1. doc.: IEEE 802.11-09/0336r0 Submission March 2009 Alexander Maltsev, Intel CorporationSlide 1 Conference Room Channel Model for 60 GHz WLAN Systems - Summary Date: 2009-03-09 Authors:

2. doc.: IEEE 802.11-09/0336r0 Submission March 2009 Alexander Maltsev, Intel CorporationSlide 2 Abstract This contribution describes the channel model for conference room environment proposed to TGad.

3. doc.: IEEE 802.11-09/0336r0 Submission March 2009 Alexander Maltsev, Intel CorporationSlide 3 Introduction This contribution presents a channel model for 60 GHz WLAN systems in a conference room environment. The word document with detailed description of the conference room channel model is uploaded to the server [1]. The channel model is based on experimental measurements partially presented in [2].

4. doc.: IEEE 802.11-09/0336r0 Submission March 2009 Alexander Maltsev, Intel CorporationSlide 4 General Structure of Channel Model where: h(t,  tx,  tx,  rx,  rx ) is a generated channel impulse response function. t,  tx,  tx,  rx,  rx are time, azimuth and elevation angles at the transmitter (AoD) and receiver (AoA), respectively. A (i) and C (i) are the gain and the channel impulse response for i-th cluster respectively.  ( )- is the Dirac delta function. T (i),  tx (i),  tx (i),  rx (i),  rx (i) are time-angular coordinates of i-th cluster.  (i,k) is the amplitude of the k-th ray of i-th cluster  (i,k),  tx (i,k),  tx (i,k),  rx (i,k),  rx (i,k) are relative time-angular coordinates of k-th ray of i-th cluster The channel impulse response function for the channel model may be written using a general structure as

5. doc.: IEEE 802.11-09/0336r0 Submission March 2009 Alexander Maltsev, Intel CorporationSlide 5 General Structure of Channel Model (Cont’d) The proposed model structure assumes generally accepted clustering approach, which was used in TGn [4] and TG3c [5]. The clustering is done in both time and angular domains. Both AoAs and AoDs are represented in the model (as in TGn model [4]) with each ray having both azimuth and elevation AoA and AoD angles. Different types of antennas with different antenna patterns can be supported in the model. The model allows for antennas beamforming to be applied at both transmitter and receiver sides.

6. doc.: IEEE 802.11-09/0336r0 Submission March 2009 Alexander Maltsev, Intel CorporationSlide 6 General Structure of Channel Model (Cont’d) The same general structure of the channel model may be used for other channel modeling scenarios (cubicle and living room, for example) Statistical characteristics of different time and angular parameters of the channel model are specific for each scenario. To improve the accuracy of the propagation channel modeling: –the clusters within each environment are classified into different types (e.g. first and second order reflections from walls are different types of clusters) with specific statistical characteristics. –the parameters of individual clusters within the same cluster type are described by taking into account their statistical dependence. These approaches improve the accuracy of the propagation channel modeling that was verified by directly comparing the channel model with experimental data and ray-tracing simulations.

7. doc.: IEEE 802.11-09/0336r0 Submission March 2009 Alexander Maltsev, Intel CorporationSlide 7 Measurements and Modeling Environments Several sets of measurements have been carried out in three similar office conference rooms with dimensions equal approximately to 3 m x 4.5 m x 3 m (W x L x H). All the conference rooms have a big table in the middle and chairs around the table. The capacity of the rooms is about 8 to 10 people. The measurement environment corresponds to the channel model environment where several devices placed on the table in a conference room communicate with each other using LOS path and NLOS first and second order reflected rays from walls and ceiling.

8. doc.: IEEE 802.11-09/0336r0 Submission March 2009 Alexander Maltsev, Intel CorporationSlide 8 Experimental Setup Used to Perform Measurements Transmitter Receiver Baseband Main characteristics of the setup: –60 GHz RF frequency –2 dBm TX power –Horn antennas with 18 dB gain and 17 deg. 3 dB beamwidth –Mechanical steering of antennas using servo motors –800 MHz baseband channel bandwidth

9. doc.: IEEE 802.11-09/0336r0 Submission March 2009 Alexander Maltsev, Intel CorporationSlide 9 Model Development Methodology The experimental results demonstrated that the propagation channel has clustering nature and that time and angular positions of the clusters correspond (with low deviations) to the first and second order reflections predicted by the geometrical optics (ray tracing). Since the experimental set of parameters values was limited, time and angular inter cluster parameters were obtained from ray tracing simulations. A ray tracing model of the conference room with dimensions 4.5 x 3 x 3 m has been used to generate multiple realizations of 1st and 2nd order reflected clusters. Communicating devices were assumed to be located at the table in a center of the room. TX and RX pairs were randomly placed in a flat layer with the height equal to 1m and the horizontal dimensions equal to 2.5 x 1 m. The TX and RX positions were distributed uniformly within this layer.

10. doc.: IEEE 802.11-09/0336r0 Submission March 2009 Alexander Maltsev, Intel CorporationSlide 10 3D Model of Conference Room Used for Ray Tracing

11. doc.: IEEE 802.11-09/0336r0 Submission March 2009 Alexander Maltsev, Intel CorporationSlide 11 Groups of Clusters All clusters were divided into five groups: –LOS path –Four first order (reflected) clusters from four walls –One first order cluster from the ceiling –Four second order clusters from the walls and ceiling –Eight second order clusters corresponding to reflections from two walls In a real environment clusters from different groups have different characteristics (e.g. rays reflected from walls have approximately zero elevation angles) and this is taken into account in the channel model. The statistical distributions of parameters for these groups of clusters were obtained from experiments and ray tracing simulations. The corresponding approximations were used for the channel model development.

12. doc.: IEEE 802.11-09/0336r0 Submission March 2009 Alexander Maltsev, Intel CorporationSlide 12 LOS Path The LOS path is modeled as a single ray with the gain equal to: A 0 = λ/(4  d) –where λ is a wavelength, and d is a distance between TX and RX. The LOS component has zero TX and RX azimuth and elevation angles and also zero time of arrival (TOA). The TX and RX elevation and azimuth angles, as well as arrival times of other clusters are defined relative to the LOS path.

13. doc.: IEEE 802.11-09/0336r0 Submission March 2009 Alexander Maltsev, Intel CorporationSlide 13 1 st Order Reflections from Walls The second group of clusters correspond to the 1 st order reflections from walls. This group includes four clusters corresponding to four walls.

14. doc.: IEEE 802.11-09/0336r0 Submission March 2009 Alexander Maltsev, Intel CorporationSlide 14 1 st Order Reflections from Walls The model for generating the clusters corresponding to the first order wall reflections take into account the following properties: –Elevation angle is equal to zero for all clusters at both TX and RX. –There are always two positive and two negative angles when considering TX azimuth angles of all four clusters. At the RX side there are also two positive and two negative azimuth angles. –Every cluster has either positive TX and negative RX azimuth angles, or, vise versa, negative TX and positive RX azimuth angles. –Considering a pair of clusters with positive TX and negative RX azimuth angles, a cluster with the larger absolute value of TX azimuth angle will have a smaller (than other cluster) absolute value of the RX azimuth angle. Correspondingly the cluster with smaller absolute TX azimuth angle will have a larger absolute RX azimuth angle. The same is true for the other pair of clusters with negative TX and positive RX azimuth angles.

15. doc.: IEEE 802.11-09/0336r0 Submission March 2009 Alexander Maltsev, Intel CorporationSlide 15 1 st Order Reflections from Walls The azimuth angles are generated simultaneously for pairs of clusters having the same signs of azimuth angles. The joint distribution for such pairs is shown in the figure (for positive and negative angles). The joint distribution is used to maintain necessary relationships between angular characteristics of different clusters. It can be seen that there are no 1 st order clusters which are closely spaced in the angular domain. Joint distribution of azimuth angles with the same sign for two clusters corresponding to first order reflections

16. doc.: IEEE 802.11-09/0336r0 Submission March 2009 Alexander Maltsev, Intel CorporationSlide 16 Approximation for Azimuth Angles for 1 st Order Wall Clusters The following distribution (uniform in the given areas) has been used in the conference room channel model for the joint PDF approximation.

17. doc.: IEEE 802.11-09/0336r0 Submission March 2009 Alexander Maltsev, Intel CorporationSlide 17 1 st Order Reflection from Ceiling The cluster corresponding to the 1 st order reflection from ceiling has the following properties taken into account during the model development: –All azimuth angles equal to zero. –Elevation angles of TX and RX are equal and are generated in accordance with the distribution shown below.

18. doc.: IEEE 802.11-09/0336r0 Submission March 2009 Alexander Maltsev, Intel CorporationSlide 18 2 nd Order Reflections from Walls and Ceiling There are in total four 2 nd order clusters corresponding to reflection from wall and then ceiling or from ceiling and then wall for the chosen distributions of TX and RX positions. There is one reflection for each wall (either wall and then ceiling or ceiling and then wall). Azimuth angles for these clusters are equal to the azimuth angles of the wall reflected 1 st order clusters. Elevation angles of the same cluster are equal for TX and RX and are generated in accordance with the distribution shown in the next slide.

19. doc.: IEEE 802.11-09/0336r0 Submission March 2009 Alexander Maltsev, Intel CorporationSlide 19 Distribution of Elevation Angles for 1 st Order Ceiling and 2 nd order Wall and Ceiling Clusters

20. doc.: IEEE 802.11-09/0336r0 Submission March 2009 Alexander Maltsev, Intel CorporationSlide 20 2 nd Order Reflection from Walls There are totally eight clusters corresponding to the 2 nd order reflections from walls. The TX azimuth angle is equal to either RX azimuth angle or RX azimuth angle +/– 180 deg. There are four regions in the joint distribution of TX and RX azimuth angles and two clusters are generated for each region. Angle distribution within each zone is approximated by uniform PDF

21. doc.: IEEE 802.11-09/0336r0 Submission March 2009 Alexander Maltsev, Intel CorporationSlide 21 Cluster Time of Arrival (TOA) Distributions TOA is calculated relative to the LOS Measured (using ray tracing) distributions are shown as solid lines Approximations are shown as dashed lines TOAs for all clusters within different cluster groups are generated independently

22. doc.: IEEE 802.11-09/0336r0 Submission March 2009 Alexander Maltsev, Intel CorporationSlide 22 Amplitude of Clusters The gain of each cluster is calculated as: A i = g i λ / (4  (d + R)); R = c  t –where g i is reflection loss, λ is a wavelength (5 mm); –d is a distance between TX and RX (along LOS path); –(d + R) is a total distance along the cluster path (R is calculated as a product of TOA relatively LOS and the speed of light). The model for g i obtained from experimental histograms of the first and second order reflections is approximated by a log-normal (normal in dB scale) distribution (see next slide).

23. doc.: IEEE 802.11-09/0336r0 Submission March 2009 Alexander Maltsev, Intel CorporationSlide 23 Experimental and Approximated Distributions of Cluster Reflection Loss Reflection Loss for 1 st Order Reflection Mean value = -10 dB RMS = 4 dB Reflection Loss for 2 nd Order Reflection (total loss for two reflections) Mean value = -16 dB RMS = 5 dB

24. doc.: IEEE 802.11-09/0336r0 Submission March 2009 Alexander Maltsev, Intel CorporationSlide 24 Blockage of Clusters In a real environment not all clusters that occur in an empty conference room may be used for communication. Part of the clusters may be blocked by people sitting or moving in the conference room and also by other objects. This effect is taken into account in the channel model by the introduction of the cluster blockage probability associated with each type of cluster. Cluster type Probability of cluster blockage LOS 0 or 1 (set as a model parameter) 1 st order reflections from walls0.4 1 st order reflections from ceiling0.1 2 nd order reflections from ceiling and wall0.3 2 nd order reflections from walls0.8

25. doc.: IEEE 802.11-09/0336r0 Submission March 2009 Alexander Maltsev, Intel CorporationSlide 25 Intra Cluster Parameters for Conference Room (CR) Channel Model Intra cluster parameters for CR channel model include the time, amplitude and angular characteristics of the rays comprising the cluster. The intra cluster parameters of the channel model were estimated from the measurement data. The individual rays were identified in the time domain, and statistical characteristics including average number of rays, ray arrival rate, and ray power decay rates were obtained experimentally. Based on the obtained results, the statistical model for the cluster time domain parameters was developed.

26. doc.: IEEE 802.11-09/0336r0 Submission March 2009 Alexander Maltsev, Intel CorporationSlide 26 Proposed Time Domain Cluster Model Cluster model was proposed to consist of: –A central ray with fixed amplitude. –Pre-cursor rays modeled by Poisson process with exponentially decaying Rayleigh distributed ray amplitudes. The average ray power is decaying in negative time direction. –Post-cursor rays also modeled by Poisson process with exponentially decaying Rayleigh distributed ray amplitudes. The average ray power is decaying in positive time direction. –The number of pre-cursor rays and post-cursor rays was obtained from measurements and is fixed in the model.

27. doc.: IEEE 802.11-09/0336r0 Submission March 2009 Alexander Maltsev, Intel CorporationSlide 27 Proposed Time Domain Cluster Model ParameterKfKf ff f NfNf KbKb bb b NbNb Value5 dB1.3 ns0.2 ns -1 210 dB2.8 ns0.12 ns -1 4

28. doc.: IEEE 802.11-09/0336r0 Submission March 2009 Alexander Maltsev, Intel CorporationSlide 28 Measured and Simulated Cluster Power Delay Profiles (PDPs) Good match between the simulated and measured PDPs is achieved.

29. doc.: IEEE 802.11-09/0336r0 Submission March 2009 Alexander Maltsev, Intel CorporationSlide 29 Intra Cluster Angular Parameters The resolution of the rays of the same cluster in the angular domain requires using antenna with very narrow beam or employing the “virtual antenna array” approach [6] (when low directional antenna element is used to perform measurements in multiple positions along the virtual antenna array to form an effective antenna aperture). In the measurements the majority of the cluster rays were received within the angle dimension of the measurement antenna pattern (about 17 deg. at 3 dB level). Therefore, a simple model may be used to describe the intra cluster angular parameters. Intra cluster azimuth and elevation angles for both transmitter and receiver are modelled as independent normally distributed random variables with zero mean and RMS equal to 5 0.

30. doc.: IEEE 802.11-09/0336r0 Submission March 2009 Alexander Maltsev, Intel CorporationSlide 30 MIMO Channel and Antenna Modeling The MIMO channel model for the systems with small separation between antenna elements (e.g. half wavelength for antenna arrays) is obtained by assuming the same angles of departure and arrival for different antenna elements and negligible difference in time of arrival between different elements is taken into account only by the appropriate signal phase shifts between different antenna elements. Three antenna models were developed together with the proposed channel model: –Isotropic radiator –Basic steerable directional antenna –Phased antenna array

31. doc.: IEEE 802.11-09/0336r0 Submission March 2009 Alexander Maltsev, Intel CorporationSlide 31 Isotropic Antenna The simplest type of the antenna model is an isotropic radiator‎. This model has a spherical antenna pattern that equally illuminates all signal rays at the transmitter and equally combines all rays coming from different directions at the receiver. The isotopic antenna can not be implemented in practice but is a convenient theoretical model which is used in the channel model for analytical purposes. This antenna model does not have any spatial selectivity and does not need any beamforming procedure for optimal steering in space.

32. doc.: IEEE 802.11-09/0336r0 Submission March 2009 Alexander Maltsev, Intel CorporationSlide 32 Basic Steerable Directional Antenna Many known wireless propagation channel models (e.g. ‎TG3c [5], SCM ‎[7]) include a basic directional antenna model that captures only essential characteristics of real world antennas but is significantly simplified to avoid unnecessary complexity. The most widely used is a directional antenna model with a main lobe of Gaussian form in linear scale (parabolic form in dB scale) and constant level of side lobes ‎[7], ‎[8]. The basic directional antenna model was extended to include both azimuth and elevation angles and support 3D beam steering. The detailed description of the basic steerable antenna model is provided in the accompanying word document [1].

33. doc.: IEEE 802.11-09/0336r0 Submission March 2009 Alexander Maltsev, Intel CorporationSlide 33 Phased Antenna Array Planar rectangular phased antenna array composed of variable number of identical elements is supported. Elements in the reference array are isotropic radiators (however, the array model is not limited to only this type of radiators, and can be simply modified for any other type). The detailed description of the phased antenna array model is provided in the accompanying word document [1].

34. doc.: IEEE 802.11-09/0336r0 Submission March 2009 Alexander Maltsev, Intel CorporationSlide 34 Conclusion The conference room channel model for 60 GHz WLAN systems is proposed. The model supports beamforming with steerable directional antennas on both TX and RX sides. The further work on the model should include development of support for polarization and non-stationary characteristics. The structure of the model may be reused for other channel modelling scenarios (cubicle, living room, etc.) by modifying parameters of the model.

35. doc.: IEEE 802.11-09/0336r0 Submission March 2009 Alexander Maltsev, Intel CorporationSlide 35 References 1.A. Maltsev et al, “Channel Models for 60 GHz WLAN Systems,” IEEE doc. 11-09/0334r0. 2.A. Maltsev et al “60 GHz WLAN Experimental Investigations,” IEEE doc. 11-08-1044r0. 3.A. Maltsev et al “Channel Modeling for 60 GHz WLAN Systems,” IEEE doc. 11-08-811r1. 4.V. Erceg et al, “TGn channel models,” IEEE doc. 802.11-03/940r4, May. 5, 2004. 5.Su-Khiong Yong et al, “TG3c channel modeling sub-committee final report,” IEEE doc. 15-07-0584-01-003c Mar. 13, 2007. 6.A. Davydov, A. Maltsev, A. Sadri “IMST Data Processing Methodology”, IEEE P802.15-06-0201-00-003c. 7.Spatial channel model text description, SCM text v.7.0, Spatial channel model AHG (combined ad-hoc from 3GPP&3GPPs), Aug. 19, 2003. 8.I. Toyoda et al., “Reference antenna model with side lobe for TG3c evaluation,” IEEE doc. 802.15-06/474r0.