LAMPIRAN A. Code Program. A1. Source Code Program. A2. Fungsi Tuncnormrnd. Universitas Sumatera Utara

Transkripsi

1 LAMPIRAN A Code Program A1. Source Code Program A2. Fungsi Tuncnormrnd

2 Lampiran A / Code Program 1/10 A.1 Source Code Program tic; clear all; clc; close all; s = 1;% Jumlah simulasi N = 2000; % jlh titik sampel %koordinat BTS D = 1000*sqrt(3); % jarak antara BTS berdekatan adalah.2000 meter X_BTS = [2000-D*sin(60*pi/180) ]; Y_BTS = [1+D/2 1 1+D]; ds = 1; % meter % Jarak Interval Sample 1 meter theta = 20; % sudut arah pergerakan MS dari BTS1 % Koordinat awal MS xk =[500*ones(s,1) zeros(s,n-1)];%sb-x yk = [500*ones(s,1) zeros(s,n-1)];%sb-y %Jarak awal MS terhadap BTS (2000,0) d1k=[sqrt((x_bts(1)-500)^2+(y_bts(1)-500)^2)*ones(s,1) zeros(s,n- 1)]; d2k=[sqrt((x_bts(2)-500)^2+(y_bts(2)-500)^2)*ones(s,1) zeros(s,n- 1)]; d3k=[sqrt((x_bts(3)-500)^2+(y_bts(3)-500)^2)*ones(s,1) zeros(s,n- 1)]; for j = 1:s for k = 2:N xk(j,k) = xk(j,k-1)+ds*cos(theta*pi/180); yk(j,k) = yk(j,k-1)+ds*sin(theta*pi/180); d1k(j,k)=sqrt((x_bts(1)-xk(j,k)).^2+(y_bts(1)-yk(j,k)).^2); d2k(j,k)=sqrt((x_bts(2)-xk(j,k)).^2+(y_bts(2)-yk(j,k)).^2); d3k(j,k)=sqrt((x_bts(3)-xk(j,k)).^2+(y_bts(3)-yk(j,k)).^2); %% menentukan model shadowing--dist. lognormal mu=0;%mean tho=[3:12];%variansi v= 20;%kecepatan MS (m/s) ts= 0.5;%waktu sampling (s) di=30;%korelasi jarak ai=exp(-v*ts/di);%koefisien korelasi K1=105; %dbm;% konstanta pathloss K2=30; %dbm;% konstanta eksponen pathloss %truncated normal random mu1=0;% mean tho1=1;% variansi xlo=-0.5;% batas bawah xhi=0.5;% batas atas % fungsi truncated normal random [F1,F2,F3]=truncnormrnd(s,N,mu1,tho1,xlo,xhi); % auto regresive -1

3 Lampiran A / Code Program 2/10 ZBTS1=[ai*ones(s,1) zeros(s,n-1)]; ZBTS2=[ai*ones(s,1) zeros(s,n-1)]; ZBTS3=[ai*ones(s,1) zeros(s,n-1)]; % kuat sinyal terima pada posisi awal S1(:,1)= K1-K2.*log10(d1k(:,1))+ ZBTS1(:,1); S2(:,1)= K1-K2.*log10(d2k(:,1))+ ZBTS2(:,1); S3(:,1)= K1-K2.*log10(d3k(:,1))+ ZBTS3(:,1); % ruang matriks untuk kuat sinyal S1=[S1(:,1).*ones(s,1) zeros(s,n-1)]; S2=[S2(:,1).*ones(s,1) zeros(s,n-1)]; S3=[S3(:,1).*ones(s,1) zeros(s,n-1)]; C=[0.0045,0.025,0.1,0.65]; for g=1:length(c) for var_tho=1:length(tho) for cc=1:s for dd=2:n ZBTS1(cc,dd)=ai*ZBTS1(cc,dd-1)+tho(var_tho)*sqrt(1- ai^2)*f1(cc,dd); ZBTS2(cc,dd)=ai*ZBTS2(cc,dd-1)+tho(var_tho)*sqrt(1- ai^2)*f2(cc,dd); ZBTS3(cc,dd)=ai*ZBTS3(cc,dd-1)+tho(var_tho)*sqrt(1- ai^2)*f3(cc,dd); for ddd=2:n % kuat sinyal terima S1(cc,ddd)= K1-K2.*log10(d1k(cc,ddd))+ ZBTS1(cc,ddd); S2(cc,ddd)= K1-K2.*log10(d2k(cc,ddd))+ ZBTS2(cc,ddd); S3(cc,ddd)= K1-K2.*log10(d3k(cc,ddd))+ ZBTS3(cc,ddd); S_123= [ S1; S2; S3]; %% Merata-ratakan kuat sinyal ds = 1;%jarak setiap sampling (m) dav = 10;% panjang rata-rata window S1_rata=[S1(:,1) zeros(s,n-1)]; S2_rata=[S2(:,1) zeros(s,n-1)]; S3_rata=[S3(:,1) zeros(s,n-1)]; b=exp(-ds/dav); for e=1:s for f=2:n %% merata-ratakan sinyal dengan metode eksponensial untuk memperhalus %% komponen sinyal shadowing yang berfluktuasi %%================================================================ %Sinyal 1 S1_rata(e,f)=exp(-(ds/dav)).*S1_rata(e,f-1)+(1-exp(- (ds/dav)))...

4 Lampiran A / Code Program 3/10.*S1(e,f); %Sinyal 2 S2_rata(e,f)=exp(-(ds/dav)).*S2_rata(e,f-1)+(1-exp(- (ds/dav)))....*s2(e,f); %Sinyal 3 S3_rata(e,f)=exp(-(ds/dav)).*S3_rata(e,f-1)+(1-exp(- (ds/dav)))....*s3(e,f); %%================================================================ S123_rata = [S1_rata;S2_rata;S3_rata]; S11_rata_eks(e,f)=(K1-K2*log10(d1k(e,f)))+ai.*(S1(e,f-1)-(K1- K2*log10(d1k(e,f-1)))); S22_rata_eks(e,f)=(K1-K2*log10(d2k(e,f)))+ai.*(S2(e,f-1)-(K1- K2*log10(d2k(e,f-1)))); S33_rata_eks(e,f)=(K1-K2*log10(d3k(e,f)))+ai.*(S3(e,f-1)-(K1- K2*log10(d3k(e,f-1)))); %================================================================= %ekspektasi==> mean dari Si & Si_rata S1_rata_eks(e,f)=b.*S1_rata(e,f-1)+(1-b).*(ai.*S1(e,f-1)+... (1-ai)*K1-K2*log10(d1k(e,f)./(d1k(e,f-1).^ai))); S2_rata_eks(e,f)=b.*S2_rata(e,f-1)+(1-b).*(ai.*S2(e,f-1)+... (1-ai)*K1-K2*log10(d2k(e,f)./(d2k(e,f-1).^ai))); S3_rata_eks(e,f)=b.*S3_rata(e,f-1)+(1-b).*(ai.*S3(e,f-1)+... (1-ai)*K1-K2*log10(d3k(e,f)./(d3k(e,f-1).^ai))); %================================================================= %================================================================= %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% %%%% Metode Suboptimal SDH %%%%%%%%% %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% Smin = 0; %dbm; varians_kuadrat(var_tho)=tho(var_tho)*sqrt((1-(ai^2)).*(1- (b.^2)));% variansi sinyal rata-rata for v=1:s for u=1:n-1 Z1(v,u)=qfunc((S1_rata_eks(v,u+1)- Smin)./(varians_kuadrat(var_tho))); Z2(v,u)=qfunc((S2_rata_eks(v,u+1)- Smin)./(varians_kuadrat(var_tho))); Z3(v,u)=qfunc((S3_rata_eks(v,u+1)- Smin)./(varians_kuadrat(var_tho))); % nilai cost (c)

5 Lampiran A / Code Program 4/10 % C=[1,0.95,0.85,0.75,0.65,0.55,0.45,0.35,0.25,0.13,0.1,0.06,0.04,0. 025,0.01,0.007,0.0045]; BTS= [1;2;3]; Z= [Z1(:,1) zeros(s,n-1)]; S_SDH=[S1(:,1) zeros(s,n-1)]; S_rata_SDH=[S1_rata(:,1) zeros(s,n-1)]; BTS_kontrol_SDH=[BTS(1)*ones(s,1) zeros(s,n-1)]; handoff = 1; % terjadi handoff tidak_handoff = 0; % tidak terjadi handoff Uk_SDH=zeros(s,N); delay_sdh=[]; S_mean_SDH= [S1_rata_eks(:,1) zeros(s,n-1)]; for h=1:s for i=2:n %(titik sampel) if i<=3 S_SDH(h,i)=S1(h,i); S_rata_SDH(h,i)=S1_rata(h,i); BTS_kontrol_SDH(h,i)=BTS(1); Uk_SDH(h,i)=[tidak_handoff]; delay_sdh(h,i)=d1k(h,i); S_mean_SDH(h,i)= S11_rata_eks(h,i); %% keadaan sebelumnya BTS1 yang melayani MS if BTS_kontrol_SDH(h,i-1)==BTS(1) if S_rata_SDH(h,(i-3:i-1))<Smin & S1_rata(h,i)<Smin continue; if Z1(h,i-1)>Z2(h,i-1)+C(g) && Z2(h,i- 1)+C(g)<Z3(h,i-1)+C(g) S_SDH(h,i)=S2(h,i); S_rata_SDH(h,i)=S2_rata(h,i); BTS_kontrol_SDH(h,i)=BTS(2); Uk_SDH(h,i)=[handoff]; delay_sdh(h,i)=d2k(h,i); S_mean_SDH(h,i)= S22_rata_eks(h,i); if Z1(h,i-1)>Z3(h,i-1)+C(g) && Z2(h,i- 1)+C(g)>Z3(h,i-1)+C(g) S_SDH(h,i)=S3(h,i); S_rata_SDH(h,i)=S3_rata(h,i); BTS_kontrol_SDH(h,i)=BTS(3); Uk_SDH(h,i)=[handoff]; delay_sdh(h,i)=d3k(h,i); S_mean_SDH(h,i)= S33_rata_eks(h,i); S_SDH(h,i)=S1(h,i); S_rata_SDH(h,i)=S1_rata(h,i); BTS_kontrol_SDH(h,i)=BTS(1); Uk_SDH(h,i)=[tidak_handoff];

6 Lampiran A / Code Program 5/10 delay_sdh(h,i)=d1k(h,i); S_mean_SDH(h,i)= S11_rata_eks(h,i); %% keadaan sebelumnya BTS2 yang melayani MS if BTS_kontrol_SDH(h,i-1)==BTS(2) if S_rata_SDH(h,(i-3:i-1))<Smin & S2_rata(h,i)<Smin continue; if Z2(h,i-1)>Z1(h,i-1)+C(g) && Z1(h,i- 1)+C(g)<Z3(h,i-1)+C(g) S_SDH(h,i)=S1(h,i); S_rata_SDH(h,i)=S1_rata(h,i); BTS_kontrol_SDH(h,i)=BTS(1); Uk_SDH(h,i)=[handoff]; delay_sdh(h,i)=d1k(h,i); S_mean_SDH(h,i)= S11_rata_eks(h,i); if Z2(h,i-1)>Z3(h,i-1)+C(g) && Z1(h,i- 1)+C(g)>Z3(h,i-1)+C(g) S_SDH(h,i)=S3(h,i); S_rata_SDH(h,i)=S3_rata(h,i); BTS_kontrol_SDH(h,i)=BTS(3); Uk_SDH(h,i)=[handoff]; delay_sdh(h,i)=d3k(h,i); S_mean_SDH(h,i)= S33_rata_eks(h,i); S_SDH(h,i)=S2(h,i); S_rata_SDH(h,i)=S2_rata(h,i); BTS_kontrol_SDH(h,i)=BTS(2); Uk_SDH(h,i)=[tidak_handoff]; delay_sdh(h,i)=d2k(h,i); S_mean_SDH(h,i)= S22_rata_eks(h,i); %% keadaan sebelumnya BTS3 yang melayani MS if BTS_kontrol_SDH(h,i-1)==BTS(3) if S_rata_SDH(h,(i-3:i-1))<Smin & S3_rata(h,i)<Smin continue; if Z3(h,i-1)>Z1(h,i-1)+C(g) && Z1(h,i- 1)+C(g)<Z2(h,i-1)+C(g) S_SDH(h,i)=S1(h,i); S_rata_SDH(h,i)=S1_rata(h,i); BTS_kontrol_SDH(h,i)=BTS(1); Uk_SDH(h,i)=[handoff]; delay_sdh(h,i)=d1k(h,i); S_mean_SDH(h,i)= S11_rata_eks(h,i); if Z3(h,i-1)>Z2(h,i-1)+C(g) && Z1(h,i- 1)+C(g)>Z2(h,i-1)+C(g) S_SDH(h,i)=S2(h,i); S_rata_SDH(h,i)=S2_rata(h,i); BTS_kontrol_SDH(h,i)=BTS(2); Uk_SDH(h,i)=[handoff];

7 Lampiran A / Code Program 6/10 delay_sdh(h,i)=d2k(h,i); S_mean_SDH(h,i)= S22_rata_eks(h,i); S_SDH(h,i)=S3(h,i); S_rata_SDH(h,i)=S3_rata(h,i); BTS_kontrol_SDH(h,i)=BTS(3); Uk_SDH(h,i)=[tidak_handoff]; delay_sdh(h,i)=d3k(h,i); S_mean_SDH(h,i)= S33_rata_eks(h,i); %% memilih kuat sinyal BTS terbaik ketika sebelumnya drop %% terjadi if (S1_rata(h,i) > Smin) & (S1_rata(h,i) > S2_rata(h,i)) & (S1_rata(h,i) > S3_rata(h,i)) S_SDH(h,i)=S1(h,i); S_rata_SDH(h,i)=S1_rata(h,i); BTS_kontrol_SDH(h,i)=BTS(1); Uk_SDH(h,i)=[tidak_handoff]; delay_sdh(h,i)=d1k(h,i); S_mean_SDH(h,i)= S11_rata_eks(h,i); if (S2_rata(h,i) > Smin) & (S1_rata(h,i) < S2_rata(h,i)) & (S2_rata(h,i) > S3_rata(h,i)) S_SDH(h,i)=S2(h,i); S_rata_SDH(h,i)=S2_rata(h,i); BTS_kontrol_SDH(h,i)=BTS(2); Uk_SDH(h,i)=[tidak_handoff]; delay_sdh(h,i)=d2k(h,i); S_mean_SDH(h,i)= S22_rata_eks(h,i); if (S3_rata(h,i) > Smin) & (S1_rata(h,i) < S3_rata(h,i)) & (S2_rata(h,i) < S3_rata(h,i)) S_SDH(h,i)=S3(h,i); S_rata_SDH(h,i)=S3_rata(h,i); BTS_kontrol_SDH(h,i)=BTS(3); Uk_SDH(h,i)=[tidak_handoff]; delay_sdh(h,i)=d3k(h,i); S_mean_SDH(h,i)= S33_rata_eks(h,i); continue; std1(var_tho)=tho(var_tho).*sqrt((1-(ai^2))); delay_sdho=(delay_sdh>(d*sqrt(3)/2)); Prob_Sdrop_SDH=qfunc((S_mean_SDH-Smin)./std1(var_tho)); %=================================================================

8 Lampiran A / Code Program 7/10 Uk_SDH_rata(var_tho,:)=1/s*sum(sum(Uk_SDH')); delay_sdh_rata(var_tho,:)=1/s*sum(sum(delay_sdho')); Prob_Sdrop_SDH_rata(var_tho,:)= 1/s*sum(mean(Prob_Sdrop_SDH')); Uk_SDH_rata_tho(:,g)=[Uk_SDH_rata]; delay_sdh_rata_tho(:,g)=[delay_sdh_rata]; Prob_Sdrop_SDH_rata_tho(:,g)=[Prob_Sdrop_SDH_rata]; %================================================================= %================================================================= %Posisi MS terhadap BTS figure(1) % posisi BTS t = linspace(0, 2*pi,7); a1 = X_BTS(1)+ (1000)*cos(t);a2 = X_BTS(2)+ (1000)*cos(t);a3 = X_BTS(3)+ (1000)*cos(t); b1 = Y_BTS(1)+ (1000)*sin(t);b2 = Y_BTS(2)+ (1000)*sin(t);b3 = Y_BTS(3)+ (1000)*sin(t); plot(a1,b1,'-b',a2,b2,'-r',a3,b3,'-g') hold on; plot(x_bts(1),y_bts(1),'bp',x_bts(2),y_bts(2),'rh',x_bts(3),y_bts( 3),'g*'); hold on; plot(xk,yk) grid on; %Bentuk level sinyal MS yang diproses tanpa metode rata-rata eksponensial figure(2) % posisi BTS plot(s1, 'b'); hold on; plot(s2(1,:), 'r'); hold on; plot(s3(1,:), 'g'); xlabel('sample ke-'); ylabel('level sinyal (db)'); leg('sinyal1','sinyal2','sinyal3'); grid on; %Bentuk level sinyal dari MS yang diproses dengan metode eksponensial figure(3) % posisi BTS plot(s1_rata(1,:), 'b'); hold on; plot(s2_rata(1,:), 'r');

9 Lampiran A / Code Program 8/10 hold on; plot(s3_rata(1,:), 'g'); xlabel('sample ke-'); ylabel('level sinyal (db)'); leg('sinyal rata-rata1','sinyal rata-rata2','sinyal ratarata3'); grid on; %pengaruh standar deviasi shadow fading terhadap jumlah sinyal degradasi figure(4) plot(tho,[prob_sdrop_sdh_rata_tho]); xlabel('tho (db)'); ylabel('sinyal Degradasi (db)'); leg('c = ','c = 0.025','c = 0.1','c = 0.65'); grid on; %variansi standar deviasi shadow fading dengan jumlah handoff figure(5) plot(tho,[uk_sdh_rata_tho]) xlabel('tho (db)'); ylabel('jumlah Handoff'); leg('c = ','c = 0.025','c = 0.1','c = 0.65'); grid on; %pengaruh standar deviasi shadow fading dengan delay figure(6) plot(tho,[delay_sdh_rata_tho]) xlabel('tho (db)'); ylabel('delay Rata-rata (m)'); leg('c = ','c = 0.025','c = 0.1','c = 0.65'); grid on; toc;

10 Lampiran A / Code Program 9/10 A.2 Fungsi Truncnormrnd function [F1,F2,F3]=truncnormrnd(s,N,mu1,tho1,xlo,xhi) % truncnormrnd: truncated normal deviate generator % usage:z=truncnormrnd(n,mu1,tho1,xlo,xhi) % % (assumes the statistics toolbox, its easy % to do witho1ut that toolbox tho1ugh) % % arguments: (input) % N - size of the resulting array of deviates % (note, if N is a scalar, then the result will be NxN.) % mu1 - scalar - Mean of underlying normal distribution % tho1 - scalar - Standard deviation of underlying normal distribution % xlo - scalar - Low truncation point, if any % xhi - scalar - High truncation point, if any % % arguments: (output) % z - array of truncated normal deviates, size(z)==n % defaults if (nargin<2) isempty(mu1) mu1=0; if (nargin<3) isempty(tho1) tho1=0; if (nargin<4) isempty(xlo) xlo=-inf; plo=0; plo=normcdf((xlo-mu1)/tho1); if (nargin<5) isempty(xhi) xhi=inf; phi=1; phi=normcdf((xhi-mu1)/tho1); % test if trunation points are reversed if xlo>xhi error 'mu1st have xlo <= xhi if both provided' % generate uniform [0,1] random deviates % r=rand(n); r1=rand(s,n); r2=rand(s,n); r3=rand(s,n); % scale to [plo,phi] % r=plo+(phi-plo)*r; r1=plo+(phi-plo)*r1; r2=plo+(phi-plo)*r2; r3=plo+(phi-plo)*r3;

11 Lampiran A / Code Program 10/10 % Invert through standard normal % F=norminv(r); F1=norminv(r1); F2=norminv(r2); F3=norminv(r3); % apply shift and scale % F=mu1+F*tho1; F1=mu1+F1*tho1; F2=mu1+F2*tho1; F3=mu1+F3*tho1;

12 LAMPIRAN B DATA HASIL SIMULASI B.1 Tabel variasi standar deviasi shadow fading dengan cost(c) terhadap parameter jumlah sinyal degradasi. B.2 Tabel variasi standar deviasi shadow fading dengan cost(c) terhadap parameter jumlah handoff. B.3 Tabel variasi standar deviasi shadow fading dengan cost(c) terhadap parameter delay.

13 Lampiran B / Data Hasil Simulasi 1/3 B1. Tabel variasi standar deviasi shadow fading dengan cost(c) terhadap parameter jumlah sinyal degradasi Lampiran B / Data Hasil Simulasi 2/3 B2. Tabel variasi standar deviasi shadow fading dengan cost(c) terhadap parameter jumlah handoff

14 Lampiran B / Data Hasil Simulasi 3/3 B3. Tabel variasi standar deviasi shadow fading dengan cost(c) terhadap parameter delay

15 LAMPIRAN C Flow Chart C.1 Flow Chart Evaluasi Metode Handoff C.2 Flow Chart Proses Handoff

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