Model Lintasan dan Posisi MS terhadap BTS
A.1 Model Lintasan Acak
Lampiran A
A.1 Model Lintasan Acak
Lintasan acak dimodelkan dalam sistem koordinat kartesian, ditunjukkan
pada Gambar A.1.
Gambar A.1
Model Lintasan Acak
,, ,
, ,
, ,
,
, ,
BTS 3
( , )
( , )
)
( , )
BTS 2
BTS 1
y
x
,
,
∆
∆
y
Pada Gambar A.1, merupakan lintasan MS setiap jarak diskrit, dengan
arah acak yang dipetakan dalam sistem kartesian. Asumsi bahwa, r = 1 (lintasan
berupa garis lurus diamati setiap 1 meter), sudut
adalah arah pergerakan
mobile yang acak pada sampel ke- , dimana
= 1,2, . . . ,
.
Persamaan matematis Gambar A.1 sebagai berikut:
∆
=
cos
(1)
∆
=
sin
(2)
∆
=
−
(3)
∆
=
−
(4)
Dari Persamaan (1) dengan (3) dan (2) dengan (4), diperoleh;
−
=
cos
(5)
=
cos
+
(6)
⋮
=
cos
+
(7)
dan
−
=
sin
(8)
=
sin
+
(9)
⋮
A.2 Menentukan Jarak MS terhadap BTS
Jarak
Mobile Seluler
terhadap
Base Tranceiver Station
dapat ditentukan
berdasarkan rumus jarak antara dua titik
(
,
)
dan
(
,
)
yaitu:
=
(
−
) + (
−
)
(11)
Berdasarkan
Persamaan
(7),
apabila
diasumsikan
bahwa
posisi
(
,
)
,
(
,
)
dan
(
,
)
adalah tetap
terhadap posisi
Mobile Seluler
yang berubah-ubah secara acak yaitu,
(
,
)
dimana,
= 1,2. . . ,
. Maka, jarak
Mobile Seluler
setiap sampel-
terhadap
adalah memenuhi Persamaan (12).
Code Program
B.1 Pseudo Code Program Metode
Handoff
3 BTS
B.2 Source Code Program
B.1 Pseudo Code Program Metode
Handoff
3 BTS
%=================================================% %++++++++pseudocode metode handoff 3 BTS++++++++++% %+++++++++++++Matlab Pogramming+++++++++++++++++++% %==============Leonardo Siregar===================% %===========Departemen Teknik Elektro=============% %==========Universitas Sumatera Utara=============% %=================================================%
for h=1:simulasi
for i=1:n %(titik sampel)
%% keadaan sebelumnya BTS1 yang melayani MS
if BTS_kontrol(h,i-1)==BTS(1)
if Sinyal(h,[i-12:i-1,i])<Sdrop
% dua belas titik sampel berturut-turut dibawah sinyal % drop, maka terjadi drop call
continue;
else
if %syarat handoff BTS1-->BTS2
BTS2 % update data
elseif %syarat handoff BTS1-->BTS3
BTS3 % update data else
BTS1 % update data end
end
%% keadaan sebelumnya BTS2 yang melayani MS elseif BTS_kontrol(h,i-1)==BTS(2)
if Sinyal(h,[i-12:i-1,i])<Sdrop
% dua belas titik sampel berturut-turut dibawah sinyal % drop, maka terjadi drop call
continue;
else
if %syarat handoff BTS1-->BTS2
BTS1 % update data
elseif %syarat handoff BTS1-->BTS3
BTS3 % update data else
BTS2 % update data end
end
%% keadaan sebelumnya BTS3 yang melayani MS elseif BTS_kontrol(h,i-1)==BTS(3)
if Sinyal(h,[i-12:i-1,i])<Sdrop
% dua belas titik sampel berturut-turut dibawah sinyal % drop, maka terjadi drop call
continue else
if %syarat handoff BTS1-->BTS2
BTS1 % update data
elseif %syarat handoff BTS1-->BTS3
BTS2 % update data else
BTS3 % update data end
%% memilih kuat sinyal BTS terbaik ketika sebelumnya drop %% terjadi
if kuat sinyal BTS1 terbaik
BTS1 % update data
elseif kuat sinyal BTS2 terbaik BTS2 % update data
elseif kuat sinyal BTS3 terbaik BTS3 % update data
else continue; end
B.2 Source Code Program
s=500;% simulasi/ jumlah lintasan
N=400;%jumlah total titik sampel per lintasan
%%fungsi transformasi bilangan acak menjadi arah(sudut)acak
[teta_random]=tetarandom(s,N);
%% menentukan posisi BTS dalam koordinat kartesian
D=100*sqrt(3); % jarak antar BTS (m)
BTS_x=[250-D*sin(60*pi/180) ,250 ,250];%sb-x
BTS_y=[75+D/2 ,75 ,75+D];%sb-y
%% posisi koordinat awal MS berkoordinat(200,0)
xi=[200*ones(s,1) zeros(s,N-1)];%sb-x
yi= [0*ones(s,1) zeros(s,N-1)];%sb-y
%% menentukan lintasan acak MS
%jarak sampling antara 2 titik berdekatan
sampling=1;% ds=1 meter
% jarak awal MS terhadap BTS (200,0)
d1i=[sqrt((BTS_x(1)-200)^2+(BTS_y(1)-0)^2)*ones(s,1) zeros(s,N-1)];
d2i=[sqrt((BTS_x(2)-200)^2+(BTS_y(2)-0)^2)*ones(s,1) zeros(s,N-1)];
d3i=[sqrt((BTS_x(3)-200)^2+(BTS_y(3)-0)^2)*ones(s,1) zeros(s,N-1)];
for c=1:s
for d=2:N
xi(c,d)= xi(c,d-1)+sampling*cos(teta_random(c,d)); yi(c,d)= yi(c,d-1)+sampling*sin(teta_random(c,d));
d1i(c,d)=sqrt((BTS_x(1)-xi(c,d))^2+(BTS_y(1)-yi(c,d))^2); d2i(c,d)=sqrt((BTS_x(2)-xi(c,d))^2+(BTS_y(2)-yi(c,d))^2); d3i(c,d)=sqrt((BTS_x(3)-xi(c,d))^2+(BTS_y(3)-yi(c,d))^2);
end end
%% menentukan model shadowing--dist. lognormal
mu=0;%mean
tho=5;%variansi
v=2;%kecepatan MS (m/s)
ts=0.5;%waktu sampling (s)
di=20;%korelasi jarak
ai=exp(-v*ts/di);%koefisien korelasi
K1=85;% konstanta pathloss
K2=35;% 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 AR-1
Fzeita1=[ai*ones(s,1) zeros(s,N-1)]; Fzeita2=[ai*ones(s,1) zeros(s,N-1)]; Fzeita3=[ai*ones(s,1) zeros(s,N-1)];
S1(:,1)= K1-K2.*log10(d1i(:,1))+ Fzeita1(:,1); S2(:,1)= K1-K2.*log10(d2i(:,1))+ Fzeita2(:,1); S3(:,1)= K1-K2.*log10(d3i(:,1))+ Fzeita3(:,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)];
for cc=1:s
for dd=2:N
Fzeita1(cc,dd)=ai*Fzeita1(cc,dd-1)+tho*sqrt(1-for ddd=2:N
% kuat sinyal terima
S1(cc,ddd)= K1-K2.*log10(d1i(cc,ddd))+ Fzeita1(cc,ddd); S2(cc,ddd)= K1-K2.*log10(d2i(cc,ddd))+ Fzeita2(cc,ddd); S3(cc,ddd)= K1-K2.*log10(d3i(cc,ddd))+ Fzeita3(cc,ddd);
end
S_123= [ S1; S2; S3];
end
%% Merata-ratakan kuat sinyal
ds=1;%jarak setiap sampling (m)
dav=[0 10 20 30];% variasi d_rata-rata
S1_rata=[S1(:,1) zeros(s,N-1)]; S2_rata=[S2(:,1) zeros(s,N-1)]; S3_rata=[S3(:,1) zeros(s,N-1)];
for rata=1:length(dav)
b(rata)=exp(-ds/dav(rata));
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(rata))).*S1_rata(e,f-1)+(1-exp(-(ds/dav(rata))))...
.*S1(e,f);
%Sinyal 2
S2_rata(e,f)=exp(-(ds/dav(rata))).*S2_rata(e,f-1)+(1-exp(-(ds/dav(rata))))...
.*S2(e,f);
%Sinyal 3
S3_rata(e,f)=exp(-(ds/dav(rata))).*S3_rata(e,f-1)+(1-exp(-(ds/dav(rata))))...
.*S3(e,f);
%%================================================================
S123_rata = [S1_rata;S2_rata;S3_rata];
S11_rata_eks(e,f)=(K1-K2*log10(d1i(e,f)))+ai.*(S1(e,f-1)-(K1-%ekspektasi==> mean dari Si & Si_rata
S1_rata_eks(e,f)=b(rata).*S1_rata(e,f-1)+(1-b(rata)).*(ai.*S1(e,f-1)+...
(1-ai)*K1-K2*log10(d1i(e,f)./(d1i(e,f-1).^ai)));
S2_rata_eks(e,f)=b(rata).*S2_rata(e,f-1)+(1-b(rata)).*(ai.*S2(e,f-1)+...
(1-ai)*K1-K2*log10(d2i(e,f)./(d2i(e,f-1).^ai)));
S3_rata_eks(e,f)=b(rata).*S3_rata(e,f-1)+(1-b(rata)).*(ai.*S3(e,f-1)+...
(1-ai)*K1-K2*log10(d3i(e,f)./(d3i(e,f-1).^ai)));
%================================================================= end
end
Sdrop=14.5; % batas level sinyal mengalami drop, jika sinyal <
Sdrop (dB)
Smin=15; % level sinyal minimum (dB)
Smax=2*Smin; % batas level sinyal maksimum, jika sinyal > Smax
(dB)
P=0.1;
% R=D/sqrt(3);% radius sel
std1=tho*sqrt((1-(ai^2)));
std=tho*sqrt((1-(ai^2)).*(1-(b(rata).^2)));% variansi Si & Si_rata
handoff=1;% handoff terjadi
tidak_handoff=0;% handoff tidak terjadi
%================================== %===metode treshold & histeresis=== %==================================
t=1:20;% variasi treshold (dB)
h=1:10;% variasi histeresis (dB)
BTS= [1;2;3];% BTS1= 1; BTS2= 2; BTS3= 3;
S_T_H= [S2(:,1) zeros(s,N-1)];
S_rata_T_H= [S2_rata(:,1) zeros(s,N-1)];
BTS_kontrol_T_H=[BTS(2)*ones(s,1) zeros(s,N-1)]; Uk_T_H=zeros(s,N);
delay_T_H=[];
S_mean_T_H= [S2_rata_eks(:,1) zeros(s,N-1)];
for p=1:length(h)
for m=1:length(t)
for n=1:s
for o=2:N
%% inisial BTS_2 yg menangani MS if o<=12
S_T_H(n,o)=S2(n,o);
S_rata_T_H(n,o)=S2_rata(n,o); BTS_kontrol_T_H(n,o)=BTS(2); Uk_T_H(n,o)=[tidak_handoff]; delay_T_H(n,o)=d2i(n,o);
else
%% jika BTS yang menangani MS sebelumnya adalah BTS_1
if BTS_kontrol_T_H(n,o-1)==BTS(1)
if S_rata_T_H(n,(o-12:o-1))<Sdrop & S1_rata(n,o)<Sdrop
continue;
else
if S1_rata(n,o) < t(m) && S1_rata(n,o)+h(p) < S2_rata(n,o) && S2_rata(n,o) > S3_rata(n,o)
S_T_H(n,o)=S2(n,o);
S_rata_T_H(n,o)=S2_rata(n,o); BTS_kontrol_T_H(n,o)=BTS(2); Uk_T_H(n,o)=[handoff];
delay_T_H(n,o)=d2i(n,o);
S_mean_T_H(n,o)= S22_rata_eks(n,o);
elseif S1_rata(n,o) < t(m) && S1_rata(n,o)+h(p) < S3_rata(n,o) && S2_rata(n,o) < S3_rata(n,o)
S_T_H(n,o)=S3(n,o);
S_rata_T_H(n,o)=S3_rata(n,o); BTS_kontrol_T_H(n,o)=BTS(3); Uk_T_H(n,o)=[handoff];
delay_T_H(n,o)=d3i(n,o);
S_mean_T_H(n,o)= S33_rata_eks(n,o);
else
S_mean_T_H(n,o)= S11_rata_eks(n,o);
end end
%% jika BTS yang menangani MS sebelumnya adalah BTS_2 elseif BTS_kontrol_T_H(n,o-1)==BTS(2)
if S_rata_T_H(n,(o-12:o-1))<Sdrop & S2_rata(n,o)<Sdrop
continue;
else
if S2_rata(n,o) < t(m) && S2_rata(n,o)+h(p) < S1_rata(n,o) && S1_rata(n,o) > S3_rata(n,o)
S_T_H(n,o)=S1(n,o);
S_rata_T_H(n,o)=S1_rata(n,o); BTS_kontrol_T_H(n,o)=BTS(1); Uk_T_H(n,o)=[handoff];
delay_T_H(n,o)=d1i(n,o);
S_mean_T_H(n,o)= S11_rata_eks(n,o);
elseif S2_rata(n,o) < t(m) && S2_rata(n,o)+h(p) < S3_rata(n,o) && S1_rata(n,o) < S3_rata(n,o)
S_T_H(n,o)=S3(n,o);
S_rata_T_H(n,o)=S3_rata(n,o); BTS_kontrol_T_H(n,o)=BTS(3); Uk_T_H(n,o)=[handoff];
delay_T_H(n,o)=d3i(n,o);
S_mean_T_H(n,o)= S33_rata_eks(n,o);
else
end end
%% jika BTS yang menangani MS sebelumnya adalah BTS_3 elseif BTS_kontrol_T_H(n,o-1)==BTS(3)
if S_rata_T_H(n,(o-12:o-1))<Sdrop & S3_rata(n,o)<Sdrop
continue;
else
if S3_rata(n,o) < t(m) && S3_rata(n,o)+h(p) < S1_rata(n,o) && S1_rata(n,o) > S2_rata(n,o)
S_T_H(n,o)=S1(n,o);
S_rata_T_H(n,o)=S1_rata(n,o); BTS_kontrol_T_H(n,o)=BTS(1); Uk_T_H(n,o)=[handoff];
delay_T_H(n,o)=d1i(n,o);
S_mean_T_H(n,o)= S11_rata_eks(n,o);
elseif S3_rata(n,o) < t(m) && S3_rata(n,o)+h(p) < S2_rata(n,o) && S1_rata(n,o) < S2_rata(n,o)
S_T_H(n,o)=S2(n,o);
S_rata_T_H(n,o)=S2_rata(n,o); BTS_kontrol_T_H(n,o)=BTS(2); Uk_T_H(n,o)=[handoff];
delay_T_H(n,o)=d2i(n,o);
S_mean_T_H(n,o)= S22_rata_eks(n,o);
else
S_mean_T_H(n,o)= S33_rata_eks(n,o);
end end
%% jika keadaan sebelumnya MS mengalami drop, maka dieksekusi pemilihan BTS
else
%% jika BTS_1 yang terbaik
if (S1_rata(n,o) > Smin) && (S1_rata(n,o) > S2_rata(n,o)) && (S1_rata(n,o) > S3_rata(n,o))
S_T_H(n,o)=S1(n,o);
S_rata_T_H(n,o)=S1_rata(n,o); BTS_kontrol_T_H(n,o)=BTS(1); Uk_T_H(n,o)=[tidak_handoff]; delay_T_H(n,o)=d1i(n,o);
S_mean_T_H(n,o)= S11_rata_eks(n,o);
%% jika BTS_2 yang terbaik
elseif (S2_rata(n,o) > Smin) && (S2_rata(n,o) > S1_rata(n,o)) && (S2_rata(n,o) > S3_rata(n,o))
S_T_H(n,o)=S2(n,o);
S_rata_T_H(n,o)=S2_rata(n,o); BTS_kontrol_T_H(n,o)=BTS(2); Uk_T_H(n,o)=[tidak_handoff]; delay_T_H(n,o)=d2i(n,o);
S_mean_T_H(n,o)= S22_rata_eks(n,o);
%% jika BTS_3 yang terbaik
elseif (S3_rata(n,o) > Smin) && (S3_rata(n,o) > S1_rata(n,o)) && (S3_rata(n,o) > S2_rata(n,o))
S_T_H(n,o)=S3(n,o);
Uk_T_H(n,o)=[tidak_handoff]; delay_T_H(n,o)=d3i(n,o);
S_mean_T_H(n,o)= S33_rata_eks(n,o);
else
continue;
end
1/s*sum((1/N*(sum(((((S_T_H<Smax)&(S_T_H>=Smin)).*S_T_H)+...
((S_T_H>=Smax).*Smax))')))-...
((Smin.*abs(N-sum((S_T_H>=Smin)')).*abs(sum((S_T_H>=Smin)')))./(P*N^2))); Prob_Sdrop_T_H1(m,:)=1/s*sum(mean(Prob_Sdrop_T_H'));
elseif h(p)==2
Uk_T_H2_rata(m,:)=1/s*sum(sum(Uk_T_H'));
delay_T_H2_rata(m,:)=1/s*sum(sum(delay_T_HH')); CQSLx_T_H2_rata(m,:)=
1/s*sum((1/N*(sum(((((S_T_H<Smax)&(S_T_H>=Smin)).*S_T_H)+...
((S_T_H>=Smax).*Smax))')))-...
((Smin.*abs(N-sum((S_T_H>=Smin)')).*abs(sum((S_T_H>=Smin)')))./(P*N^2))); Prob_Sdrop_T_H2(m,:)=1/s*sum(mean(Prob_Sdrop_T_H'));
elseif h(p)==3
Uk_T_H3_rata(m,:)=1/s*sum(sum(Uk_T_H'));
delay_T_H3_rata(m,:)=1/s*sum(sum(delay_T_HH')); CQSLx_T_H3_rata(m,:)=
1/s*sum((1/N*(sum(((((S_T_H<Smax)&(S_T_H>=Smin)).*S_T_H)+...
((S_T_H>=Smax).*Smax))')))-...
((Smin.*abs(N-sum((S_T_H>=Smin)')).*abs(sum((S_T_H>=Smin)')))./(P*N^2))); Prob_Sdrop_T_H3(m,:)=1/s*sum(mean(Prob_Sdrop_T_H'));
elseif h(p)==4
Uk_T_H4_rata(m,:)=1/s*sum(sum(Uk_T_H'));
delay_T_H4_rata(m,:)=1/s*sum(sum(delay_T_HH')); CQSLx_T_H4_rata(m,:)=
1/s*sum((1/N*(sum(((((S_T_H<Smax)&(S_T_H>=Smin)).*S_T_H)+...
((S_T_H>=Smax).*Smax))')))-...
((Smin.*abs(N-sum((S_T_H>=Smin)')).*abs(sum((S_T_H>=Smin)')))./(P*N^2))); Prob_Sdrop_T_H4(m,:)=1/s*sum(mean(Prob_Sdrop_T_H'));
elseif h(p)==5
Uk_T_H5_rata(m,:)=1/s*sum(sum(Uk_T_H'));
delay_T_H5_rata(m,:)=1/s*sum(sum(delay_T_HH')); CQSLx_T_H5_rata(m,:)=
1/s*sum((1/N*(sum(((((S_T_H<Smax)&(S_T_H>=Smin)).*S_T_H)+...
((S_T_H>=Smax).*Smax))')))-...
Prob_Sdrop_T_H5(m,:)=1/s*sum(mean(Prob_Sdrop_T_H'));
elseif h(p)==6
Uk_T_H6_rata(m,:)=1/s*sum(sum(Uk_T_H'));
delay_T_H6_rata(m,:)=1/s*sum(sum(delay_T_HH')); CQSLx_T_H6_rata(m,:)=
1/s*sum((1/N*(sum(((((S_T_H<Smax)&(S_T_H>=Smin)).*S_T_H)+...
((S_T_H>=Smax).*Smax))')))-...
((Smin.*abs(N-sum((S_T_H>=Smin)')).*abs(sum((S_T_H>=Smin)')))./(P*N^2))); Prob_Sdrop_T_H6(m,:)=1/s*sum(mean(Prob_Sdrop_T_H'));
elseif h(p)==7
Uk_T_H7_rata(m,:)=1/s*sum(sum(Uk_T_H'));
delay_T_H7_rata(m,:)=1/s*sum(sum(delay_T_HH')); CQSLx_T_H7_rata(m,:)=
1/s*sum((1/N*(sum(((((S_T_H<Smax)&(S_T_H>=Smin)).*S_T_H)+...
((S_T_H>=Smax).*Smax))')))-...
((Smin.*abs(N-sum((S_T_H>=Smin)')).*abs(sum((S_T_H>=Smin)')))./(P*N^2))); Prob_Sdrop_T_H7(m,:)=1/s*sum(mean(Prob_Sdrop_T_H'));
elseif h(p)==8
Uk_T_H8_rata(m,:)=1/s*sum(sum(Uk_T_H'));
delay_T_H8_rata(m,:)=1/s*sum(sum(delay_T_HH')); CQSLx_T_H8_rata(m,:)=
1/s*sum((1/N*(sum(((((S_T_H<Smax)&(S_T_H>=Smin)).*S_T_H)+...
((S_T_H>=Smax).*Smax))')))-...
((Smin.*abs(N-sum((S_T_H>=Smin)')).*abs(sum((S_T_H>=Smin)')))./(P*N^2))); Prob_Sdrop_T_H8(m,:)=1/s*sum(mean(Prob_Sdrop_T_H'));
elseif h(p)==9
Uk_T_H9_rata(m,:)=1/s*sum(sum(Uk_T_H'));
delay_T_H9_rata(m,:)=1/s*sum(sum(delay_T_HH')); CQSLx_T_H9_rata(m,:)=
1/s*sum((1/N*(sum(((((S_T_H<Smax)&(S_T_H>=Smin)).*S_T_H)+...
((S_T_H>=Smax).*Smax))')))-...
((Smin.*abs(N-1/s*sum((1/N*(sum(((((S_T_H<Smax)&(S_T_H>=Smin)).*S_T_H)+...
((S_T_H>=Smax).*Smax))')))-...
((Smin.*abs(N-Uk_T_H1_rata_0_10_20_30(:,rata)=[Uk_T_H1_rata];%jlh handoff
rata-rata
delay_T_H1_rata_0_10_20_30(:,rata)=[delay_T_H1_rata];%lama delay
rata-rata
CQSLx_T_H1_rata_0_10_20_30(:,rata)=[CQSLx_T_H1_rata];% kualitas
Prob_Sdrop_T_H1_rata_0_10_20_30(:,rata)=[Prob_Sdrop_T_H1];% link drop rata-rata
%=================================================================
%%%%% Metode variasi Treshold dengan Histeresis Adaptif%%%% %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
t=0:20;% variasi treshold (dB)
R=D/sqrt(3);% radius sel/ BTS
BTS= [1;2;3];
S_var_T_adap_H= [S2(:,1) zeros(s,N-1)];
S_rata_var_T_adap_H= [S2_rata(:,1) zeros(s,N-1)];
BTS_kontrol_var_T_adap_H=[BTS(2)*ones(s,1) zeros(s,N-1)]; Uk_var_T_adap_H=zeros(s,N);
S_mean_T_Hadap= [S2_rata_eks(:,1) zeros(s,N-1)];
%======================================================
d_MS_BTS_kontrol=[d2i(:,1).*ones(s,1) zeros(s,N-1)]; h_adap=[d_MS_BTS_kontrol(:,1).*ones(s,1) zeros(s,N-1)];
for mm=1:length(t)
for nn=1:s
for oo=2:N
%%================================= if oo<=12
d_MS_BTS_kontrol(nn,oo)=d2i(nn,oo);
S_mean_T_Hadap(nn,oo)= S22_rata_eks(nn,oo);
else
%% BTS yang menangani sebelumnya adalah BTS_1
if BTS_kontrol_var_T_adap_H(nn,oo-1)==BTS(1)
d_MS_BTS_kontrol(nn,oo)=d1i(nn,oo);
h_adap(nn,oo)=max(20*(1-(d_MS_BTS_kontrol(nn,oo)./R).^4),0);
if S_rata_var_T_adap_H(nn,(oo-12:oo-1))<Sdrop & S1_rata(nn,oo)<Sdrop
continue;
else
if S1_rata(nn,oo) < t(mm) && S1_rata(nn,oo)+h_adap(nn,oo) < S2_rata(nn,oo) && S2_rata(nn,oo) > S3_rata(nn,oo)
S_var_T_adap_H(nn,oo)=S2(nn,oo);
S_rata_var_T_adap_H(nn,oo)=S2_rata(nn,oo); BTS_kontrol_var_T_adap_H(nn,oo)=BTS(2); Uk_var_T_adap_H(nn,oo)=[handoff];
delay_T_Hadap(nn,oo)=d2i(nn,oo);
S_mean_T_Hadap(nn,oo)= S22_rata_eks(nn,oo);
elseif S1_rata(nn,oo) < t(mm) &&
S1_rata(nn,oo)+h_adap(nn,oo) < S3_rata(nn,oo) && S2_rata(nn,oo) < S3_rata(nn,oo)
S_mean_T_Hadap(nn,oo)= S33_rata_eks(nn,oo);
else
S_mean_T_Hadap(nn,oo)= S11_rata_eks(nn,oo);
end end
elseif BTS_kontrol_var_T_adap_H(nn,oo-1)==BTS(2) d_MS_BTS_kontrol(nn,oo)=d2i(nn,oo);
h_adap(nn,oo)=max(20*(1-(d_MS_BTS_kontrol(nn,oo)./R).^4),0);
if S_rata_var_T_adap_H(nn,(oo-12:oo-1))<Sdrop & S2_rata(nn,oo)<Sdrop
else
if S2_rata(nn,oo) < t(mm) && S2_rata(nn,oo)+h_adap(nn,oo) < S1_rata(nn,oo) && S1_rata(nn,oo) > S3_rata(nn,oo)
S_var_T_adap_H(nn,oo)=S1(nn,oo);
S_rata_var_T_adap_H(nn,oo)=S1_rata(nn,oo); BTS_kontrol_var_T_adap_H(nn,oo)=BTS(1); Uk_var_T_adap_H(nn,oo)=[handoff];
delay_T_Hadap(nn,oo)=d1i(nn,oo);
S_mean_T_Hadap(nn,oo)= S11_rata_eks(nn,oo);
elseif S2_rata(nn,oo) < t(mm) &&
S2_rata(nn,oo)+h_adap(nn,oo) < S3_rata(nn,oo) && S1_rata(nn,oo) < S3_rata(nn,oo)
S_mean_T_Hadap(nn,oo)= S33_rata_eks(nn,oo);
else
S_mean_T_Hadap(nn,oo)= S22_rata_eks(nn,oo);
end end
elseif BTS_kontrol_var_T_adap_H(nn,oo-1)==BTS(3) d_MS_BTS_kontrol(nn,oo)=d3i(nn,oo);
h_adap(nn,oo)=max(20*(1-(d_MS_BTS_kontrol(nn,oo)./R).^4),0);
if S_rata_var_T_adap_H(nn,(oo-12:oo-1))<Sdrop & S3_rata(nn,oo)<Sdrop
continue;
else
if S3_rata(nn,oo) < t(mm) && S3_rata(nn,oo)+h_adap(nn,oo) < S1_rata(nn,oo) && S1_rata(nn,oo) > S2_rata(nn,oo)
S_var_T_adap_H(nn,oo)=S1(nn,oo);
S_rata_var_T_adap_H(nn,oo)=S1_rata(nn,oo); BTS_kontrol_var_T_adap_H(nn,oo)=BTS(1); Uk_var_T_adap_H(nn,oo)=[handoff];
delay_T_Hadap(nn,oo)=d1i(nn,oo);
S_mean_T_Hadap(nn,oo)= S11_rata_eks(nn,oo);
elseif S3_rata(nn,oo) < t(mm) &&
S3_rata(nn,oo)+h_adap(nn,oo) < S2_rata(nn,oo) && S1_rata(nn,oo) < S2_rata(nn,oo)
S_mean_T_Hadap(nn,oo)= S22_rata_eks(nn,oo);
else
S_mean_T_Hadap(nn,oo)= S33_rata_eks(nn,oo);
end else
if (S1_rata(nn,oo) > Smin) && (S1_rata(nn,oo) > S2_rata(nn,oo)) && (S1_rata(nn,oo) > S3_rata(nn,oo))
%=====================================
S_mean_T_Hadap(nn,oo)= S11_rata_eks(nn,oo);
elseif (S2_rata(nn,oo) > Smin) && (S2_rata(nn,oo) > S1_rata(nn,oo)) && (S2_rata(nn,oo) > S3_rata(nn,oo))
%=====================================
S_mean_T_Hadap(nn,oo)= S22_rata_eks(nn,oo);
elseif (S3_rata(nn,o) > Smin) && (S3_rata(nn,oo) > S1_rata(nn,oo)) && (S3_rata(nn,oo) > S2_rata(nn,oo))
%=====================================
S_mean_T_Hadap(nn,oo)= S33_rata_eks(nn,oo);
else
continue;
end
.*S_var_T_adap_H)+...
((Smin.*abs(N-%%%%% Metode Suboptimal SDH %%% %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
varians_kuadrat(rata)=tho*sqrt((1-(ai^2)).*(1-(b(rata).^2)));%
variansi sinyal rata-rata
for v=1:s
for u=1:N-1
Z1(v,u)=qfunc((S1_rata_eks(v,u+1)-% nilai cost(c)
C=[0.0045,0.007,0.01,0.025,0.04,0.06,0.1,0.13,0.25,0.35,0.45,0.55, 0.65,0.75,0.85,0.95];
BTS= [1;2;3];
Z= [Z2(:,1) zeros(s,N-1)]; S_SDH=[S2(:,1) zeros(s,N-1)];
S_rata_SDH=[S2_rata(:,1) zeros(s,N-1)];
BTS_kontrol_SDH=[BTS(2)*ones(s,1) zeros(s,N-1)]; Uk_SDH=zeros(s,N);
delay_SDH=[];
S_mean_SDH= [S2_rata_eks(:,1) zeros(s,N-1)];
for x=1:length(C)
for y=1:s
for z=2:N
if z<=12
S_SDH(y,z)=S2(y,z);
S_rata_SDH(y,z)=S2_rata(y,z); BTS_kontrol_SDH(y,z)=BTS(2); Uk_SDH(y,z)=[tidak_handoff]; delay_SDH(y,z)=d2i(y,z);
S_mean_SDH(y,z)= S22_rata_eks(y,z);
else
if BTS_kontrol_SDH(y,z-1)==BTS(1)
if S_rata_SDH(y,(z-12:z-1))<Sdrop & S1_rata(y,z)<Sdrop
continue;
if Z1(y,z-1)>1)+C(x) &&
Z2(y,z-S_mean_SDH(y,z)= S22_rata_eks(y,z);
elseif Z1(y,z-1)>Z3(y,z-1)+C(x) && Z2(y,z-1)+C(x)>Z3(y,z-1)+C(x)
S_mean_SDH(y,z)= S33_rata_eks(y,z);
else
S_mean_SDH(y,z)= S11_rata_eks(y,z);
end end
elseif BTS_kontrol_SDH(y,z-1)==BTS(2)
if S_rata_SDH(y,(z-12:z-1))<Sdrop & S2_rata(y,z)<Sdrop
continue;
else
if Z2(y,z-1)>1)+C(x) && Z1(y,z-1)+C(x)<Z3(y,z-1)+C(x)
S_mean_SDH(y,z)= S11_rata_eks(y,z);
elseif Z2(y,z-1)>Z3(y,z-1)+C(x) && Z1(y,z-1)+C(x)>Z3(y,z-1)+C(x)
S_mean_SDH(y,z)= S33_rata_eks(y,z);
else
S_mean_SDH(y,z)= S22_rata_eks(y,z);
end end
elseif BTS_kontrol_SDH(y,z-1)==BTS(3)
if S_rata_SDH(y,(z-12:z-1))<Sdrop & S3_rata(y,z)<Sdrop
continue;
if Z3(y,z-1)>1)+C(x) &&
Z1(y,z-S_mean_SDH(y,z)= S11_rata_eks(y,z);
elseif Z3(y,z-1)>Z2(y,z-1)+C(x) && Z1(y,z-1)+C(x)>Z2(y,z-1)+C(x)
S_mean_SDH(y,z)= S22_rata_eks(y,z);
else
S_mean_SDH(y,z)= S33_rata_eks(y,z);
end end else
if (S1_rata(y,z) > Smin) & (S1_rata(y,z) > S2_rata(y,z)) & (S1_rata(y,z) > S3_rata(y,z))
S_SDH(y,z)=S1(y,z);
S_rata_SDH(y,z)=S1_rata(y,z); BTS_kontrol_SDH(y,z)=BTS(1); Uk_SDH(y,z)=[tidak_handoff]; delay_SDH(y,z)=d1i(y,z);
S_mean_SDH(y,z)= S11_rata_eks(y,z);
elseif (S2_rata(y,z) > Smin) & (S1_rata(y,z) < S2_rata(y,z)) & (S2_rata(y,z) > S3_rata(y,z))
S_SDH(y,z)=S2(y,z);
S_rata_SDH(y,z)=S2_rata(y,z); BTS_kontrol_SDH(y,z)=BTS(2); Uk_SDH(y,z)=[tidak_handoff]; delay_SDH(y,z)=d2i(y,z);
S_mean_SDH(y,z)= S22_rata_eks(y,z);
elseif (S3_rata(y,z) > Smin) & (S1_rata(y,z) < S3_rata(y,z)) & (S2_rata(y,z) < S3_rata(y,z))
S_SDH(y,z)=S3(y,z);
S_rata_SDH(y,z)=S3_rata(y,z); BTS_kontrol_SDH(y,z)=BTS(3); Uk_SDH(y,z)=[tidak_handoff]; delay_SDH(y,z)=d3i(y,z);
S_mean_SDH(y,z)= S33_rata_eks(y,z);
else
continue;
end end end
delay_SDHO=(delay_SDH>(D/2)).*ts;
1/s*sum((1/N*(sum(((((S_SDH<Smax)&(S_SDH>=Smin)).*S_SDH)+...
((S_SDH>=Smax).*Smax))')))-...
((Smin.*abs(N-sum((S_SDH>=Smin)')).*abs(sum((S_SDH>=Smin)')))./(P*N^2))); Prob_Sdrop_SDH_rata(x,:)= 1/s*sum(mean(Prob_Sdrop_SDH'));
end
% figure hasil simulasi
% (A).analisa pengaruh parameter kontrol(treshold, histeresis dan cost)
% terhadap parameter tradeoff handoff
% 1)kurva variasi threshold dgn histeresis tetap (d rata-rata=0)
figure(1) subplot(221)
plot(1:10,[CQSLx_T_H1_rata_0_10_20_30(11:20,1),CQSLx_T_H2_rata_0_1
0_20_30(11:20,1),CQSLx_T_H3_rata_0_10_20_30(11:20,1),...
CQSLx_T_H4_rata_0_10_20_30(11:20,1),CQSLx_T_H5_rata_0_10_20_30(11:
20,1),CQSLx_T_H6_rata_0_10_20_30(11:20,1),...
CQSLx_T_H7_rata_0_10_20_30(11:20,1),CQSLx_T_H8_rata_0_10_20_30(11:
20,1),CQSLx_T_H9_rata_0_10_20_30(11:20,1),...
CQSLx_T_H10_rata_0_10_20_30(11:20,1)]')
xlabel('Histeresis (dB)');ylabel('CQSL rata-rata(dB)') legend('threshold= 11 dB','threshold= 12 dB','threshold= 13 dB',...
'threshold= 14 dB','threshold= 15 dB','threshold= 16 dB',...
'threshold= 17 dB','threshold= 18 dB','threshold= 19 dB',...
'threshold= 20 dB') subplot(222)
plot(1:10,[Prob_Sdrop_T_H1_rata_0_10_20_30(11:20,1),Prob_Sdrop_T_H 2_rata_0_10_20_30(11:20,1),Prob_Sdrop_T_H3_rata_0_10_20_30(11:20,1 ),...
Prob_Sdrop_T_H4_rata_0_10_20_30(11:20,1),Prob_Sdrop_T_H5_rata_0_10
_20_30(11:20,1),Prob_Sdrop_T_H6_rata_0_10_20_30(11:20,1),...
Prob_Sdrop_T_H7_rata_0_10_20_30(11:20,1),Prob_Sdrop_T_H8_rata_0_10
_20_30(11:20,1),Prob_Sdrop_T_H9_rata_0_10_20_30(11:20,1),...
Prob_Sdrop_T_H10_rata_0_10_20_30(11:20,1)]')
xlabel('Histeresis (dB)');ylabel('link drop rata-rata') legend('threshold= 11 dB','threshold= 12 dB','threshold= 13 dB',...
'threshold= 14 dB','threshold= 15 dB','threshold= 16 dB',...
'threshold= 17 dB','threshold= 18 dB','threshold= 19 dB',...
subplot(223)
plot(1:10,[delay_T_H1_rata_0_10_20_30(11:20,1),delay_T_H2_rata_0_1
0_20_30(11:20,1),delay_T_H3_rata_0_10_20_30(11:20,1),...
delay_T_H4_rata_0_10_20_30(11:20,1),delay_T_H5_rata_0_10_20_30(11:
20,1),delay_T_H6_rata_0_10_20_30(11:20,1),...
delay_T_H7_rata_0_10_20_30(11:20,1),delay_T_H8_rata_0_10_20_30(11:
20,1),delay_T_H9_rata_0_10_20_30(11:20,1),...
delay_T_H10_rata_0_10_20_30(11:20,1)]')
xlabel('Histeresis (dB)');ylabel('Delay rata-rata(s)') legend('threshold= 11 dB','threshold= 12 dB','threshold= 13 dB',...
'threshold= 14 dB','threshold= 15 dB','threshold= 16 dB',...
'threshold= 17 dB','threshold= 18 dB','threshold= 19 dB',...
'threshold= 20 dB') subplot(224)
plot(1:10,[Uk_T_H1_rata_0_10_20_30(11:20,1),Uk_T_H2_rata_0_10_20_3
0(11:20,1),Uk_T_H3_rata_0_10_20_30(11:20,1),...
Uk_T_H4_rata_0_10_20_30(11:20,1),Uk_T_H5_rata_0_10_20_30(11:20,1),
Uk_T_H6_rata_0_10_20_30(11:20,1),...
Uk_T_H7_rata_0_10_20_30(11:20,1),Uk_T_H8_rata_0_10_20_30(11:20,1),
Uk_T_H9_rata_0_10_20_30(11:20,1),...
Uk_T_H10_rata_0_10_20_30(11:20,1)]')
xlabel('Histeresis (dB)');ylabel('handoff rata-rata')
legend('threshold= 11 dB','threshold= 12 dB','threshold= 13 dB',...
'threshold= 14 dB','threshold= 15 dB','threshold= 16 dB',...
'threshold= 17 dB','threshold= 18 dB','threshold= 19 dB',...
'threshold= 20 dB')
% 2)kurva variasi threshold dgn histeresis adaptif (d rata-rata=0)
figure(2) subplot(221)
plot(0:20,CQSLx_var_T_Hadaptif_rata_0_10_20_30(:,1))
xlabel('threshold(0-20 dB)');ylabel('CQSL rata-rata(dB)')
title('CQSL rata-rata & threshold dgn histeresis adaptif') legend('d rata-rata=0')
subplot(222)
plot(0:20,Prob_Sdrop_T_Hadaptif_rata_0_10_20_30(:,1))
xlabel('threshold (0-20 dB)');ylabel('link drop rata-rata')
title('laju drop & threshold dgn histeresis adaptif') legend('d rata-rata=0')
subplot(223)
plot(0:20,delay_T_Hadaptif_rata_0_10_20_30(:,1))
xlabel('threshold (0-20 dB)');ylabel('Delay rata-rata(s)') title('Delay rata-rata & threshold dgn histeresis adaptif') legend('d rata-rata=0')
subplot(224)
plot(0:20,Uk_var_T_Hadaptif_rata_0_10_20_30(:,1))
xlabel('threshold (0-20 dB)');ylabel('handoff rata-rata')
title('handoff rata-rata & threshold dgn histeresis adaptif') legend('d rata-rata=0')
C=[0.0045,0.007,0.01,0.025,0.04,0.06,0.1,0.13,0.25,0.35,0.45,0.55, 0.65,0.75,0.85,0.95];
figure(3) subplot(221)
plot(C,CQSLx_SDH_rata_0_10_20_30(:,1))
xlabel('variasi C');ylabel('CQSL rata-rata(dB)') title('CQSL rata-rata & variasi cost(C)')
legend('d rata-rata=0') subplot(222)
plot(C,Prob_Sdrop_SDH_rata_0_10_20_30(:,1))
xlabel('variasi C');ylabel('link drop rata-rata') title('laju drop & variasi cost(C)')
legend('d rata-rata=0') subplot(223)
plot(C,delay_SDH_rata_0_10_20_30(:,1))
xlabel('variasi C');ylabel('Delay rata-rata(s)') title('Delay rata-rata & variasi cost(C)')
legend('d rata-rata=0') subplot(224)
plot(C,Uk_SDH_rata_0_10_20_30(:,1))
xlabel('variasi C');ylabel('handoff rata-rata') title('handoff rata-rata & variasi cost (C)') legend('d rata-rata=0')
% (B).analisis pengaruh panjang rata-rata window terhadap parameter tradeoff
% handoff
% 1)kurva variasi threshold dgn histeresis tetap 1 dB (d rata-rata=0,10,20,30)
figure(4) subplot(221)
plot(1:20,CQSLx_T_H1_rata_0_10_20_30)
xlabel('threshold(1-20 dB)');ylabel('CQSL rata-rata(dB)')
title('CQSL rata-rata & threshold dgn histeresis 1 dB')
legend('d rata-rata=0','d rata-rata=10','d rata-rata=20','d rata-rata=30')
subplot(222)
plot(1:20,Prob_Sdrop_T_H1_rata_0_10_20_30)
xlabel('threshold (1-20 dB)');ylabel('link drop rata-rata')
title('laju drop & threshold dgn histeresis 1 dB')
legend('d rata-rata=0','d rata-rata=10','d rata-rata=20','d rata-rata=30')
subplot(223)
plot(1:20,delay_T_H1_rata_0_10_20_30)
xlabel('threshold (1-20 dB)');ylabel('Delay rata-rata(s)') title('Delay rata-rata & threshold dgn histeresis 1 dB')
legend('d rata-rata=0','d rata-rata=10','d rata-rata=20','d rata-rata=30')
subplot(224)
plot(1:20,Uk_T_H1_rata_0_10_20_30)
xlabel('threshold (1-20 dB)');ylabel('handoff rata-rata')
title('handoff rata-rata & threshold dgn histeresis 1 dB')
legend('d rata-rata=0','d rata-rata=10','d rata-rata=20','d rata-rata=30')
% 2)kurva variasi threshold dgn histeresis adaptif (d rata-rata=0,10,20,30)
subplot(221)
plot(0:20,CQSLx_var_T_Hadaptif_rata_0_10_20_30)
xlabel('threshold(0-20 dB)');ylabel('CQSL rata-rata(dB)')
title('CQSL rata-rata & threshold dgn histeresis adaptif')
legend('d rata-rata=0','d rata-rata=10','d rata-rata=20','d rata-rata=30')
subplot(222)
plot(0:20,Prob_Sdrop_T_Hadaptif_rata_0_10_20_30)
xlabel('threshold (0-20 dB)');ylabel('link drop rata-rata')
title('laju drop & threshold dgn histeresis adaptif')
legend('d rata-rata=0','d rata-rata=10','d rata-rata=20','d rata-rata=30')
subplot(223)
plot(0:20,delay_T_Hadaptif_rata_0_10_20_30)
xlabel('threshold (0-20 dB)');ylabel('Delay rata-rata(s)') title('Delay rata-rata & threshold dgn histeresis adaptif')
legend('d rata-rata=0','d rata-rata=10','d rata-rata=20','d rata-rata=30')
subplot(224)
plot(0:20,Uk_var_T_Hadaptif_rata_0_10_20_30)
xlabel('threshold (0-20 dB)');ylabel('handoff rata-rata')
title('handoff rata-rata & threshold dgn histeresis adaptif') legend('d rata-rata=0','d rata-rata=10','d rata-rata=20','d rata-rata=30')
% 3)kurva variasi cost metode SDH (d rata-rata=0,10,20,30)
C=[0.0045,0.007,0.01,0.025,0.04,0.06,0.1,0.13,0.25,0.35,0.45,0.55, 0.65,0.75,0.85,0.95];
figure(6) subplot(221)
plot(C,CQSLx_SDH_rata_0_10_20_30)
xlabel('variasi C');ylabel('CQSL rata-rata(dB)') title('CQSL rata-rata & variasi cost(C)')
legend('d rata-rata=0','d rata-rata=10','d rata-rata=20','d rata-rata=30')
subplot(222)
plot(C,Prob_Sdrop_SDH_rata_0_10_20_30)
xlabel('variasi C');ylabel('link drop rata-rata') title('laju drop & variasi cost(C)')
legend('d rata-rata=0','d rata-rata=10','d rata-rata=20','d rata-rata=30')
subplot(223)
plot(C,delay_SDH_rata_0_10_20_30)
xlabel('variasi C');ylabel('Delay rata-rata(s)') title('Delay rata-rata & variasi cost(C)')
legend('d rata-rata=0','d rata-rata=10','d rata-rata=20','d rata-rata=30')
subplot(224)
plot(C,Uk_SDH_rata_0_10_20_30)
xlabel('variasi C');ylabel('handoff rata-rata') title('handoff rata-rata & variasi cost (C)')
legend('d rata-rata=0','d rata-rata=10','d rata-rata=20','d rata-rata=30')
% (C).pendekatan optimalisasi parameter tradeoff handoff
figure(7)
plot3([Uk_T_H1_rata_0_10_20_30(13:18,1),Uk_T_H2_rata_0_10_20_30(13
:18,1),Uk_T_H3_rata_0_10_20_30(13:18,1),...
Uk_T_H4_rata_0_10_20_30(13:18,1)],...
[delay_T_H1_rata_0_10_20_30(13:18,1),delay_T_H2_rata_0_10_20_30(13
:18,1),delay_T_H3_rata_0_10_20_30(13:18,1),...
delay_T_H4_rata_0_10_20_30(13:18,1)],...
[Prob_Sdrop_T_H1_rata_0_10_20_30(13:18,1),Prob_Sdrop_T_H2_rata_0_1
0_20_30(13:18,1),Prob_Sdrop_T_H3_rata_0_10_20_30(13:18,1),...
Prob_Sdrop_T_H4_rata_0_10_20_30(13:18,1)]) hold on;
plot3(Uk_var_T_Hadaptif_rata_0_10_20_30(13:18,1),delay_T_Hadaptif_
rata_0_10_20_30(13:18,1),...
Prob_Sdrop_T_Hadaptif_rata_0_10_20_30(13:18,1)) hold on;
plot3(Uk_SDH_rata_0_10_20_30(:,1),delay_SDH_rata_0_10_20_30(:,1),.
..
Prob_Sdrop_SDH_rata_0_10_20_30(:,1));
xlabel('handoff rata-rata');ylabel('Delay
rata-rata');zlabel('L.drop rata-rata');
legend('threshold dgn histeresis= 1 dB','threshold dgn histeresis=
2 dB','threshold dgn histeresis= 3 dB','threshold dgn histeresis= 4 dB',...
'threshold dgn histeresis adaptif','suboptimal SDH')
figure(8)
% d rata-rata=10
plot3([Uk_T_H1_rata_0_10_20_30(13:18,2),Uk_T_H2_rata_0_10_20_30(13
:18,2),Uk_T_H3_rata_0_10_20_30(13:18,2),...
Uk_T_H4_rata_0_10_20_30(13:18,2)],...
[delay_T_H1_rata_0_10_20_30(13:18,2),delay_T_H2_rata_0_10_20_30(13
:18,2),delay_T_H3_rata_0_10_20_30(13:18,2),...
delay_T_H4_rata_0_10_20_30(13:18,2)],...
[Prob_Sdrop_T_H1_rata_0_10_20_30(13:18,2),Prob_Sdrop_T_H2_rata_0_1
0_20_30(13:18,2),Prob_Sdrop_T_H3_rata_0_10_20_30(13:18,2),...
Prob_Sdrop_T_H4_rata_0_10_20_30(13:18,2)]) hold on;
plot3(Uk_var_T_Hadaptif_rata_0_10_20_30(13:18,2),delay_T_Hadaptif_
rata_0_10_20_30(13:18,2),...
Prob_Sdrop_T_Hadaptif_rata_0_10_20_30(13:18,2)) hold on;
plot3(Uk_SDH_rata_0_10_20_30(:,2),delay_SDH_rata_0_10_20_30(:,2),.
..
Prob_Sdrop_SDH_rata_0_10_20_30(:,2));
xlabel('handoff rata-rata');ylabel('Delay
rata-rata');zlabel('L.drop rata-rata');
legend('threhold dgn histeresis= 1 dB','threshold dgn histeresis=
2 dB','threshold dgn histeresis= 3 dB','threshold dgn histeresis= 4 dB',...
'threshold dgn histeresis adaptif','suboptimal SDH')
figure(9)
%d rata-rata=20
plot3([Uk_T_H1_rata_0_10_20_30(13:18,3),Uk_T_H2_rata_0_10_20_30(13
Uk_T_H4_rata_0_10_20_30(13:18,3)],...
[delay_T_H1_rata_0_10_20_30(13:18,3),delay_T_H2_rata_0_10_20_30(13
:18,3),delay_T_H3_rata_0_10_20_30(13:18,3),...
delay_T_H4_rata_0_10_20_30(13:18,3)],...
[Prob_Sdrop_T_H1_rata_0_10_20_30(13:18,3),Prob_Sdrop_T_H2_rata_0_1
0_20_30(13:18,3),Prob_Sdrop_T_H3_rata_0_10_20_30(13:18,3),...
Prob_Sdrop_T_H4_rata_0_10_20_30(13:18,3)]) hold on;
plot3(Uk_var_T_Hadaptif_rata_0_10_20_30(13:18,3),delay_T_Hadaptif_
rata_0_10_20_30(13:18,3),...
Prob_Sdrop_T_Hadaptif_rata_0_10_20_30(13:18,3)) hold on;
plot3(Uk_SDH_rata_0_10_20_30(:,3),delay_SDH_rata_0_10_20_30(:,3),.
..
Prob_Sdrop_SDH_rata_0_10_20_30(:,3));
xlabel('handoff rata-rata');ylabel('Delay
rata-rata');zlabel('L.drop rata-rata');
legend('threshold dgn histeresis= 1 dB','threshold dgn histeresis=
2 dB','threshold dgn histeresis= 3 dB','threshold dgn histeresis= 4 dB',...
'threshold dgn histeresis adaptif','suboptimal SDH')
figure(10)
%d rata-rata=30
plot3([Uk_T_H1_rata_0_10_20_30(13:18,4),Uk_T_H2_rata_0_10_20_30(13
:18,4),Uk_T_H3_rata_0_10_20_30(13:18,4),...
Uk_T_H4_rata_0_10_20_30(13:18,4)],...
[delay_T_H1_rata_0_10_20_30(13:18,4),delay_T_H2_rata_0_10_20_30(13
:18,4),delay_T_H3_rata_0_10_20_30(13:18,4),...
delay_T_H4_rata_0_10_20_30(13:18,4)],...
[Prob_Sdrop_T_H1_rata_0_10_20_30(13:18,4),Prob_Sdrop_T_H2_rata_0_1
0_20_30(13:18,4),Prob_Sdrop_T_H3_rata_0_10_20_30(13:18,4),...
Prob_Sdrop_T_H4_rata_0_10_20_30(13:18,4)]) hold on;
plot3(Uk_var_T_Hadaptif_rata_0_10_20_30(13:18,4),delay_T_Hadaptif_
rata_0_10_20_30(13:18,4),...
Prob_Sdrop_T_Hadaptif_rata_0_10_20_30(13:18,4)) hold on;
plot3(Uk_SDH_rata_0_10_20_30(:,4),delay_SDH_rata_0_10_20_30(:,4),.
..
Prob_Sdrop_SDH_rata_0_10_20_30(:,4));
xlabel('handoff rata-rata');ylabel('Delay
rata-rata');zlabel('L.drop rata-rata');
legend('threshold dgn histeresis= 1 dB','threshold dgn histeresis=
2 dB','threshold dgn histeresis= 3 dB','threshold dgn histeresis= 4 dB',...
'threshold dgn histeresis adaptif','suboptimal SDH')
B.3 Fungsi Tetarandom dan Truncnormrnd
1.
Fungsi tetarandom
% fungsi membangkitkan teta_random function[teta_random]=tetarandom(s,N)
%teta_random_uniform adl. bil.acak uniform %teta_random adl.sudut (arah MS) dgn nilai acak
teta_random_uniform = 0+1.*rand(s,N);
for a=1:s
for b=2:N
% membangkitkan teta random(jlh simulasi,jlh titik sampel) if teta_random_uniform(a,b) >=0 && teta_random_uniform(a,b) < 0.125
teta_random(a,b) = 22.5*pi/180;
elseif teta_random_uniform(a,b) >= 0.125 && teta_random_uniform(a,b) < 0.25
teta_random(a,b) = 45*pi/180;
elseif teta_random_uniform(a,b) >= 0.25 && teta_random_uniform(a,b) < 0.375
teta_random(a,b) = 67.5*pi/180;
elseif teta_random_uniform(a,b) >= 0.375 && teta_random_uniform(a,b) < 0.5
teta_random(a,b) = 90*pi/180;
elseif teta_random_uniform(a,b) >= 0.5 && teta_random_uniform(a,b) < 0.625
teta_random(a,b) = 115.5*pi/180;
elseif teta_random_uniform(a,b) >= 0.625 && teta_random_uniform(a,b) < 0.75
teta_random(a,b) = 135*pi/180;
elseif teta_random_uniform(a,b) >= 0.75 && teta_random_uniform(a,b) < 0.875
teta_random(a,b) = 157.5*pi/180;
else
%teta_random_uniform(a,b) >= 0.875 && teta_random_uniform(a,b) < 1
teta_random(a,b) = 180*pi/180;
end
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;
end
if (nargin<3)|isempty(tho1) tho1=0;
end
if (nargin<4)|isempty(xlo) xlo=-inf;
plo=0;
else
plo=normcdf((xlo-mu1)/tho1);
end
if (nargin<5)|isempty(xhi) xhi=inf;
phi=1;
else
phi=normcdf((xhi-mu1)/tho1);
end
% test if trunation points are reversed if xlo>xhi
error 'mu1st have xlo <= xhi if both provided'
end
% 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;
% Invert through standard normal % F=norminv(r);
F3=norminv(r3);
% apply shift and scale
Distribusi Normal dan Q-Function
C.1 Distribusi Normal atau Gaussian
C.1 Distribusi Normal atau Gaussian
Sebuah r.v.X disebut sebagai r.v.normal (atau Gaussian) jika pdf-nya ditentukan
dengan Persamaan (1).
(1)
(2)
Misal :
,
Maka,
(3)
Karena pada Persamaan (3) identik dengan distribusi Gaussian
, sehingga
perhitungan Persamaan (3) didekati dengan metode numerik, yang didefinisikan
sebagai fungsi z, ditulis dengan Persamaan (4).
(4)
C.2 Q-Function
Jika normal variabel random
~ ( ,
)
, maka probabilitas bahwa:
1.
>
(
≥
) =
−
2.
<
Flow Chart
D.1
Flow Chart
Evaluasi Metode
Handoff
Data Hasil Simulasi
E.1 Tabel variasi
threshold
dengan histeresis tetap terhadap parameter
tradeoff handoff.
E.2 Tabel variasi
threshold
dengan histeresis adaptif terhadap parameter
tradeoff handoff.
E.3 Tabel variasi
cost(c)
terhadap parameter
tradeoff handoff.
E.4 Variasi
threshold
dengan histeresis 1 dB terhadap parameter
tradeoff
handoff.
E.1.a)
Tabel variasi
threshold
dengan histeresis tetap terhadap parameter
.
E.1.b)
Tabel variasi
threshold
dengan histeresis tetap terhadap parameter
.
Histeresis (dB)
Threshold
(dB) 1 2 3 4 5 6 7 8 9 10
(dB)
11 6,977517 7,321558 7,30816 7,33621 7,294477 7,269304 7,26728 7,262607 7,255852 7,239756
12 7,659373 7,918422 7,903043 7,892621 7,849147 7,789883 7,718695 7,621002 7,520473 7,414205
13 10,08691 10,13431 10,0745 9,878249 9,596868 9,32885 8,820435 8,437575 8,006864 7,678094
14 14,96554 14,86998 14,40611 13,6082 12,59456 11,60286 10,2958 9,267026 8,411999 7,827352
15 18,3419 17,85763 17,05827 15,68531 14,0549 12,45383 10,83402 9,493885 8,526717 7,889672
16 18,4267 17,94635 17,16376 15,77592 14,1505 12,50426 10,85779 9,50172 8,532796 7,890194
17 18,45342 17,96834 17,18287 15,80705 14,17404 12,51612 10,85804 9,501945 8,53285 7,890247
18 18,46019 17,97246 17,18469 15,80778 14,17426 12,51615 10,85804 9,501945 8,53285 7,890247
19 18,46112 17,9732 17,18483 15,80799 14,17426 12,51615 10,85804 9,501945 8,53285 7,890247
20 18,46127 17,97325 17,18483 15,80799 14,17426 12,51615 10,85804 9,501945 8,53285 7,890247
Threshold
(dB)
Histeresis (dB)
1 2 3 4 5 6 7 8 9 10
11 0,081492 0,07887 0,078989 0,078844 0,079084 0,079198 0,079211 0,079245 0,07929 0,079398
12 0,076989 0,075048 0,075211 0,075282 0,075542 0,075886 0,076331 0,076962 0,077598 0,078284
13 0,063477 0,063197 0,063515 0,064548 0,065998 0,067512 0,070344 0,072517 0,074926 0,076811
14 0,042541 0,042924 0,044767 0,048009 0,052626 0,057299 0,063625 0,06873 0,073053 0,076126
15 0,029394 0,03076 0,033828 0,039456 0,046631 0,05383 0,061395 0,067742 0,072567 0,07586
16 0,024896 0,026997 0,030875 0,037575 0,045393 0,053227 0,061173 0,067643 0,072516 0,075844
17 0,024052 0,026349 0,030419 0,037243 0,045188 0,053146 0,061171 0,067641 0,072516 0,075843
18 0,023955 0,026291 0,030399 0,037237 0,045185 0,053145 0,061171 0,067641 0,072516 0,075843
19 0,023951 0,026275 0,030399 0,037236 0,045185 0,053145 0,061171 0,067641 0,072516 0,075843
E.1.c)
Tabel variasi
threshold
dengan histeresis tetap terhadap parameter
(lanjutan)
E.1.d)
Tabel variasi
threshold
dengan histeresis tetap terhadap parameter
(lanjutan)
Threshold
(dB)
Histeresis (dB)
1
2
3
4
5
6
7
8
9
10
(s)
11
46,467
46,633
46,731
46,599
46,795
46,822
46,824
46,828
46,837
46,859
12
46,005
46,044
46,142
46,12
46,162
46,135
46,217
46,344
46,479
46,624
13
42,963
43,022
43,06
43,534
43,757
44,005
44,715
45,234
45,828
46,269
14
36,166
36,166
36,717
37,756
39,146
40,593
42,53
44,059
45,268
46,074
15
30,094
30,293
31,249
33,481
36,093
38,893
41,497
43,605
45,058
45,955
16
26,65
26,937
28,49
31,862
35,031
38,459
41,347
43,527
45,024
45,945
17
25,62
25,872
27,774
31,452
34,842
38,362
41,34
43,522
45,023
45,944
18
25,357
25,655
27,674
31,419
34,833
38,361
41,34
43,522
45,023
45,944
19
25,284
25,553
27,665
31,407
34,833
38,361
41,34
43,522
45,023
45,944
20
25,272
25,548
27,665
31,407
34,833
38,361
41,34
43,522
45,023
45,944
Threshold
(dB)
Histeresis (dB)
1
2
3
4
5
6
7
8
9
10
11
0,092
0,096
0,09
0,09
0,088
0,084
0,082
0,076
0,066
0,046
12
0,44
0,444
0,424
0,41
0,392
0,366
0,33
0,264
0,204
0,14
13
1,08
1,058
1,016
0,964
0,88
0,802
0,65
0,496
0,36
0,232
14
1,41
1,338
1,252
1,148
1,028
0,932
0,754
0,57
0,402
0,25
15
1,618
1,41
1,298
1,19
1,046
0,938
0,76
0,574
0,404
0,25
16
1,856
1,498
1,316
1,202
1,052
0,942
0,762
0,574
0,404
0,25
17
2,058
1,518
1,322
1,204
1,054
0,942
0,762
0,574
0,404
0,25
18
2,142
1,522
1,322
1,204
1,054
0,942
0,762
0,574
0,404
0,25
19
2,154
1,522
1,322
1,204
1,054
0,942
0,762
0,574
0,404
0,25
E.2
Tabel variasi
threshold
dengan histeresis adaptif terhadap parameter
tradeoff handoff
Metode Handoff
Parameter kontrol (dB)
Threshold Histeresis Panjang window rata-rata (drata-rata)
dB dB 0 10 20 30 0 10 20 30
Threshold dengan Histeresis
Adaptif
0 0 - 20 6,8676163 4,667727 1,0774011 -2,069107 0,0822433 0,0948237 0,1172143 0,1392398
1 0 - 20 6,8676163 4,667727 1,0774011 -2,069107 0,0822433 0,0948237 0,1172143 0,1392398
2 0 - 20 6,8676163 4,667727 1,0774011 -2,069107 0,0822433 0,0948237 0,1172143 0,1392398
3 0 - 20 6,8676163 4,667727 1,0774011 -2,069107 0,0822433 0,0948237 0,1172143 0,1392398
4 0 - 20 6,8676163 4,667727 1,0774011 -2,069107 0,0822433 0,0948237 0,1172143 0,1392398
5 0 - 20 6,8676163 4,667727 1,0774011 -2,069107 0,0822433 0,0948237 0,1172143 0,1392398
6 0 - 20 6,8676163 4,667727 1,0774011 -2,069107 0,0822433 0,0948237 0,1172143 0,1392398
7 0 - 20 6,8676163 4,667727 1,0774011 -2,069107 0,0822433 0,0948237 0,1172143 0,1392398
8 0 - 20 6,8676163 4,667727 1,0774011 -2,069107 0,0822433 0,0948237 0,1172143 0,1392398
9 0 - 20 6,8676163 4,667727 1,0774011 -2,069107 0,0822433 0,0948237 0,1172143 0,1392398
10 0 - 20 6,8734087 4,667727 1,0774011 -2,069107 0,0822038 0,0948237 0,1172143 0,1392398
11 0 - 20 6,9710363 4,667727 1,0774011 -2,069107 0,0815473 0,0948237 0,1172143 0,1392398
12 0 - 20 7,6459883 4,6920992 1,0774011 -2,069107 0,0770733 0,0946544 0,1172143 0,1392398
13 0 - 20 9,9749941 5,2031468 1,2372761 -2,0286394 0,0641159 0,0911352 0,116057 0,13894
14 0 - 20 14,057641 7,7101812 3,4966574 0,0068392 0,0464442 0,075767 0,1003584 0,1236767
15 0 - 20 16,649009 12,453207 8,4917372 4,9126156 0,0364267 0,0531029 0,0718672 0,0917571
16 0 - 20 16,672475 15,261013 12,959752 10,091388 0,034021 0,0410738 0,0511744 0,064492
17 0 - 20 16,685406 15,740785 14,638311 12,945466 0,0336476 0,0380421 0,0433204 0,0510287
18 0 - 20 16,687829 15,759327 14,831402 13,417384 0,0336188 0,0377172 0,0421479 0,0486873
19 0 - 20 16,688018 15,760647 14,833611 13,431314 0,0336181 0,0377007 0,0420905 0,0485907
E.2
Tabel variasi
threshold
dengan histeresis adaptif terhadap parameter
tradeoff handoff
(
lanjutan
).
Metode Handoff
Parameter kontrol (s)
Threshold Histeresis Panjang window rata-rata (drata-rata)
dB dB 0 10 20 30 0 10 20 30
Threshold dengan Histeresis
Adaptif
0 0 - 20 46,44 49,324 54,673 59,565 0 0 0 0
1 0 - 20 46,44 49,324 54,673 59,565 0 0 0 0
2 0 - 20 46,44 49,324 54,673 59,565 0 0 0 0
3 0 - 20 46,44 49,324 54,673 59,565 0 0 0 0
4 0 - 20 46,44 49,324 54,673 59,565 0 0 0 0
5 0 - 20 46,44 49,324 54,673 59,565 0 0 0 0
6 0 - 20 46,44 49,324 54,673 59,565 0 0 0 0
7 0 - 20 46,44 49,324 54,673 59,565 0 0 0 0
8 0 - 20 46,44 49,324 54,673 59,565 0 0 0 0
9 0 - 20 46,44 49,324 54,673 59,565 0 0 0 0
10 0 - 20 46,437 49,324 54,673 59,565 0,006 0 0 0
11 0 - 20 46,35 49,324 54,673 59,565 0,09 0 0 0
12 0 - 20 45,914 49,303 54,673 59,565 0,432 0,026 0 0
13 0 - 20 43,099 48,873 54,525 59,526 1,072 0,38 0,15 0,042
14 0 - 20 37,743 45,924 51,8 56,93 1,354 1,046 0,96 0,924
15 0 - 20 32,634 39,471 44,863 49,755 1,47 1,268 1,18 1,118
16 0 - 20 30,208 34,261 38,223 42,418 1,51 1,336 1,278 1,212
17 0 - 20 29,328 31,809 34,37 37,402 1,516 1,352 1,298 1,256
18 0 - 20 29,104 31,225 33,328 36,04 1,516 1,354 1,302 1,26
19 0 - 20 29,083 31,138 33,211 35,928 1,516 1,354 1,302 1,26
E.3
Tabel variasi
cost(c)
terhadap parameter
tradeoff handoff.
Metode Handoff
(dB)
Cost (c) Panjang window rata-rata (drata-rata)
0 10 20 30 0 10 20 30
suboptimal SDH
0,0045 18,501611 17,54692 14,415906 10,405911 0,0232584 0,0294301 0,0442783 0,0627928
0,007 18,502121 17,47932 14,176714 10,095516 0,0232614 0,0299007 0,0453777 0,0642897
0,01 18,50337 17,409111 13,951888 9,8546883 0,0232664 0,0304003 0,0463489 0,0654363
0,025 18,500551 17,120101 13,264951 9,0894095 0,0233059 0,0321025 0,0493726 0,0692726
0,04 18,489895 16,893943 12,834883 8,6505783 0,023372 0,0333109 0,0512823 0,0714699
0,06 18,477381 16,631148 12,385481 8,2246861 0,023477 0,03467 0,0532614 0,0736261
0,1 18,452572 16,177113 11,759957 7,6394962 0,0237792 0,0368374 0,0561691 0,076651
0,13 18,407589 15,88248 11,377523 7,3045637 0,0240602 0,0381875 0,0579294 0,0783882
0,25 18,253395 14,851831 10,243731 6,3336813 0,0256354 0,0425772 0,0632921 0,0836238
0,35 18,007947 13,981568 9,5366081 5,7209216 0,0277758 0,0463394 0,0666421 0,087054
0,45 17,535476 13,168619 8,8736621 5,1929781 0,030615 0,0497003 0,0699099 0,0901102
0,55 16,63465 12,30827 8,2251799 4,6483294 0,0350261 0,0535365 0,0731716 0,0933378
0,65 15,283931 11,461763 7,5618372 4,094917 0,0408361 0,0572847 0,0765925 0,0966953
0,75 13,201056 10,450927 6,8268915 3,4747787 0,0495151 0,0619456 0,0806491 0,1004812
0,85 10,69099 9,215791 5,8921909 2,7514907 0,0608225 0,0679318 0,0858835 0,1050789
E.3
Variasi
cost(c)
terhadap parameter
tradeoff handoff
(lanjutan).
Metode Handoff
(s)
Cost (c) Panjang window rata-rata (drata-rata)
0 10 20 30 0 10 20 30
suboptimal SDH
0,0045 25,257 28,317 35,454 41,785 6,02 1,584 1,316 1,214
0,007 25,262 28,677 35,897 42,251 5,796 1,564 1,312 1,21
0,01 25,24 29,095 36,309 42,633 5,524 1,546 1,308 1,204
0,025 25,238 30,168 37,547 43,873 4,426 1,492 1,296 1,19
0,04 25,278 30,876 38,305 44,528 3,82 1,456 1,28 1,186
0,06 25,267 31,684 39,052 45,135 3,254 1,42 1,27 1,18
0,1 25,309 32,797 40,124 45,974 2,466 1,384 1,246 1,166
0,13 25,569 33,428 40,722 46,43 2,196 1,37 1,24 1,16
0,25 26,541 35,214 42,444 47,788 1,65 1,312 1,2 1,14
0,35 27,925 36,883 43,407 48,641 1,48 1,278 1,188 1,13
0,45 29,802 38,128 44,364 49,354 1,37 1,244 1,178 1,12
0,55 31,982 39,596 45,236 50,21 1,302 1,218 1,162 1,11
0,65 34,834 40,831 46,118 51,05 1,25 1,198 1,148 1,092
0,75 38,264 42,241 47,217 51,957 1,152 1,174 1,13 1,078
0,85 42,175 43,884 48,554 53,017 1,02 1,148 1,108 1,068
E.4
Variasi
threshold
dengan histeresis 1 dB terhadap parameter
tradeoff handoff.
Metode Handoff
Parameter kontrol (dB)
Threshold Histeresis Panjang window rata-rata ( drata-rata)
dB dB 0 10 20 30 0 10 20 30
Thresholddengan Histeresis 1 dB
1 1 6,8740968 4,6651921 1,0774011 -2,069107 0,0821895 0,0948358 0,1172143 0,1392398
2 1 6,8740968 4,6651921 1,0774011 -2,069107 0,0821895 0,0948358 0,1172143 0,1392398
3 1 6,8740968 4,6651921 1,0774011 -2,069107 0,0821895 0,0948358 0,1172143 0,1392398
4 1 6,8740968 4,6651921 1,0774011 -2,069107 0,0821895 0,0948358 0,1172143 0,1392398
5 1 6,8740968 4,6651921 1,0774011 -2,069107 0,0821895 0,0948358 0,1172143 0,1392398
6 1 6,8740968 4,6651921 1,0774011 -2,069107 0,0821895 0,0948358 0,1172143 0,1392398
7 1 6,8740968 4,6651921 1,0774011 -2,069107 0,0821895 0,0948358 0,1172143 0,1392398
8 1 6,8740968 4,6651921 1,0774011 -2,069107 0,0821895 0,0948358 0,1172143 0,1392398
9 1 6,8740968 4,6651921 1,0774011 -2,069107 0,0821895 0,0948358 0,1172143 0,1392398
10 1 6,8798892 4,6651921 1,0774011 -2,069107 0,08215 0,0948358 0,1172143 0,1392398
11 1 6,9775168 4,6651921 1,0774011 -2,069107 0,0814919 0,0948358 0,1172143 0,1392398
12 1 7,6593732 4,6895643 1,0774011 -2,069107 0,0769889 0,0946665 0,1172143 0,1392398
13 1 10,08691 5,2050132 1,2372761 -2,0286394 0,0634766 0,0911447 0,116057 0,13894
14 1 14,965543 7,7503549 3,50275 0,0068956 0,0425408 0,0755766 0,100316 0,1236828
15 1 18,341899 12,72034 8,5102385 4,9060987 0,0293935 0,0518705 0,0717679 0,0918386
16 1 18,426698 16,101891 12,938402 9,6346243 0,0248963 0,0370519 0,0509243 0,0666524
17 1 18,453418 16,795701 14,487856 11,641062 0,0240519 0,0325859 0,0435509 0,0569637
18 1 18,460191 16,830171 14,632047 11,863179 0,0239546 0,0320101 0,0426404 0,0558651
19 1 18,461125 16,831739 14,633306 11,86811 0,0239507 0,0319924 0,0426068 0,055831
E.4
Variasi
threshold
dengan histeresis 1 dB terhadap parameter
tradeoff handoff
(lanjutan).
Metode Handoff
Parameter kontrol (s)
Threshold Histeresis Panjang window rata-rata (drata-rata)
dB dB 0 10 20 30 0 10 20 30
Thresholddengan Histeresis 1 dB
1 1 46,557 49,332 54,673 59,565 0 0 0 0
2 1 46,557 49,332 54,673 59,565 0 0 0 0
3 1 46,557 49,332 54,673 59,565 0 0 0 0
4 1 46,557 49,332 54,673 59,565 0 0 0 0
5 1 46,557 49,332 54,673 59,565 0 0 0 0
6 1 46,557 49,332 54,673 59,565 0 0 0 0
7 1 46,557 49,332 54,673 59,565 0 0 0 0
8 1 46,557 49,332 54,673 59,565 0 0 0 0
9 1 46,557 49,332 54,673 59,565 0 0 0 0
10 1 46,554 49,332 54,673 59,565 0,006 0 0 0
11 1 46,467 49,332 54,673 59,565 0,092 0 0 0
12 1 46,005 49,311 54,673 59,565 0,44 0,026 0 0
13 1 42,963 48,872 54,525 59,526 1,08 0,378 0,15 0,042
14 1 36,166 45,883 51,806 56,932 1,41 1,038 0,964 0,924
15 1 30,094 39,053 44,84 49,774 1,618 1,232 1,168 1,108
16 1 26,65 32,415 37,82 42,729 1,856 1,3 1,24 1,172
17 1 25,62 28,98 34,042 38,897 2,058 1,32 1,25 1,186
18 1 25,357 28,055 33,205 38,229 2,142 1,326 1,252 1,186
19 1 25,284 27,976 33,145 38,2 2,154 1,326 1,252 1,186
E.5
Tabel variasi metode
handoff
terhadap parameter
tradeoff handoff.
Metode Handoff
Parameter kontrol (dB) (s)
Threshold Histeresis Panjang window rata-rata (drata-rata)
dB dB 0 10 20 30 0 10 20 30 0 10 20 30 0 10 20 30
Threshold
dengan histeresis
1 dB
13 1
10,08691 5,2050132 1,2372761
-2,0286394 0,0634766 0,0911447 0,116057 0,13894 42,963 48,872 54,525 59,526 1,08 0,378 0,15 0,042
14 1 14,965543 7,7503549 3,50275 0,0068956 0,0425408 0,0755766 0,100316 0,1236828 36,166 45,883 51,806 56,932 1,41 1,038 0,964 0,924
15 1 18,341899 12,72034 8,5102385 4,9060987 0,0293935 0,0518705 0,0717679 0,0918386 30,094 39,053 44,84 49,774 1,618 1,232 1,168 1,108
16 1 18,426698 16,101891 12,938402 9,6346243 0,0248963 0,0370519 0,0509243 0,0666524 26,65 32,415 37,82 42,729 1,856 1,3 1,24 1,172
17 1 18,453418 16,795701 14,487856 11,641062 0,0240519 0,0325859 0,0435509 0,0569637 25,62 28,98 34,042 38,897 2,058 1,32 1,25 1,186
18 1 18,460191 16,830171 14,632047 11,863179 0,0239546 0,0320101 0,0426404 0,0558651 25,357 28,055 33,205 38,229 2,142 1,326 1,252 1,186
Threshold
dengan histeresis
2 dB
13 2 10,134314 5,4096449 1,4684761 -1,760692 0,0631969 0,0896 0,114278 0,1368451 43,022 49,055 54,813 59,735 1,058 0,38 0,15 0,042
14 2 14,869976 7,7507458 3,4904555 0,006754 0,042924 0,0755417 0,1003773 0,1236913 36,166 45,914 51,951 57,055 1,338 1,016 0,956 0,918
15 2 17,857631 12,323164 8,1957816 4,6679322 0,0307597 0,053535 0,0735273 0,0934663 30,293 39,376 45,125 50,114 1,41 1,184 1,126 1,072
16 2 17,94635 14,939331 11,599628 8,3454247 0,0269969 0,0419812 0,0572282 0,0737491 26,937 34,063 39,625 44,593 1,498 1,222 1,156 1,108
17 2 17,968336 15,361311 12,429923 9,3644221 0,026349 0,0393189 0,0532669 0,0689192 25,872 31,825 37,507 42,745 1,518 1,226 1,158 1,11
18 2
17,972457 15,375589 12,472805 9,4223065 0,0262906 0,0391054 0,0529773 0,0686182 25,655 31,502 37,235 42,568 1,522 1,226 1,158 1,11
Threshold
dengan histeresis
3 dB
13 3 10,074502 5,3990748 1,467932 -1,760692 0,0635148 0,0896648 0,1142815 0,1368451 43,06 49,055 54,813 59,735 1,016 0,37 0,148 0,042
14 3
14,406112 7,5920795 3,4243721
-0,0400692 0,0447673 0,0764802 0,1008603 0,1240622 36,717 46,121 52,018 57,124 1,252 0,968 0,924 0,902
15 3 17,058269 11,465322 7,5763367 4,0718169 0,0338282 0,0576204 0,0771011 0,0974527 31,249 40,337 45,966 50,984 1,298 1,1 1,066 1,03
16 3 17,16376 13,256258 9,8562451 6,4707441 0,0308751 0,0496321 0,0661774 0,0847036 28,49 36,669 42,287 47,437 1,316 1,124 1,074 1,046
17 3 17,182874 13,461103 10,221668 6,8685581 0,0304185 0,0483673 0,0644254 0,082869 27,774 35,591 41,414 46,748 1,322 1,124 1,074 1,046
