Project: IEEE P802.15 Working Group for Wireless Personal Area Networks (WPANs)

1. Project: IEEE P802.15 Working Group for Wireless Personal Area Networks (WPANs) Submission Title: [NICT Indoor 60 GHz Channel Measurements and Analysis update] Date Submitted: [7 March 2006] Source: [Z. Krusevac, S. Krusevac, A. Gupta,T. Pollock, D. Miniutti,C. Liu,E. Skafidas] Company [National ICT Australia Limited] Address [Level 2, 216 Northbourne Ave, Canberra, ACT 2602, Australia] Voice:[+61 2 6125 3797], FAX: [+61 2 6230 6121], E-Mail:[tony.pollock@nicta.com.au] Source: [Hirokazu Sawada,Chang-Soon Choi,YozoShoji, Hiroyo Ogawa] Company [National Institute of Information and Communications Technology] Address [3-4, Hikarino-Oka, Yokosuka, Kanagawa, 239-0847, Japan] Voice:[+81.46.847.5096], FAX: [+81.46.847.5079], E-Mail:[sawahiro@nict.go.jp, shoji@nict.go.jp, hogawa@nict.go.jp] Re: [Response to the TG3c channel model subgroup call for channel models] Abstract: [Analysis of the NICT data for proposed 60 GHz Channel Model ref15-06-0103-00] Purpose: [Contribution to 802.15 TG3c at March 2006 meeting in Denver, USA] Notice: This document has been prepared to assist the IEEE P802.15. It is offered as a basis for discussion and is not binding on the contributing individual(s) or organization(s). The material in this document is subject to change in form and content after further study. The contributor(s) reserve(s) the right to add, amend or withdraw material contained herein. Release: The contributor acknowledges and accepts that this contribution becomes the property of IEEE and may be made publicly available by P802.15. Tony Pollock, NICTA

2. Purpose • Channel model sub-committee requires a common channel model for evaluation of PHY layer proposals • Bulk of proposed applications require directional antennas • Committee needs a model with AoA Require a measurement campaign to: • Determine an appropriate channel model with AoA • Determine the set of parameters that accurately describes the 60 GHz channel for indoor situations Tony Pollock, NICTA

3. L = number of clusters; Kl = number of multipath components (number of rays) in the l-th cluster; = multipath gain coefficient of the k-th ray in the l-th cluster; Tl = arrival time of the first ray of the l-th cluster; k,l = delay of the k-th ray within the l-th cluster relative to the first path arrival time, Tl; = mean angle of arrival of l-thcluster; = angle of arrival of the k-th ray within the l-th cluster. Recall: Proposed Channel Modelref: 15-06-0103-00 S-V Model with AoA extension Tony Pollock, NICTA

4. Recall: Model Parameters Tony Pollock, NICTA

5. NICT AoA Channel Measurementsref: 15-06-0012-01 • LOS Residential and NLOS Office environments • Polarization: Vertical • Antenna height: 1.1m • Antenna separation: 3m(home), 10m(office) • Tx antenna: always fixed • Rx antenna: rotated from 0 to 360 degree in 5 degree steps Tony Pollock, NICTA

6. Using Vector Network Analyzer HP8510C Environment Residential Office Center frequency 62.5 GHz Bandwidth 3 GHz Time resolution 0.25 ns Distance resolution 19.1cm No. frequency points 401 801 Frequency step 7.5 MHz 3.75 MHz Max. excess delay 133.3 ns 266.7 ns Times of average 128 Equipment Tony Pollock, NICTA

7. Residential Environment (LOS) • Living room without fixtures (LOS) • Surface of a wall and ceiling are covered with wallpaper • Window is plane glass • Wooden door and floor Tony Pollock, NICTA

8. Office Environment (NLOS) • The office room is made of steel wall, steel ceiling and steel floor • The floor and the ceiling are covered with carpet and plaster board, respectively • Plate glass windows are attached on wall Tony Pollock, NICTA

9. Single Directional Channel Model • deconvolve Rx antenna pattern from measured data • Solution to a large set of linear simultaneous equations Tony Pollock, NICTA

10. Cluster Identification Summary • PDPs are converted to a grayscale image • Matlab tool imtool.m is used for the picture analysis • Individual pixel analysis - contrast adjustment • Blind deconvolution tool deconvblind.m forcleaning the picture • CLEAN algorithm to uncorrelate pixels • Observed clusters (PDPs) then obtained from original data for more precise details and parameter extraction Tony Pollock, NICTA

11. Cluster Identification Tony Pollock, NICTA

12. Cluster Identification • Identify cluster shape • Pixel level indicates strength of MPC • Used to determine rough cluster size/shape • Indicates where in data to extract more precise cluster MPCs Tony Pollock, NICTA

13. MPC Selection • Many possible methods: • Visual • CLEAN algorithm • Lucy algorithm • Maximum Entropy Methods • Maximum likelihood algorithms based on blind deconvolution techniques • Currently using CLEAN and visual ray extraction • Looking to improve using other algorithms Tony Pollock, NICTA

14. Residential – Parameter Extraction I • Cluster decay time constant • Ray decay time constant Method: Linear Regression Tony Pollock, NICTA

15. Residential – Cluster Decay Rate v360 Tony Pollock, NICTA

16. Residential – Ray Decay Rate v360 Tony Pollock, NICTA

17. Residential – Parameter Extraction II • Cluster arrival rate 1/ • Ray arrival rate 1/ Method: distribution fitting tool (dfittool.m) Note: arrival times from Poisson distribution (95% confidence – see Goodness of Fit testing) Tony Pollock, NICTA

18. Residential – Cluster Arrival Rate v360 Tony Pollock, NICTA

19. Residential – Ray Arrival Rate v360 Tony Pollock, NICTA

20. Distribution Extraction • Multipath Gains • Angle of Arrival Method: Goodness of Fit and distribution fitting tool Tony Pollock, NICTA

21. Goodness of Fit Summary • Probability Plotting • selection of the distribution hypothesis based on preliminary fitting analysis • use an inverse distribution scale so that a cumulative distribution function (CDF) plots as a straight line • Regression testing • to fit a straight line on the probability plot • Error plotting • gives the confidence level of the goodness of fit • Mean Squared error gives the error value between the data and the hypothesis distribution • Steps 1-3 done for every hypothesis distribution • Parameter extraction • dfittool used to extract distribution parameters Tony Pollock, NICTA

22. Residential – AoA Distribution Tony Pollock, NICTA

23. Residential – AoA Distribution Tony Pollock, NICTA

24. Residential – AoA Distribution Tony Pollock, NICTA

25. Residential – Multipath Gain Distribution • No conclusive result at this time • Similar in process to AoA and arrival rate distributions • Further work required Tony Pollock, NICTA

26. Tx ant. [ns] [ns] [ns] [ns] [deg] Number of clusters RMS delay spread [ns] Mean excess delay spread[ns] 1/ 1/ v15 2.94 0.454 3.833 0.706 12.91 3 1.399 2.399 v30 4.54 0.222 4.667 0.597 14.47 3 3.815 2.02 v60 5.88 0.582 2.75 0.658 14.95 6 4.85 5.02 v360 9.09 1.25 2.833 0.642 10.29 6 6.51 7.48 ResidentialSummary of Parameters Extracted Tony Pollock, NICTA

27. Identical analysis as for Residential environment Office Summary of Parameters Extracted Tx ant. [ns] [ns] [ns] [ns] [deg] Number of clusters RMS delay spread [ns] Mean excess delay spread[ns] 1/ 1/ v30 113.63 1.492 25.91 0.535 15.04 3 49.01 74 v360 76.03 0.833 12.87 0.453 10.47 6 40.47 78 Tony Pollock, NICTA

28. Remaining Work • Improve MPC selection • Determine multipath gain distribution and parameters • Determine time and angle correlation • Generate model realization technique • Timeline: completed before Jacksonville meeting (May) Tony Pollock, NICTA