency was selected, and a dy-namic range of more than 100 dB was obtained. Two amplifiers

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1048 IEEE ANTENNAS AND WIRELESS PROPAGATION LETTERS, VOL. 13, 2014

Fig. 1. Indoor scenario.

were used in the transmission to compensate for the attenuationof the cables. The system is THROUGH calibrated to eliminatethe effect of cables and amplifiers. Both Tx and Rx antennasare vertically polarized antennas (Q-par QOM55–65 VRA)with 4.5 dBi gain. The antennas have omnidirectional patternsin the H-plane and 40 , 28 , and 21 beamwidth at half-powercentered in the E-plane at 55, 60, and 65 GHz, respectively.The height of the transmitting antenna was 1.44 and 1.54 m forthe receiving antenna. A virtual uniform linear array (ULA)with five positions is used for Rx ( -axis orientation), whereasa 6 6 virtual uniform rectangular array (URA) parallel toRx was used for Tx, resulting in 180 possible channels. Theinterelement distance was set to 2 mm for both arrays.

C. Simulations

A simplified, yet faithful, numerical model of the scenariohas been developed with the main furniture. Suitable permit-tivity and conductivity values, constant through the whole band-width, were assigned to the scenario elements [11]. The 3-D raytracing (3D RT) technique employed in this work is fully writteninMATLAB and provides the computation of the usual reflectedand diffracted components. Furthermore, single-order diffusecomponents have been simulated with the directive model inorder to increase the accuracy of the model [9]. Following theapproach of [8], the best parameters for the directive model( and ) were found by comparing the mea-sured power delay profile (PDP) to the simulated PDP obtainedwith different combinations of the model parameters. The max-imum number of reflections was set to two. These values pro-vide a natural convergence of the algorithm for all simulations.Finally, we note that the radiating pattern of the antennas wasincluded to adjust the complex gain of each path. However, theprecision stage guide and mounting bracket were not includedin the model.For each Tx–Rx pair, 3D RT simulations were performed

over the same frequency points as the VNA to obtain numericalversions of the measured MIMO channels. This is simply doneby summing the contribution of all waves for each frequencyvalue to reconstruct the transfer functions in the frequencydomain. This simplifies the comparison between measurementsand simulations. The classical MPC data model used in the lit-erature and this work is frequency-dependent in the time-delaydomain. However, it is narrowband for the spatial domain (i.e.,single frequency). Indeed, a wideband description of the spatialdomain would imply measuring the radiating pattern for each

frequency point, which is simply not feasible. Hence, a sub-bandcould be selected from both measured and simulated channelsto perform a parametric estimation of the MPCs.

III. MPC EXTRACTION THROUGH RIMAX

Both measured and simulated MIMO radio channels wereprocessed with the RiMAX maximum-likelihood algorithm.This estimator was developed to extract the propagation pathsparameters (time delays, azimuth/elevation angles, and com-plex gains) and dense multipath components (DMC) [10].The DMC is stochastic by nature and includes both diffusescattering and paths that cannot be resolved. The incorporationof the DMCs into the data model was shown to improve theaccuracy and validity of the estimated propagation paths [10].Estimated parameters are typically subject to data model andcalibration errors. Hence, the purpose of estimating the pa-rameters from the simulated channels instead of actually usingthose predicted by the 3D RT is to compare fairly the measuredand simulated data. The variance of the measured noise wascomputed from the measured channels for each position andadded to the simulated channels since it is used in the estimatordata model.The following set of parameters is obtained for each multi-

path component :

(1)

where are the complex amplitude, el-evation angle of departure, azimuth angle of arrival and depar-ture, and time delay, respectively.To comply with the narrowband spatial model hypothesis

discussed earlier, a 1.12-GHz bandwidth around 57.56 GHz(512 frequency points) was selected out of the 9 GHz availablebandwidth. In addition, the whole MIMO array was selectedto perform the estimation (6 6 URA for Tx and five-elementULA for Rx). The five-element ULA restricts the angularestimation between 90 and 90 , but is here sufficient tograsp the physics of the propagation mechanisms. Also, notethat elevation estimation is limited to the Tx array in this work.Finally, we note that the radiation pattern of the antennas wasnot included into the estimator data model. Preliminary estima-tions from 3D RT simulated transfer functions have shown thatthe azimuth and elevation angles are correctly grasped with anomnidirectional approach. Also, the error between the RT andestimated transfer functions was in the order of 0.05 dB. Due tothe configuration of the room, the most energetic paths arrivewith low elevation angles where the antenna gain is almostmaximal.

IV. RESULTS

A. 9-GHz Bandwidth

The PDP is computed as the inverse Fourier transform ofobtained from both measurements and simulations, and aver-aged over all 180 channel transfer functions. As an example,Fig. 2 presents the PDP for position 3 with 9-GHz bandwidth.For the sake of clarity, no measurement noise was added to thesimulations. It is visually shown that the shape of the simulatedPDP matches well that of the measured one between 10 and30 ns. However, the baseline of the simulated PDP diverges be-yond 30 ns.

MARTINEZ-INGLES et al.: DETERMINISTIC AND EXPERIMENTAL INDOOR mmW CHANNEL MODELING 1049

TABLE IRELATIVE RECEIVED POWER, DS, AND MED IN 9 GHZ FROM MEASURED AND SIMULATED (WITH AND WITHOUT DIFFUSE SCATTERING) CHANNELS

Fig. 2. Power delay profile for measurements and simulations.

This proves that second-order diffusion should be added tofit correctly the shape of the PDP. However, those componentswere not considered in this work to reduce the computationtime, but also because its contribution to the total energy of thechannel is very weak. For instance, a maximum difference of1–2 dB was obtained between the simulated (without second-order scattering) and measured transfer functions. Both resultsindicate the correctness of the 3D RT data model. The wide-band relative received power in decibels can be computed fromthe PDP as the sum of all PDP components

(2)

The RMS DS (second-order moment) that gives us a measureof the maximum data throughput without equalization can alsobe computed from the PDP by [12]

(3)

where are the components of the PDP within athreshold and their corresponding delay. Finally, the max-imum excess delay (MED) can be computed as the delayrelative to the first arriving path

(4)

Table I presents the wideband received power, DS, and MEDfor simulations (with and without diffuse scattering) and mea-surements with 9-GHz bandwidth for the first five positions.A 30-dB threshold was used to eliminate noise and low-powercontributions for the computation of the received power, DS,and MED. A mean RMS DS of 4.1 ns was computed from the

Fig. 3. Simulated and measured relative received power.

measured and simulated data using all positions. In comparisonto the literature, a 4.8-ns RMS DS was reported in [5] for a28.2-m room (3.7 ns for 32.9 m in this work). A maximumexcess delay of 29.8 and 27.2 ns was obtained using (4) fromthe measurements and simulations, respectively.Furthermore, the results show that including diffuse scat-

tering, which accounts for 10% of the total energy for allsimulated positions, improves the accuracy of the simulations.Evidently, this energetic contribution would strongly increasefor obstructed or non-line-of sight (OLOS or NLOS) scenariossince the LOS component is found to be 10–15 dB moreenergetic than secondary paths.The relative received power computed using (2) is displayed

in Fig. 3 for both measurements and simulations. From the av-eraged received power, a typical one-slope model was fitted tothe data

(5)

where is the received power for a 1-m reference distance,the decay factor, and the distance between Tx and Rx.The one-slope models obtained from the measured and simu-

lated data are in good agreement with a computed decay factorof 1.52 and 1.51, respectively. These values are in the rangeof 1.2 and 2.0 reported in [2] and [5] for mmW LOS measure-ments. Indeed, the authors in [2] explained that can be smallerthan 2 when wave-guiding and reverberation effects are present,resulting in power levels increase by multipath aggregation. Inaddition, a distribution of the measured and simulated resultsaround the average received power can be modeled by a zeromean Gaussian distribution . A 2.17- and 0.23-dB standarddeviation for was found for the measurements and simula-tions, respectively.

1050 IEEE ANTENNAS AND WIRELESS PROPAGATION LETTERS, VOL. 13, 2014

TABLE IIEXTRACTED PARAMETERS FOR SIMULATED AND MEASURED DATA

B. 1.12 GHz Bandwidth

The MPCs were extracted from both measured and simulatedchannel transfer functions over a 1.12-GHz bandwidth (relativebandwidth less than 2% and thus satisfying the narrowband as-sumption). Once all MPCs are estimated, the total number ofrays (TNR) is obtained after applying a 30-dB threshold to re-move the weaker paths. The angular spread (AS) in azimuth andelevation for direction of arrival and departure angles was alsocomputed as [13]

(6)

where for the three possible angularspreads. Note that angle ambiguities were removed to correctlycompute the azimuth AS for the direction of departure.Table II summarizes in details the parameters for the posi-

tions 1–5 extracted from both simulated and measured data, aswell as the averaged values and standard deviation for the 20 po-sitions. The average number of extracted MPCs (total numberof rays, TNR) using RiMAX is 15 for the simulations and 60for measurements. Here, the difference is attributed to the sim-plified modeling of the propagation scenario.Finally, an AS value of 41.5 (63.6 ) and 55.1 (65.5 ) was

computed for ( ) from the simulations and measure-ments, respectively. Similarly, an AS value of 18.4 and 16.6was computed for from the simulations and measurements,respectively. In general, a larger spread is obtained from themeasurements than the simulations due to the modeling of theroom, as discussed previously. Nevertheless, the results can beconsidered quite satisfactory.Authors from [4] measured , , ,

values of 40 , 17.2 , 11.4 , and 17.2 , while we havemeasured 55.1 , 65.6 , 24.3 and 16.6 . A large difference isobserved between both . This is attributed to the factthat the authors in [4] used a URA for Rx, whereas a ULAwas chosen in this work. Hence, all rays are folded back into

, which results into increasing its angular spread.

V. CONCLUSION

In this letter, we have presented an extensive multidimen-sional analysis of LOS experimental data and ray tracingsimulations including single-order diffuse scattering in themillimeter-wave frequency band for 20 transmitting positionsin an 80-m office. The results support the idea that diffusescattering, which accounts for 10% of the total energy, must

be taken into account in simulations to faithfully reconstructchannel transfer functions. However, second-order scatteringmight not be necessary to assess the propagation parametersof the mmW channels. The RiMAX algorithm was used toextract the MPC parameters from both measured and simulateddatasets. From this analysis, a good agreement is reachedbetween the time delays and power angular spreads computedfrom the RT and measured channels. Those values are alsofound to be similar to other results published in the scien-tific literature. In summary, the results show that even a rawdescription of the environment can be used to predict mmWpropagation with ray tracing.

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