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Jan 2007 doc.: IEEE 802.15-07/0533r0 Hiroshi Harada (NICT), Rick Roberts (Intel)Slide 1Submission Project: IEEE P802.15 Working Group for Wireless Personal.

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Presentation on theme: "Jan 2007 doc.: IEEE 802.15-07/0533r0 Hiroshi Harada (NICT), Rick Roberts (Intel)Slide 1Submission Project: IEEE P802.15 Working Group for Wireless Personal."— Presentation transcript:

1 Jan 2007 doc.: IEEE /0533r0 Hiroshi Harada (NICT), Rick Roberts (Intel)Slide 1Submission Project: IEEE P Working Group for Wireless Personal Area Networks (WPANs) Submission Title: [CM MATLAB Release 1.0 Support Document] Date Submitted: [Nov 2007] Source: [Rick Roberts] Company [Intel, Corp], Source: [Hiroshi Harada, Ryuhei Funada, Hirokazu Sawada ] Company [NICT], Re: [] Abstract:[This document supports release 1.0 of the Matlab CM code.] behavior Purpose:[] Notice:This document has been prepared to assist the IEEE P 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 P

2 Jan 2007 doc.: IEEE /0533r0 Hiroshi Harada (NICT), Rick Roberts (Intel)Slide 2Submission This document “documents” the version 1.0 release of the MATLAB CM code.

3 Jan 2007 doc.: IEEE /0533r0 Hiroshi Harada (NICT), Rick Roberts (Intel)Slide 3Submission Channel ModelEnvironment CM1Residential LOS TSV & SV CM2Residential NLOS TSV & SV CM3Office LOS TSV CM4Office NLOS TSV CM5Library LOS SV CM6Library NLOS SV CM7N/A CM8N/A CM9Desktop LOS TSV & SV CM10Corridor LOS SV

4 Jan 2007 doc.: IEEE /0533r0 Hiroshi Harada (NICT), Rick Roberts (Intel)Slide 4Submission Overloaded Channel Models ModelEnvironment CM1.1TSV - TX: 360, RX: 15 CM1.2TSV - TX: 60, RX: 15 CM1.3TSV - TX: 30, RX: 15 CM1.4TSV - TX: 15, RX: 15 CM1.5SV - TX: 360, RX: 15 ModelEnvironment CM3.1TSV - TX: 30, RX: 30 CM3.2TSV - TX: 60, RX: 60 ModelEnvironment CM9.1TSV - TX: 30, RX: 30 CM9.2TSV - TX: 60, RX: 60 CM9.3SV - TX: 360, RX: 21 dBi

5 Jan 2007 doc.: IEEE /0533r0 Hiroshi Harada (NICT), Rick Roberts (Intel)Slide 5Submission Pertinent Definitions source: c

6 Jan 2007 doc.: IEEE /0533r0 Hiroshi Harada (NICT), Rick Roberts (Intel)Slide 6Submission    AoA ToA   1 1 2 2    LOS Fig 1: Graphical representation of the CIR as a function of TOA and AOA. Source: c

7 Jan 2007 doc.: IEEE /0533r0 Hiroshi Harada (NICT), Rick Roberts (Intel)Slide 7Submission Small Scale Parameterization

8 Jan 2007 doc.: IEEE /0533r0 Hiroshi Harada (NICT), Rick Roberts (Intel)Slide 8Submission Small Scale Parameterization (2)

9 Jan 2007 doc.: IEEE /0533r0 Hiroshi Harada (NICT), Rick Roberts (Intel)Slide 9Submission Source: c } These first 3 parameters are stored in the data base but not used in the simulation. Is shadowing part of the link budget or should it be included in the simulation?

10 Jan 2007 doc.: IEEE /0533r0 Hiroshi Harada (NICT), Rick Roberts (Intel)Slide 10Submission Configuration of the code

11 Jan 2007 doc.: IEEE /0533r0 Hiroshi Harada (NICT), Rick Roberts (Intel)Slide 11Submission Start Set channel model number (cm_num), the number of channel realizations (num_channels), center frequency (fc[Hz]), minimum time resolution (Ts [ns]), andtypes of antenna pattern (ant_type) Call function to obtain parameters for TSV channel model call functions to generate N continuous impulse responses Done Plot out the impulse responses, and calculate RMS delay spreadsand K factors Save N discrete impulse responses and some of parameters Call functions to resample the continuous impulse responses TSV or SV Call function to obtain parameters for SV channel model call functions to generate N continuous impulse responses SV TSV Save N continuous impulse responses and some of parameters (1) (2) (3) (4) (5) (6) (7)

12 Jan 2007 doc.: IEEE /0533r0 Hiroshi Harada (NICT), Rick Roberts (Intel)Slide 12Submission TSV Code Support

13 Jan 2007 doc.: IEEE /0533r0 Hiroshi Harada (NICT), Rick Roberts (Intel)Slide 13Submission Overview of TSV model Relative Amplitude S-V model response Cluster Rician factor (  K) Time of Arrival ray Rician factor (  k)  Amplitude of each ray exponentially decays by the order of e -t    : Amplitude of each cluster exponentially decays by the order of e -t/  Each cluster arrives according to the exponential distribution with average value of 1/  Each ray arrives according to the exponential distribution with average value of 1/ Statistical two-path response (LOS desktop model) Fixed impulse response (Other models)

14 Jan 2007 doc.: IEEE /0533r0 Hiroshi Harada (NICT), Rick Roberts (Intel)Slide 14Submission Definition of TSV model Two-path parameters (4)S-V parameters (7)Antenna parameters (2) Two-path response Arrival rate: Poisson process CIR: (Complex impulse response) PL d : Path loss of the first impulse response t: time[ns]  ・  Delta function l = cluster number, m = ray number in l-th cluster, L = total number of clusters; M l = total number of rays in the l-th cluster; T l = arrival time of the first ray of the l-th cluster;  l,m = delay of the m-th ray within the l-th cluster relative to the firs path arrival time, T l ;  0 = Average power of the first ray of the first cluster  l ∝ Uniform[0,2  arrival angle of the first ray within the l-th cluster  l,m = arrival angle of the m-th ray within the l-th cluster relative to the first path arrival angle,  l Rician factor (2) A NLOS : Constant attenuation for NLOS

15 Jan 2007 doc.: IEEE /0533r0 Hiroshi Harada (NICT), Rick Roberts (Intel)Slide 15Submission Summary of available TSV channel models by MATLAB LOSNLOS Residential CM1 AvailableCM2 Available (LOS component extraction) Office CM3 AvailableCM4 Available Desktop CM9 AvailableN/A Library CM10N/A Measurement and analysis to obtain TSV channel model parameters are finished by NICT. MATLAB code is now available using analyzed parameters.

16 Jan 2007 doc.: IEEE /0533r0 Hiroshi Harada (NICT), Rick Roberts (Intel)Slide 16Submission Channel Model Parameters for TSV model ParameterCM1.1CM1.2CM1.3CM1.4CM3.1CM3.2CM4.1CM4.2 Λ [1/ns] λ [1/ns] Γ [ns] γ [ns] σ cluster σ ray σ φ Δk [dB] Ω(d) [dB] d d n d A NLOS

17 Jan 2007 doc.: IEEE /0533r0 Hiroshi Harada (NICT), Rick Roberts (Intel)Slide 17Submission Channel Model Parameters for TSV model (cont’) ParameterCM7.1CM7.2 Λ [1/ns] λ [1/ns] Γ [ns] γ [ns] σ cluster σ ray σ φ Δk [dB] Ω(d) [dB]4.44d d n d 22 A NLOS 00 ParameterCM7.1CM7.2 h 1 Uniform dist. Range: Uniform dist. Range: h 2 Uniform dist. Range: Uniform dist. Range: dUniform dist. Range: d±0.3 Uniform dist. Range: d±0.3 G t1 ※※ G r1 ※※ G t2 ※※ G r2 ※※ ※ Antenna gain are calculated by reference antenna model. (Ref. Doc. No )

18 Jan 2007 doc.: IEEE /0533r0 Hiroshi Harada (NICT), Rick Roberts (Intel)Slide 18Submission tg3c_tsv_results_disp.m (to show some figures) Function calls in TSV channel model MATLAB code tg3c_tsv_eval_r6.m (Main script M-file in TSV channel model MATLAB code) tg3c_tsv_params_r3.m tg3c_tsv_ct_r5.m tg3c_sv_cnvrt_ct.m resample.m (built-in function) tsv_beta_calc_r4.m tsv_ant_gain_r5.m tsv_laplacernd.m tsv_poissrnd.m tg3c_tsv_menu_disp.m (for dialogical parameter input) Explained in this documents

19 Jan 2007 doc.: IEEE /0533r0 Hiroshi Harada (NICT), Rick Roberts (Intel)Slide 19Submission Flowchart of tg3c_tsv_eval_r6.m Red closed line is related to TSV channel model in continuous time Start of TSV model Set channel parameters such as channel model index (cm_num), center frequency (fc 0 [GHz]), number of channel realizations (num_channels) using function tg3c_tsv_menu_disp.m Call function tg3c_tsv_params_r3.m to load TSV channel model parameters Call function tg3c_tsv_ct_r5.m to generate num_channels sets of amplitude of rays in continuous time (after and/or before antenna gain convolution ) with their TOA and AOA Plot the impulse responses, and calculate RMS delay spread and K factor (if needed) Save num_channels sets of amplitude, TOA and AOA of rays in continuous time and/or num_channels sets of discrete impulse responses and some of parameters (if needed) Call function resample.m and then tg3c_tsv_convrt_ct_r2.m to generate num_channels sets of impulse responses (if needed) done

20 Jan 2007 doc.: IEEE /0533r0 Hiroshi Harada (NICT), Rick Roberts (Intel)Slide 20Submission Summary of tg3c_tsv_eval_r6.m  Main script M-file  This function generates sets of AOA, TOA, and amplitude of rays in continuous time on the basis of TSV model, and also generates and evaluates discrete impulse responses, which are generated using the sets of the AOA, TOA and amplitude of rays in the continuous time.  MATLAB codes distributed in IEEE a was modified  This M-file are composed of six sub-functions – tg3c_tsv_param_r.m – tg3c_tsv_ct_r.m – tg3c_sv_cnvrt_ct.m – resample.m (built-in function) – tg3c_tsv_menu_disp.m (for dialogical parameter input) – tg3c_tsv_results_disp.m (to show some figures)

21 Jan 2007 doc.: IEEE /0533r0 Hiroshi Harada (NICT), Rick Roberts (Intel)Slide 21Submission function tg3c_tsv_param_r3.m Red closed line is related to TSV channel model in continuous time Start of TSV model Set channel parameters such as channel model index (cm_num), center frequency (fc 0 [GHz]), number of channel realizations (num_channels) using function tg3c_tsv_menu_disp.m Call function tg3c_tsv_params_r3.m to load TSV channel model parameters Call function tg3c_tsv_ct_r5.m to generate num_channels sets of amplitude of rays in continuous time (after and/or before antenna gain convolution ) with their TOA and AOA Plot the impulse responses, and calculate RMS delay spread and K factor (if needed) Save num_channels sets of amplitude, TOA and AOA of rays in continuous time and/or num_channels sets of discrete impulse responses and some of parameters (if needed) Call function resample.m and then tg3c_tsv_convrt_ct_r2.m to generate num_channels sets of impulse responses (if needed) done

22 Jan 2007 doc.: IEEE /0533r0 Hiroshi Harada (NICT), Rick Roberts (Intel)Slide 22Submission Summary of tg3c_tsv_params_r3.m  This function M-file outputs channel model parameters according to channel model index (cm_num)  Antenna beam-widths described in this function are same as those used for the experiments, but Rx antenna beam-widths can be changed outside this function  Relative power of the LOS component is calculated from carrier frequency (fc [Hz]) and assuming distance (adist [m])

23 Jan 2007 doc.: IEEE /0533r0 Hiroshi Harada (NICT), Rick Roberts (Intel)Slide 23Submission function [adist, nlos, los_beta_flag, Omega0, smallk, Lmean, Lam, lambda, Gam,... gamma, std_ln_1, std_ln_2, sigma_fai, L_pl, tx_hpbw, rx_hpbw] = tg3c_tsv_params_r3(cm_num, fc) % Arguments % cm_num channel model number % fc carrier center frequency in GHz % Output parameters % nlos flag of NLOS environment % Lmean number of Average arrival clusters % Lam cluster arrival rate (clusters per nsec) % lambda ray arrival rate (rays per nsec) % Gam cluster decay factor (time constant, nsec) % gamma ray decay factor (time constant, nsec) % std_ln_1 standard deviation of log-normal variable for cluster fading % std_ln_2 standard deviation of log-normal variable for ray fading % sigma_fai cluster angle-of-arrival spread in deg % Parameters added by NICT % adist assuming distance between Tx and Rx in mappded usage model (meter) % los_beta_flag flag used for beta calculation (Renamed from LOS_desktop_flag) % this flag is also used for making LOS extraction for NLOS condition from a LOS condition. % If this value is -1, the LOS component extraction mode is done % Omega0 cluster power level % smallk small Rician factor % L_pl pathloss of the LOS component normalized with that of 1m % tx_hpbw Tx half-power angle in deg % rx_hpbw Rx half-power angle in deg Parameters defined in tg3c_tsv_params_r3.m

24 Jan 2007 doc.: IEEE /0533r0 Hiroshi Harada (NICT), Rick Roberts (Intel)Slide 24Submission %************* LOS Residential channel model (UM1) ******************* if cm_num == 11 % Experimental data TX : 360deg, RX : 15deg adist = 5; nlos = 0; los_beta_flag = 0; Omega0 = -88.7; smallk = 4.34; Lmean = 9; Lam = 1/5.24; lambda = 1/0.820; Gam = 4.46; gamma = 6.25; std_ln_1 = 6.28; std_ln_2 = 13.0; sigma_fai = 49.8; tx_hpbw = 360; rx_hpbw = 15; L_pl = -20*log10(4*pi*adist/ramda); Example of parameters defined in tg3c_tsv_params_r3.m

25 Jan 2007 doc.: IEEE /0533r0 Hiroshi Harada (NICT), Rick Roberts (Intel)Slide 25Submission function tg3c_tsv_ct_r5.m Start of TSV model Set channel parameters such as channel model index (cm_num), center frequency (fc 0 [GHz]), number of channel realizations (num_channels) using function tg3c_tsv_menu_disp.m Call function tg3c_tsv_params_r3.m to load TSV channel model parameters Call function tg3c_tsv_ct_r5.m to generate num_channels sets of amplitude of rays in continuous time (after and/or before antenna gain convolution ) with their TOA and AOA Plot the impulse responses, and calculate RMS delay spread and K factor (if needed) Save num_channels sets of amplitude, TOA and AOA of rays in continuous time and/or num_channels sets of discrete impulse responses and some of parameters (if needed) Call function resample.m and then tg3c_tsv_convrt_ct_r2.m to generate num_channels sets of impulse responses (if needed) done

26 Jan 2007 doc.: IEEE /0533r0 Hiroshi Harada (NICT), Rick Roberts (Intel)Slide 26Submission Summary of tg3c_tsv_ct_r5.m  This function generates sets of AOA, TOA, and power of rays in continuous time on the basis of TSV model  This function consists of four sub-functions – tsv_beta_calc_r4.m – tsv_ant_gain_r5.m – tsv_laplacernd.m – tsv_poissrnd.m

27 Jan 2007 doc.: IEEE /0533r0 Hiroshi Harada (NICT), Rick Roberts (Intel)Slide 27Submission Flowchart of tg3c_tsv_ct_r5.m

28 Jan 2007 doc.: IEEE /0533r0 Hiroshi Harada (NICT), Rick Roberts (Intel)Slide 28Submission function [beta,h,aoa,t,t0,np,cl_idx] = tg3c_tsv_ct_r5(... nlos, num_channels,... % Channel params adist, fc, los_beta_flg, L_pl,... % T-S-V model params Lam, lambda, Gam, gamma, std_ln_1, std_ln_2,... % SV model params Lmean, Omega0, smallk, sigma_fai,... tx_hpbw, rx_hpbw, ant_type) % Antenna model params % Arguments: % nlos : Flag of NLOS environment % num_channels : Number of channel realizations % Lam : Cluster arrival rate (clusters per nsec) % lambda : Ray arrival rate (rays per nsec) % Gam : Cluster decay factor (time constant, nsec) % gamma : Ray decay factor (time constant, nsec) % std_ln_1 : Standard deviation of log-normal variable for cluster fading % std_ln_2 : Standard deviation of log-normal variable for ray fading % Lmean : Average number of arrival clusters Arguments of tg3c_tsv_ct_r5.m

29 Jan 2007 doc.: IEEE /0533r0 Hiroshi Harada (NICT), Rick Roberts (Intel)Slide 29Submission % Parameters added for making TG3c channel model % fc : Carrier frequency [GHz] % los_beta_flg : Flag used for beta calculation % L_pl : path loss regarding LOS component % Omega0 : Cluster power level % smallk : Small Rician effect % sigma_fai : Cluster arrival angle spread in deg % tx_hpbw : TX half-power angle in deg % rx_hpbw : RX half-power angle in deg % ant_type : Antenna model used in simulation % 1: Simple Gaussian distribution % 2: Reference antenna model % Output values: % h : Amplitudes of rays in clusters including LOS component in continuous time % t : TOAs of h % t0 : Arrival time of the first ray of the first SV cluster % np : Number of paths in clusters including LOS component % Output values added for making TG3c channel model % beta : Amplitude of the LOS component % aoa : AOAs of rays in clusters including LOS component in continuous time Arguments of tg3c_tsv_ct_r5.m (Cont’)

30 Jan 2007 doc.: IEEE /0533r0 Hiroshi Harada (NICT), Rick Roberts (Intel)Slide 30Submission %****************** Initialize and precompute some things ****************** std_L = 1/sqrt(2*Lam); % std dev (nsec) of cluster arrival spacing std_lam = 1/sqrt(2*lambda); % std dev (nsec) of ray arrival spacing %************************** Simulation preparation ************************* h_len = 1000; % there must be a better estimate of # of paths than this ngrow = 1000; % amount to grow data structure if more paths are needed %Output variables beta = zeros(1,num_channels); h = zeros(h_len,num_channels); t = zeros(h_len,num_channels); t0 = zeros(1,num_channels); np = zeros(1,num_channels); aoa = zeros(h_len,num_channels); %added for making TG3c channel model cl_idx = zeros(h_len,num_channels); %added for making TG3c channel model for display Constant value for calculating TOAs of clusters and rays in each cluster Initial number of array for storing results is set to be This number increases in increments of 1000 if necessary Blue lines are added by NICT for making TSV MATLAB codes Modification points in tg3c_tsv_ct_r5.m (1/11)

31 Jan 2007 doc.: IEEE /0533r0 Hiroshi Harada (NICT), Rick Roberts (Intel)Slide 31Submission for k = 1:num_channels % loop over number of channels tmp_h = zeros(size(h,1),1); tmp_t = zeros(size(h,1),1); tmp_aoa = zeros(size(h,1),1); %added for making TG3c channel model tmp_clidx = zeros(size(h,1),1); %added for making TG3c channel model %Set the number of generated clusters L = max(1, tsv_poissrnd(Lmean)); % tsv_poisson.m is added for making TG3c channel model %Initialize counter regarding the number of rays in clusters including %LOS component path_ix = 0; Arrays for storing amplitudes, TOAs, and AOAs of rays in one channel realization Number of clusters are determined according to the Poisson distribution Counter for counting the number of generated paths Modification points in tg3c_tsv_ct_r5.m (2/11)

32 Jan 2007 doc.: IEEE /0533r0 Hiroshi Harada (NICT), Rick Roberts (Intel)Slide 32Submission %The following lines are added for making TG3c channel model if nlos==0 % LOS condition expressed by TSV model if los_beta_flg == 1 % Desktop model % Compute LOS component (beta) on the basis of TSV model [beta0] = tg3c_tsv_beta_calc_pre_fin_rev4(fc, adist, tx_hpbw, rx_hpbw, ant_type); beta(k)=beta0; else % The other LOS models % LOS path loss beta(k)=1; end path_ix = path_ix + 1; %path_ix=1; tmp_h(path_ix)=beta(k); tmp_t(path_ix) = 0; tmp_clidx(path_ix) = 1; %LOS component assumed to be a cluster in display tmp_aoa(path_ix) = 0; else % NLOS condition expressed by TSV model if los_beta_flg == -1 % LOS extraction mode beta(k)=0; end When nlos =1 and los_beta_flg = -1, LOS extraction mode are applied and beta is set to be 0 In the case of all the LOS models except LOS desktop model,  When nlos=0 and LOS_beta_flg =1, beta will be calculated in a function of LOS desktop behavior Modification points in tg3c_tsv_ct_r5.m (3/11)

33 Jan 2007 doc.: IEEE /0533r0 Hiroshi Harada (NICT), Rick Roberts (Intel)Slide 33Submission Summary of tsv_beta_calc_r4.m  This function computes amplitude of LOS component (beta) on the accordance with the two-path theory of TSV model function [beta] = tsv_beta_calc_r4(fc, muD, tx_hpbw, rx_hpbw, ant_type) % Arguments: % fs : Center carrier frequency % muD : Average distance between TX and RX % tx_hpbw : TX half-power angle in deg % rx_hpbw : RX half-power angle in deg (horizontal and vartical gain are same) % ant_type : Antenna model used in simulation % Output values: % beta : Amplitude of LOS component (beta)

34 Jan 2007 doc.: IEEE /0533r0 Hiroshi Harada (NICT), Rick Roberts (Intel)Slide 34Submission Block diagram of beta calculation in tsv_beta_calc_r4.m D, h1,h2 (in this figure, the heights of Tx and Rx) fluctuates according to the uniform distribution within +-30cm from the average value) Beta can be calculated as below.

35 Jan 2007 doc.: IEEE /0533r0 Hiroshi Harada (NICT), Rick Roberts (Intel)Slide 35Submission How to calculate  t  t,  r  r in tsv_beta_calc_r4.m D tt tt rr rr

36 Jan 2007 doc.: IEEE /0533r0 Hiroshi Harada (NICT), Rick Roberts (Intel)Slide 36Submission % gamma0 : Reflection coefficient gamma0 = 1; % Assuming angle of incidence is large % these parameters will be discussed D0 = [ ]+muD; % Range of D (m) Ht = [0 0.3]; % Range of Ht (m) Hr = [0 0.3]; % Range of Hr (m) % Determine TX and RX heights by the Monte-carlo method h1 = (Ht(2)-Ht(1))*rand+Ht(1); h2 = (Hr(2)-Hr(1))*rand+Hr(1); % Determine distance between TX and RX by the Monte-carlo method D = (D0(2)-D0(1))*rand+D0(1); % Wave length ramda = 3e8/fc; Determine ranges of D and the heights of Tx and Rx antennas The heights of Tx and Rx antennas vary according to the uniform distribution MATLAB code tsv_beta_calc_r4.m

37 Jan 2007 doc.: IEEE /0533r0 Hiroshi Harada (NICT), Rick Roberts (Intel)Slide 37Submission %********** Calculate the reflection point of the re f lection path ********** tx_p = i.*h1; rx_p = D+i.*h2; rfl_p = D*h1/(h1+h2); %************ Determine direction of direct and reflection paths *********** tp = angle([rx_p-tx_p (tx_p-rx_p) rfl_p-tx_p (rfl_p-rx_p)]); tp = tp./pi*180; dr_theta = tp(1); dr_fai = dr_theta; rfl_theta = tp(3); rfl_fai = -rfl_theta; Set the positions of Tx and Rx antennas and the reflection point of radio wave transmitted from Tx in vector Determine angles of departure and arrival of the radio wave in the horizontal axis Calculate  t,  t,  r,  r shown in slide X MATLAB code tsv_beta_calc_r4.m (Cont’)

38 Jan 2007 doc.: IEEE /0533r0 Hiroshi Harada (NICT), Rick Roberts (Intel)Slide 38Submission % TX % Direct path gt1 = tsv_ant_gain_r5(ant_type, tx_hpbw, dr_theta); % Reflection path gt2 = tsv_ant_gain_r5(ant_type, tx_hpbw, rfl_theta); % RX % Direct path gr1 = tsv_ant_gain_r5(ant_type, rx_hpbw, dr_fai); % Reflection path gr2 = tsv_ant_gain_r5(ant_type, rx_hpbw, rfl_fai); beta = (muD/D).*abs(gt1.*gr1+gt2.*gr2....*gamma0.*exp(j.*(2*pi./ramda).*(2.*h1.*h2./D) Determine electric strength of Tx and Rx antennas (in slide X) See the equation expressed in slide X MATLAB code tsv_beta_calc_r4.m (Cont’)

39 Jan 2007 doc.: IEEE /0533r0 Hiroshi Harada (NICT), Rick Roberts (Intel)Slide 39Submission Summary of tsv_ant_gain_r5.m  This function M-file outputs electric strength according to angle of arrival (AOA). The antenna models contributed in TG3C can be used: –Reference antenna model (IEEE c) –Gaussian-distributed antenna model (IEEE c) function g = tsv_ant_gain_r5(ant_type, hpbw, fai) % Arguments % ant_type : Antenna model used in simulation % 1: Reference antenna model % 2: Gaussian-distributed antenna model % hpbw : Half-power angle in deg % fai : Angle of arrival in deg % Option % fig_on : Index of figure that shows relative antenna gain % TITLE : figure title % Output value % g : Electric strength (True value )

40 Jan 2007 doc.: IEEE /0533r0 Hiroshi Harada (NICT), Rick Roberts (Intel)Slide 40Submission switch ant_type case 1 %Reference antenna model g = zeros(size(fai)); for ii=1:length(fai) theta_ml=2.6*hpbw; G0 = 10*log10(( /sin(hpbw*pi/180/2))^2); if abs(fai(ii))<=theta_ml/2 G = G * (2*abs(fai(ii))./hpbw).^2; else G = *log(hpbw) ; end g0=G-G0; g(ii) = 10.^(g0/20); end case 2 %Gaussian-distributed antenna model alfa = 4*log(2)./(hpbw*pi/180).^2; g = sqrt(exp(-alfa.*abs(fai./180*pi).^2)); otherwise error('Antenna model error') end MATLAB code tsv_ant_gain_r4.m

41 Jan 2007 doc.: IEEE /0533r0 Hiroshi Harada (NICT), Rick Roberts (Intel)Slide 41Submission Flowchart of tg3c_tsv_ct_r4.m (again)

42 Jan 2007 doc.: IEEE /0533r0 Hiroshi Harada (NICT), Rick Roberts (Intel)Slide 42Submission %************************** SV cluster computation ************************* % Determine TOA and AOA of the fisrt SV cluster Tc = (std_L*randn)^2 + (std_L*randn)^2; %added for making TG3c channel model %AOA of clusters is distributed according to the uniform distribution cl_ang_deg = 360*rand-180; if nlos == 1 && los_beta_flg == -1 t0(k) = Tc; end % delta K factor dK = L_pl-Omega0; %added for making TG3c channel model Tc0 = Tc; Determine cluster’s TOA according to the Poisson arrival distribution, which is same as those in 15.3a and 15.4a Calculate AOA of the first cluster. The angle is uniformly distributed from -180 to 180 degree In the case of NLOS condition, the first arrival time of ray is stored, which is used for display Calculate Rician factor (dK) Modification points of tg3c_tsv_ct_r4.m (4/11)

43 Jan 2007 doc.: IEEE /0533r0 Hiroshi Harada (NICT), Rick Roberts (Intel)Slide 43Submission for ncluster = 1:L % relative arrival time of the first ray is set to be 0 in each cluster Tr = 0; %added for making TG3c channel model %fray: flag set to be 1 when it is the first arrival ray fray = 1; Mcluster = std_ln_1*randn; %Pcluster = 10*log10(exp(-1*Tc/Gam))+Mcluster; % total cluster power %added for making TG3c channel model %The first ray of the first cluster is related to delta K factor Pcluster = (-dK-10*(Tc-Tc0)/Gam./log(10))+Mcluster; Process of cluster generation is performed with cluster by cluster TOA of the first ray is set to be 0 in each cluster In the case of only the first ray, flag is set to be 1 The power of a cluster is distributed by the log-normal distribution with variance of std_ln_1 and mean of (dK-10*(Tc-Tc0)/Gam./log(10)). The average power of the first ray in each cluster is dK [dB] because Tc=Tc0 Modification points of tg3c_tsv_ct_r4.m (5/11)

44 Jan 2007 doc.: IEEE /0533r0 Hiroshi Harada (NICT), Rick Roberts (Intel)Slide 44Submission Tr_len = 10*gamma; while (Tr < Tr_len), t_val = (Tc+Tr); % TOA of this ray % %The following lines are added for making TG3c channel model % Memo: first ray of the first cluster is set to the mean of the cluster. if fray == 1 % AOA = cluster arrival angle (first ray in each cluster) ray_ang_deg = cl_ang_deg; else % AOA = cluster arrival angle + ray arrival angle % Recalculate if AOA is more than 180 deg or less than -180 deg while 1 % Determine AOA of the ray according to the Laplace distribution in deg ray_ang_deg0 = tsv_laplacernd(sigma_fai); % average is 0 deg if abs(ray_ang_deg0) <= 180 break; end ray_ang_deg = cl_ang_deg+ray_ang_deg0; end ray_aoa_c = exp(j.*ray_ang_deg./180*pi); aoa_val = angle(ray_aoa_c)/pi*180; The TOA of ray is calculated until Tr is larger than Tr_len(10*gamma), the value of which is same as that written in the 15.4a MATLAB code Calculated TOA of this ray AOA of the first ray is set to the AOA of cluster The angles of the other ray is Laplace distributed so as that mean values of the rays AOA is the AOA of the cluster. If the angle is larger than degree, the angle is re-generated. Calculate AOA of the ray in deg Modification points of tg3c_tsv_ct_r4.m (6/11)

45 Jan 2007 doc.: IEEE /0533r0 Hiroshi Harada (NICT), Rick Roberts (Intel)Slide 45Submission Mray = std_ln_2*randn; if fray == 1 %First ray of a cluster %Pray = 10*log10(exp(-Tr/gamma))+Mray; Pray = Mray; %Tr = 0 if small_dk = 0 % Set flag to be 0 after the first-ray's power calculation fray=0; else % Convert the base of small Racian facter small_dk = smallk.*10*log10(exp(1)); Pray = -10*Tr/gamma./log(10)-small_dk+Mray; %Pray=10*log10(exp(-Tr/gamma))-small_dk+Mray; end h_val = 10^((Pcluster+Pray)/20); The power of ray is distributed by the log- normal distribution with variance of std_ln_2 2 and mean of 10*log10(exp(- Tr/gamma))-small_dk. Pray: power of ray, fray: flag (1:first ray and 0:othres) Amplitude of the ray, fray: flag (1:first ray) Modification points of tg3c_tsv_ct_r4.m (7/11)

46 Jan 2007 doc.: IEEE /0533r0 Hiroshi Harada (NICT), Rick Roberts (Intel)Slide 46Submission % The following lines are the same as that of 15.4a MATLAB code except for some notes % Increment the number of paths path_ix = path_ix + 1; if path_ix > h_len, % grow the output structures to handle more paths as needed tmp_h = [tmp_h; zeros(ngrow,1)]; tmp_t = [tmp_t; zeros(ngrow,1)]; h = [h; zeros(ngrow,num_channels)]; t = [t; zeros(ngrow,num_channels)]; %added for making TG3c channel model tmp_aoa = [tmp_aoa; zeros(ngrow,1)]; tmp_clidx = [tmp_clidx; zeros(ngrow,1)]; aoa = [aoa; zeros(ngrow,num_channels)]; cl_idx = [cl_idx; zeros(ngrow,num_channels)]; Increment the number of rays If prepared arrays are fully occupied, 1000 arrays are added to the old arrays Store the amplitude, TOA, AOA, and cluster index of the ray Modification points of tg3c_tsv_ct_r4.m (8/11)

47 Jan 2007 doc.: IEEE /0533r0 Hiroshi Harada (NICT), Rick Roberts (Intel)Slide 47Submission Modification points of tg3c_tsv_ct_r4.m (9/11) h_len = h_len + ngrow; end tmp_h(path_ix) = h_val; tmp_t(path_ix) = t_val; tmp_clidx(path_ix) = ncluster+1; %added for making TG3c channel model tmp_aoa(path_ix) = aoa_val; Tr = Tr + (std_lam*randn)^2 + (std_lam*randn)^2; end % Set the TOA and AOA of the next cluster to be generated Tc = Tc + (std_L*randn)^2 + (std_L*randn)^2; cl_ang_deg = 360*rand-180; %added for making TG3c channel model end Set TOA of the next ray Set TOA and AOA of the next cluster

48 Jan 2007 doc.: IEEE /0533r0 Hiroshi Harada (NICT), Rick Roberts (Intel)Slide 48Submission Modification points of g3c_tsv_ct_r4.m (10/11) % The following lines are the same as that of 15.4a MATLAB code except for some notes %********************************* Sorting ********************************* np(k) = path_ix; % Number of rays (or paths) for this realization [sort_tmp_t,sort_ix] = sort(tmp_t(1:np(k))); % sort in ascending time order t(1:np(k),k) = sort_tmp_t; h(1:np(k),k) = tmp_h(sort_ix(1:np(k))); aoa(1:np(k),k) = tmp_aoa(sort_ix(1:np(k))); %added for making TG3c channel model %Attach the generated cluster index to each ray cl_idx(1:np(k),k) = tmp_clidx(sort_ix(1:np(k))); %added for making TG3c channel model

49 Jan 2007 doc.: IEEE /0533r0 Hiroshi Harada (NICT), Rick Roberts (Intel)Slide 49Submission Modification points of tg3c_tsv_ct_r4.m (11/11) %************** Generate continuous complex impulse responses ************** %************** with antenna gain convolution ************** % The following lines are added for making TG3c channel model if op_num == 2 || op_num == 3 tGrh = tsv_ant_gain_r5(ant_type,rx_hpbw, aoa); for ij=1:num_channels tGrh(np(ij)+1:end,ij)=0; end h2 = h.*tGrh; else h2 = []; end Amplitude or rays are multiplied by the electric strength Calculate electric strength obtained form AOA of the ray and antenna gain

50 Jan 2007 doc.: IEEE /0533r0 Hiroshi Harada (NICT), Rick Roberts (Intel)Slide 50Submission S-V cluster Antenna height Tx: 170 mm Rx: 150 mm Beam width: 60 deg Distance: 3m LOS component S-V clusters Beam width: 60 deg Assuming distance: 3m LOS component Comparison of experimental and simulated results Experimental resultsSimulated results Average RMS delay spread 10.6[ns]7.9 [ns] (Dependent on the distribution of β and antenna pattern ) (a) Experimental result(b) Simulation result Simulation data is a snap-shot.

51 Jan 2007 doc.: IEEE /0533r0 Hiroshi Harada (NICT), Rick Roberts (Intel)Slide 51Submission File format of MAT file for set of the TOA, AOA, and amplitude of ray h_ct(1,1)h_ct(1,2)h_ct(1,N ch,) h_ct(2,1)h_ct(2,2)h_ct(2,N ch ) h_ct(np(1),1) h_ct(np(2)- 1,2) 0 h_ct(np(2),2) 00 h_ct(np(N ch )-1, N ch ) 00 h_ct(np(N ch ), N ch ) # of channel realizations (num_channels denoted by N ch ) # of rays  Generated MAT file (named tsv_goldset_CM**) includes Matrix of TOA(t_ct), AOA(aoa_ct) and amplitude without convolution of any antenna gain (h_ct) as well as number of paths (np). Formats of h_ct matrix and np are shown below. aoa_ct and t_ct have the same structure of matrix as h_ct. np(1)np(2)Np(N ch ) # of channel realizations (num_channels denoted by N ch ) Channel model index

52 Jan 2007 doc.: IEEE /0533r0 Hiroshi Harada (NICT), Rick Roberts (Intel)Slide 52Submission  Generated MAT file (named tsv_dIR_cm**_n*_at*_fs*) includes Discrete impulse responses (combined with convolution of antenna gain) (h). Format of h matrix is shown below. aoa_ct and t_ct have the same structure of matrix as h. Channel model index File format of MAT file for discrete impulse responses h(1,1)h(1,2)h(1,N ch,) h(2,1)h (2,2)h(2,N ch ) h(ngrow,1)h(ngrow,2)h(ngrow,N ch ) # of channel realizations (num_channels denoted by N ch ) # of taps (dependentsample rate) Number of channel realizations Antenna model Sample rate

53 Jan 2007 doc.: IEEE /0533r0 Hiroshi Harada (NICT), Rick Roberts (Intel)Slide 53Submission Example of Power Delay Profile (CM1.3) PDP without convolution of antenna gain (*) Power of LOS component is normalized to be dB PDP with RX antenna beam-width Of 30 deg (*)

54 Jan 2007 doc.: IEEE /0533r0 Hiroshi Harada (NICT), Rick Roberts (Intel)Slide 54Submission Summary of TSV channel model Matlab code  Explained the following items –Overview, equations and parameters of TSV model –Available channel models by TSV model –Flowchart of the TSV model MATLAB code –Primal functions in the program  Exhibited the following items –Comparison of experimental and simulated results –File format of saved MAT files –Power delay profile

55 Jan 2007 doc.: IEEE /0533r0 Hiroshi Harada (NICT), Rick Roberts (Intel)Slide 55Submission Appendix A: tsv_laplacernd.m  This function generates random values according to the Laplace distribution as function [out]=tsv_laplacernd(a); U1=rand; U2=rand; out=(2.*(U1>=0.5)-1).*(a./sqrt(2)).*log(U2);

56 Jan 2007 doc.: IEEE /0533r0 Hiroshi Harada (NICT), Rick Roberts (Intel)Slide 56Submission Appendix B: tsv_poissrnd.m  This function M-file generates random value from the Poisson distribution function [out] = tsv_poissrnd(lamda) ar=exp(lamda)*rand; if ar<=1 out=0; return end out=1; while 1 ar=ar*rand; if ar<=1 return end out=out+1; end

57 Jan 2007 doc.: IEEE /0533r0 Hiroshi Harada (NICT), Rick Roberts (Intel)Slide 57Submission Appendix C: tg3c_sv_cnvrt_ct.m  The function converts continuous-time channel model h_ct to N-times over-sampled discrete-time samples convert continuous-time channel model h_ct to N-times oversampled discrete-time samples h_ct, t, np, and num_channels are as specified in uwb_sv_model ts is the desired time resolution hN will be produced with time resolution ts / N.  It is up to the user to then apply any filtering and/or complex down-conversion and then decimate by N to finally obtain an impulse response at time resolution ts.

58 Jan 2007 doc.: IEEE /0533r0 Hiroshi Harada (NICT), Rick Roberts (Intel)Slide 58Submission Appendix D: tg3c_tsv_menu_disp.m and tg3c_tsv_results_disp.m  Tg3c_tsv_menu_disp.m, and tg3c_tsv_results_disp setups input arguments, and exhibits some of highlight simulation results, respectively

59 Jan 2007 doc.: IEEE /0533r0 Hiroshi Harada (NICT), Rick Roberts (Intel)Slide 59Submission Main Menu for c TSV Channel Model... Option 1: Create CM Golden Set (Power,TOA, and AOA of Rays before Antenna Gain Convolution) Option 2: Create Discrete CM Impulse Responses using Antenna Model Option 3: Create Discrete CM Impulse Responses using Antenna Model with Simulation Results Displayed Option 4: Exit Program Select menu index: Option To make channel response based on TSV-model If you use “Option 3”, please press “3+ Enter” key. Select menu index: Option 3 ******************* T-S-V Channel Model Parameter Setup ******************* Channel Model Index: ScenarioEnvironmentEngine CM1:LOSResidentialTSV Engine CM2:NLOSResidentialTSV Engine (LOS component exstraction mode) CM3:LOSOfficeTSV Engine CM4:NLOSOfficeTSV Engine CM5:LOSLibrarySV engine CM6:NLOSLibrarySV engine CM7:LOSConferenceSV engine CM8:NLOSConferenceSV engine CM9:LOSDesktopTSV Engine CM10:NLOSCorridorSV engine Select Channel Model index to Generate: CM If you use “CM1”, please press “1 + Enter”.key.

60 Jan 2007 doc.: IEEE /0533r0 Hiroshi Harada (NICT), Rick Roberts (Intel)Slide 60Submission Select Channel Model index to Generate: CM LOS Residential Channels will be Generated with TSV Engine Measured Antenna model used in simulation configulation CM1.1: Tx : 360 deg, Rx : 15 deg CM1.2: Tx : 60 deg, Rx : 15 deg CM1.3: Tx : 30 deg, Rx : 15 deg CM1.4: Tx : 15 deg, Rx : 15 deg NOTICE: Rx Antenna Beam-width can be changed, whereas Tx Antenna Beam-width is fixed, Select CM to Generate: CM1. To make channel response based on TSV-model (cont’) If you use “CM1.3”, please press ”3+ Enter” key. Select CM to Generate: CM Center Carrier Frequency Set Center Carrier Frequency in GHz : If skipped, this variable will be set to be 60 (GHz) -> If you select “skip”, please press “Enter” key.

61 Jan 2007 doc.: IEEE /0533r0 Hiroshi Harada (NICT), Rick Roberts (Intel)Slide 61Submission Antenna Model Antenna Model: Model 1: Reference Antenna Model Model 2: Gaussian-Distributed Antenna Model Set Antenna Model Used in Simulation: Model If skipped, Reference Antenna Model will be used ->1 To make channel response based on TSV-model (cont’) If you use “Model 1”, please press ”1 + Enter” key Rx antenna HPBW Input Rx Beam-width used in Simulation in Deg from 0 to 360 Deg If skipped, this variable is set to 30 (Deg) (Default value) -> If you select “skip”, please press “Enter” key Channel Realization Set Number of Channel Realizations If skipped, Number of Channel Realizations will be set to be 100 -> If you select “skip”, please press “Enter” key.

62 Jan 2007 doc.: IEEE /0533r0 Hiroshi Harada (NICT), Rick Roberts (Intel)Slide 62Submission ***************************** Save and Display **************************** Save Discrete Impulse Responses Save Discrete Impulse Responses to MAT file? YES(1) or NO(0) ->1 To make channel response based on TSV-model (cont’) Please press ”1+Enter” if you save discrete impulse response and some of parameters Display Simulation Results Display Antenna Model used in Simulation? YES(1) or NO(0) ->0 Please press “1 + Enter” key if you want to see power delay profile, Display Power Delay Profile? YES(1) or NO(0) ->0 Press “3 +Enter” key if you display 3D delay power profile Please press ”1 + Enter” key if you display Tx and Rx antenna models used 2D Profile in Each Realization(1) 2D Profile in All Realizations(2) 3D Profile(3) Sample rate Set Sample Rate in GHz : If skipped, this Variable is set to be 1 (GHz) ->1 Please Press “1+ Enter” key if you use a sample rate of 1Gbps

63 Jan 2007 doc.: IEEE /0533r0 Hiroshi Harada (NICT), Rick Roberts (Intel)Slide 63Submission SV Code Support

64 Jan 2007 doc.: IEEE /0533r0 Hiroshi Harada (NICT), Rick Roberts (Intel)Slide 64Submission Channel Model Parameters Blue = Provided Red = Assumed (missing value) Ref

65 Jan 2007 doc.: IEEE /0533r0 Hiroshi Harada (NICT), Rick Roberts (Intel)Slide 65Submission ParamCM1.5CM5CM9.3CM10 n PLo ss  ns -1 1/ N/A ns -1 1/  ns N/A  ns  c dB N/A  r dB   degs  K dB 10 8 N/A  k dB nlos 0000 TSV 0000 Syn NLOS 0000 Note: CM2.5 and CM6 derived from CM1.5 and CM5 by nulling out the LOS component

66 Jan 2007 doc.: IEEE /0533r0 Hiroshi Harada (NICT), Rick Roberts (Intel)Slide 66Submission Target Channel Characteristics CM1.5CM5CM9.3CM10 Λ Cluster Arrival Rate (ns -1 ) λ Ray Arrival Rate (ns -1 ) Γ Cluster Decay Factor (ns) γ Ray decay Factor (ns) σ c sd of cluster σ r sd of ray σ Φ sd of AoA Simulated Model Characteristics Λ Cluster Arrival Rate (ns -1 ) λ Ray Arrival Rate (ns -1 ) Γ Cluster Decay Factor (ns) γ Ray decay Factor (ns) σ c sd of cluster σ r sd of ray σ Φ sd of AoA Good agreement on Cluster Statistics between theory and actual.

67 Jan 2007 doc.: IEEE /0533r0 Hiroshi Harada (NICT), Rick Roberts (Intel)Slide 67Submission Distribution Functions Log Normal Poisson Determining the number of clusters and the number of rays per cluster

68 Jan 2007 doc.: IEEE /0533r0 Hiroshi Harada (NICT), Rick Roberts (Intel)Slide 68Submission Cluster Generation Ray Generation Definition of Variables

69 Jan 2007 doc.: IEEE /0533r0 Hiroshi Harada (NICT), Rick Roberts (Intel)Slide 69Submission Putting it All Together – Composite Cluster/Ray Generation

70 Jan 2007 doc.: IEEE /0533r0 Hiroshi Harada (NICT), Rick Roberts (Intel)Slide 70Submission Cluster Definition

71 Jan 2007 doc.: IEEE /0533r0 Hiroshi Harada (NICT), Rick Roberts (Intel)Slide 71Submission

72 Jan 2007 doc.: IEEE /0533r0 Hiroshi Harada (NICT), Rick Roberts (Intel)Slide 72Submission Ray Definition

73 Jan 2007 doc.: IEEE /0533r0 Hiroshi Harada (NICT), Rick Roberts (Intel)Slide 73Submission

74 Jan 2007 doc.: IEEE /0533r0 Hiroshi Harada (NICT), Rick Roberts (Intel)Slide 74Submission Combined Cluster + Ray Definition

75 Jan 2007 doc.: IEEE /0533r0 Hiroshi Harada (NICT), Rick Roberts (Intel)Slide 75Submission

76 Jan 2007 doc.: IEEE /0533r0 Hiroshi Harada (NICT), Rick Roberts (Intel)Slide 76Submission 3-D Representation

77 Jan 2007 doc.: IEEE /0533r0 Hiroshi Harada (NICT), Rick Roberts (Intel)Slide 77Submission

78 Jan 2007 doc.: IEEE /0533r0 Hiroshi Harada (NICT), Rick Roberts (Intel)Slide 78Submission Discrete Time Sorted Definition

79 Jan 2007 doc.: IEEE /0533r0 Hiroshi Harada (NICT), Rick Roberts (Intel)Slide 79Submission sort

80 Jan 2007 doc.: IEEE /0533r0 Hiroshi Harada (NICT), Rick Roberts (Intel)Slide 80Submission Apply the Spatial Filtering to form IR

81 Jan 2007 doc.: IEEE /0533r0 Hiroshi Harada (NICT), Rick Roberts (Intel)Slide 81Submission

82 Jan 2007 doc.: IEEE /0533r0 Hiroshi Harada (NICT), Rick Roberts (Intel)Slide 82Submission Creating Continuous Time Impulse Response

83 Jan 2007 doc.: IEEE /0533r0 Hiroshi Harada (NICT), Rick Roberts (Intel)Slide 83Submission Convert Continuous Time to Discrete Time

84 Jan 2007 doc.: IEEE /0533r0 Hiroshi Harada (NICT), Rick Roberts (Intel)Slide 84Submission Synthesizing NLOS Clusters from LOS Clusters

85 Jan 2007 doc.: IEEE /0533r0 Hiroshi Harada (NICT), Rick Roberts (Intel)Slide 85Submission Regular LOS Clusters First cluster contains both LOS impulse and multipath energy

86 Jan 2007 doc.: IEEE /0533r0 Hiroshi Harada (NICT), Rick Roberts (Intel)Slide 86Submission Synthesized NLOS Clusters First cluster (LOS) is nulled out

87 Jan 2007 doc.: IEEE /0533r0 Hiroshi Harada (NICT), Rick Roberts (Intel)Slide 87Submission Impulse Response Truncation

88 Jan 2007 doc.: IEEE /0533r0 Hiroshi Harada (NICT), Rick Roberts (Intel)Slide 88Submission % truncate impulse response to the -40 dB point z_max=max(max(abs(ImpDt))); for index_cn=1:NumChannels IM_done=0; for index=length(ImpDt):-1:1 % work backwards thru vector if IM_done==0 if abs(ImpDt(index,index_cn))>z_max/1e2 index_max(index_cn)=index; % search for largest index that gives -40 dB IM_done=1; end ImpDtTrunc=ImpDt(1:max(index_max),:); % truncate by using the largest index Discrete Time Impulse Response Truncation Routine – prevents excessively long impulse responses containing little energy

89 Jan 2007 doc.: IEEE /0533r0 Hiroshi Harada (NICT), Rick Roberts (Intel)Slide 89Submission SV Menu Options Most of the menus are self explanatory

90 Jan 2007 doc.: IEEE /0533r0 Hiroshi Harada (NICT), Rick Roberts (Intel)Slide 90Submission *************************************************************************************************** *** Merged version 1.01 of channel model MATLAB code (TSV Engine and SV engine) Jan *** *** Programmed by Richard D Roberts (SV engine), Hiroshi Harada, Ryuhei Funada, Hirokazu Sawada *** ***, Yozo Shoji and Shuzo Kato (TSV engine) *** *************************************************************************************************** *************** *** History *** *************** *** SV engine *** *** Version Release 1.000, December *** *** TSV engine *** *** Version Release 1.000, December *** ---- Feature Supported CM1,2,3,4, and 9 2. Generated continuous data and resampled data 3. Included reference antenna pattern discussed in Nov Implemented all of the changes discussed in Nov Bug report ---- Jan 9, 2007 rev added to Menu, SV models CM1.5, CM2.5 and CM9.3 Do you want to run TSV (1) or SV (2) model? 2 Main Menu for c SV Channel Model... Option 1: Analyze Statistics of a Previously Generated CM Impulse Response & View Realizations Option 2: Generate CM Impulse Responses by Appling Spatial Filtering & Entering Sample Rate [run this to generate impulse responses] Option 3: Obtain Cluster Statistics Option 4: Graphically View S-V Clusters for a Particular CM Option 5: Generate All New S-V Clusters [run this second to generate all the S-V clusters] Option 6: Load S-V Parameters and Make Directories [run this first to build directories] Option 7: Exit Program Option 8: Revision History Input Menu Option Number [1, 2, 3, 4, 5, 6, 7, 8] Main SV Menu

91 Jan 2007 doc.: IEEE /0533r0 Hiroshi Harada (NICT), Rick Roberts (Intel)Slide 91Submission Main Menu for c SV Channel Model... Option 1: Analyze Statistics of a Previously Generated CM Impulse Response & View Realizations Option 2: Generate CM Impulse Responses by Appling Spatial Filtering & Entering Sample Rate Option 3: Obtain Cluster Statistics Option 4: Graphically View S-V Clusters for a Particular CM Option 5: Generate All New S-V Clusters Option 6: Load S-V Parameters and Make Directories Option 7: Exit Program Option 8: Revision History Input Menu Option Number [1, 2, 3, 4, 5, 6, 7, 8] 5 Caution: proceeding will overwrite previously stored clusters! Do you want to proceed? [1="yes", 2="no"] 1 Do you want to regenerate "Golden Clusters"? [1="yes", 2="no"] 2 [type 1 to generate golden clusters] SV Parameters Loaded --> Running Generate Clusters *** Warning: Be sure to run option 6 first to generate sub-directory structure *** Please Input Number of Channels to Generate (e.g. 100) 100 [enter number of realizations to generate] Option 5

92 Jan 2007 doc.: IEEE /0533r0 Hiroshi Harada (NICT), Rick Roberts (Intel)Slide 92Submission Main Menu for c SV Channel Model... Option 1: Analyze Statistics of a Previously Generated CM Impulse Response & View Realizations Option 2: Generate CM Impulse Responses by Appling Spatial Filtering & Entering Sample Rate Option 3: Obtain Cluster Statistics Option 4: Graphically View S-V Clusters for a Particular CM Option 5: Generate All New S-V Clusters Option 6: Load S-V Parameters and Make Directories Option 7: Exit Program Option 8: Revision History Input Menu Option Number [1, 2, 3, 4, 5, 6, 7, 8] 2 Please Enter Channel Model Number of Interest Please Input SV CM Number:(1.5, 2.5, 5, 6, 9.3, 10) > Running Generate Impulse Response This routine generates a complex baseband impulse response Input Sample Frequency (Gsps): 2.5 Use applicable TSV default antenna beamwidths (1) or select your own beamwidth (2)? 2 Input Antenna Beam Width: [1 to 360 degs]: 90...RX Antenna Beamwidth=90 degrees Do you want "Gaussian Sidelobes" (1) or "Ideal" (2): 1 Input Ant Point Ang: [-180 to 180 degs] - or - enter "181" for automatic pointing per realization: 181 Do you want to track the strongest cluster [1] or strongest ray [2]? 2 Running Auto Antenna Pointing Algorithm Model Characteristics Mean delays: excess (tau_m) = 0.05 ns, RMS (tau_rms) = 0.34 ns # paths: NP_10dB = 1.0, NP_85% = 1.0 Channel energy: mean = -0.0 dB, std deviation = 0.0 dB Channels Spatially Nulled: 0.0, Remaining Channels: Writing ASCII files IR_real.xls and IR_imag.xls to directory CM1.5 *** Strike Any Key to Continue *** Option 2

93 Jan 2007 doc.: IEEE /0533r0 Hiroshi Harada (NICT), Rick Roberts (Intel)Slide 93Submission CM MAT File Definition

94 Jan 2007 doc.: IEEE /0533r0 Hiroshi Harada (NICT), Rick Roberts (Intel)Slide 94Submission Directory Structure

95 Jan 2007 doc.: IEEE /0533r0 Hiroshi Harada (NICT), Rick Roberts (Intel)Slide 95Submission save ClusterInfo ToaCluster AoaCluster AvePowCluster InsPowCluster cluster+ray metrics in cluster ordered columns by channel CM Vector 1xN vector CM Array M*N x N array cluster metrics in cluster columns by channel save FullArray ToaArray AoaArray InsPowArray save FullValues Toa Aoa InsPow cluster+ray metrics in a cluster ordered vector by channel CM Vector M*N x 1 CM Array MxN Array ray metrics in cluster columns by channel save RayInfo ToaRay AoaRay AvePowRay InsPowRay CM Array M x N array cluster+ray metrics in cluster columns by channel save FullVectors ToaVector InsPowVector AoaWrappedVector ray metrics in cluster ordered columns by channel save RayArray ToaRayArray AoaRayArray AvePowRayArray InsPowRayArray CM Array M*N x N array time sorted cluster+ray metrics in a cluster ordered vector by channel CM Vector M*N x 1 save SortedVectors SortedAmp SortedTime SortedAng N = number of clusters M = number of rays per cluster L = impulse response length save ImpResp ImpDtTrunc TimeDt t0 NumChannels NothingLeft CM Vector L x 1 vector discrete time response column vector by channel save ImpInfoStuff t0 NumRays NumRaysPerCluster NumClusters NumChannels miscellaneous scalars used throughout the program save IR_real.xls IR_real -ASCII -TABS save IR_imag.xls IR_imag -ASCII -TABS CM Vector L x 1 vector continuous time response column vector by channel CM Vector L x 1 vector continuous time response column vector by channel

96 Jan 2007 doc.: IEEE /0533r0 Hiroshi Harada (NICT), Rick Roberts (Intel)Slide 96Submission SV Flow Chart

97 Jan 2007 doc.: IEEE /0533r0 Hiroshi Harada (NICT), Rick Roberts (Intel)Slide 97Submission start TSV or SV ? TSVSV Select Option: 1. Analyze IR 2. Generte IR 3. Statistics 4. View Clusters 5. Generate Clusters 6. Load Parameters 7. Exit Program 8. Revision History Call: AnalyzeImpulse Opt. 1 Call: GenImpulse Opt. 2 Call: ClusterStats Opt. 3 Call: ViewClusters Opt. 4 Call: GenClusters Opt. 5 Call: LoadParams Opt. 6 quit Opt. 7 print out history Opt. 8 Main Menu

98 Jan 2007 doc.: IEEE /0533r0 Hiroshi Harada (NICT), Rick Roberts (Intel)Slide 98Submission AnalyzeImpulse start Load selected CM clusters Determine channel energy Calculate excess delay RMS delay Number of significant paths Calculate average PDP Plot out results return

99 Jan 2007 doc.: IEEE /0533r0 Hiroshi Harada (NICT), Rick Roberts (Intel)Slide 99Submission GenImpulse start Load selected CM clusters Input sample rate Input beam width Time sort overlapped clusters Normalize energy Truncate impulse response to -40 dBr point Save complex impulse response to a file return Auto-point ? yesno Max ray or max cluster ? raycluster Input pointing AoA Find AoA of max ray Find AoA of max cluster Reject energy not inside the beam Convert discrete time to continuous time

100 Jan 2007 doc.: IEEE /0533r0 Hiroshi Harada (NICT), Rick Roberts (Intel)Slide 100Submission ClusterStats start Load selected CM clusters Display database desired stats Calculate cluster arrival rate Calculate ray arrival rate Calculate cluster decay factor Calculate ray decay factor Calculate cluster amplitude statistics Calculate ray amplitude statistics Calculate strongest cluster AoA return Calculate strongest ray AoA

101 Jan 2007 doc.: IEEE /0533r0 Hiroshi Harada (NICT), Rick Roberts (Intel)Slide 101Submission ViewClusters start Load selected CM clusters Plot average power per cluster Plot instantaneous power per cluster Plot cluster AoA Plot cluster ToA Plot 3-D cluster return Plot average power per ray Plot instantaneous power per ray Plot ray AoA Plot ray ToA Plot composite average power Plot composite instantaneous power Plot composite AoA Plot composite ToA

102 Jan 2007 doc.: IEEE /0533r0 Hiroshi Harada (NICT), Rick Roberts (Intel)Slide 102Submission GenClusters Start GenClusters Input number of realizations Fetch stored parameters return Determine number of clusters to generate Generate clusters Generate rays within each cluster if synthesizing NLOS then null out first cluster Make composite clusters by combining cluster and ray info Store off cluster, ray and composite matrices


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