TITLE: PERFORMANCE OF DIGITAL COMMUNICATION SYSTEM CORRUPTED BY NOISE.
OBJECTIVES
1. To study the perfor performa mance nce of digital digital communi communicati cation on system system when it is corrup corrupted ted by noise. 2. To study the performance of digital communication system when it is under the
influence of Inter-symbol Interface (ISI) only. on ly. 3. To study the performance of digital communication system when it is both under the
influence of Inter-symbol Interference (ISI) and corrupted by noise.
PROCEDURES Part 1: A basic digital communication system that transmits an Amplitude Shift Keying Signal (ASK) 1. In part 1(a) The purpose of the three function files which represents a basic digital
communication system that transmits an Amplitude Shift Keying (ASK) is explained. a) test_noise b) binseq_tx c) bin binseq_det det
2. In Part 1 (b) (b) the main main specificat specifications ions for the the ASK signal signal in the the main file file is identifie identified d a) Bit rate b) Sampling frequency c) Volt Voltag agee ampl amplit itud udee d) Numbe Numberr of bit bitss in a packe packett e) Numb Number er of pack packet etss
3. In Part 1 (c), two M-files missing function is developed from the list before they can
be executed. a) A function function to generate generate bytes bytes of pseudor pseudorandom andom binary binary sequence sequence b) A Q-function
4. In Part 1 (d) (d) , Using the the two functions functions develope developed d in the previous previous procedure procedure , Matlab Matlab programs is executed and tabulated its values following the parameters mentioned. a) Volt Voltag agee ampl amplit itud udee b) Sampling frequency c) Bit rate d) Bit error e) Pack Packet et err error f) Number Number of of bits bits for for the the whole whole tran transmi smissi ssion on g) Theo Theore reti tica call BER BER h) Meas Measur ured ed BER BER i) Meas Measur ured ed pack packet et err error or rat ratee (PER (PER))
5. In Part 1 (e) (e) , the previous previous step step then repeated repeated by varying varying the the following following paramete parameters. rs. a) Voltage Voltage amplitude, amplitude, A=2,3,4 A=2,3,4 and 5 volts. volts. Sampling Sampling frequency frequency=10 =10 and bit rate rate =1. b) Sampling frequency, fsamp=2,6,14 and 20Hz. Voltage amplitude=1 and bit rate =1. c) Bit rate rate = 2,3,4 and 5 bits/s bits/sec. ec. voltage voltage amplitude amplitude = 1 and sampli sampling ng frequency frequency =10.
6. In Part Part 1 (f)(i (f)(i)) , BER graph agains againstt each of the varyi varying ng paramete parameters rs in Part 1 (e) is plotted for both theoretical and measured BER’s.
7. In Part Part 1 (f)( (f)(ii ii)) , BER BER graph graph again against st SNR(d SNR(dB) B) is plotte plotted d for for each of the the varyi varying ng parameters in Part 1 (e) for theoretical and measured BER’s
Part 2: Performance of digital communication system under the influence of Inter-symbol Interference (ISI) only.
8. In Part Part 2 (1), (1), under under the influe influence nce of Inters Intersym ymbol bol Interf Interfere erence nce (ISI) (ISI) the syste systems ms
performance is evaluated without the noise and the altered part of the programs is indicated.
9. In Part 2 (a), steps in Part 1 (d),(e),and (f) is repeated and results is commented.
Part 3: Performance of digital communication system under the influence of Inter-symbol Interference (ISI) with corrupted by noise.
10. In Part 3 (a), the systems performance again is considered under the influence of
Intersymbol Interference and modified program is identified.
11. In Part 3 (b), steps in Part 1 (d),(e),and (f) is repeated and results is commented.
12. The overall results obtained from Part 1 to P art 3 are contrast and compared.
Coding 1. Codi Coding ng for for tes test_ t_no nois ise: e: %
Program to test the BER and packet-error rate for binary sequences.
function test_noise() A=1
fsamp=10 bit_rate=1 npack=1000; ndelay=0; knoise=0.9; Loop=10; h = [0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0];
%ISI problem
bit_error=0; packet_error=0; energy_bit=(A^2)*fsamp/bit_rate; power_noise=knoise^2; N0=power_noise*bit_rate/fsamp; gamma=(A^2)/(N0); SNR=energy_bit/power_noise; SNR_dB=10*log10(SNR) BER_theory=Q_function(sqrt(gamma)); for l=1:Loop s0=rand_seq1(npack); %s0
%Generate sequence
y=binseq_tx(fsamp,bit_rate,s0); %transmitted signal %y % introduce ISI y = filter(h,1,y); y=A*y; y_lng=length(y); %y_lng ns=randn(1,y_lng); for k=1:y_lng y0(k)=y(k)+knoise*ns(k); end %y0
%Signal + noise
[s1]=binseq_det(fsamp,bit_rate,y0,ndelay); using Matched Filter %s0 transmitted and detected data %s1 %Calculate number of error % k=1; ctr_bit_error=0; ctr_packet_error=0; while (k<=length(s0)) if s0(k)~=s1(k) ctr_bit_error=ctr_bit_error+1; ctr_packet_error=1; end k=k+1; end
%decode received signal %Use to observe
bit_error=bit_error+ctr_bit_error; packet_error=packet_error+ctr_packet_error; end bit_error packet_error Total_bits=Loop*npack BER_theory BER_measured=bit_error/Total_bits PER_measured=packet_error/Loop
2. Coding for binseq_text: % % % % % %
Fungsi di bawah adalah untuk mendapatkan sequence bagi ASK Beberapa variable yang perlu dimasukkan pada main MATLAB ialah Frekuensi sampling, signal frekuensi, bit-rate dan sequence Berikut adalah contohnya : >> s=[1 0 1 1 0] >> x=binseq1(8000,100,s)
function [x]=binseq_tx(fs,b,s) a=1; % a mewakili amplitud Tb=1/b; % bit-duration ns=Tb*fs; num_s=length(s); % untuk menentukan baris dan lajur sequence yang diberi num_t=ns*num_s; ctr=1; sctr=1; while(sctr<=num_s) while (sctr<=num_s) if s(sctr)==1 % apabila s=1, arahan berikut akan dibuat for k=ctr:ctr+ns x(k)=a; end else for k=ctr:ctr+ns x(k)=-a; end end ctr=ctr+ns; sctr=sctr+1; end
3. Codin Coding g for for binse binseq_ q_det det:: % %
Function to implement coherent ASK detection for 1 packet of chosen length.
function [s]=binseq_det(fsamp,bit_rate,x,ndelay) Nbit=round(fsamp/bit_rate); Npack=length(x); x0=zeros(1,2*Npack);
sig0=zeros(1,2*Npack); sig1=zeros(1,2*Npack); x0_det=zeros(1,2*Npack); x1_det=zeros(1,2*Npack); s=zeros(1,round(Npack/Nbit)); for k=1:Npack x0(k)=x(k); end %
Generate subcarriers at f1. %
sig0(1:Npack)=-1; sig1(1:Npack)=1; %
Multiply the subcarriers with received signal.
%
for k=1:Npack x0_det(k)=x0(k)*sig0(k); x1_det(k)=x0(k)*sig1(k); end %subplot(211),plot(x0_det); %subplot(212),plot(x1_det); %
Detect transmitted sequence.
ptr0=1; ptr1=1; ctr0=1; for k=1:Npack x20(ptr0)=x0_det(k); x21(ptr0)=x1_det(k); if (ptr0==Nbit) sum21=sum(x20)-sum(x21); duration. s21(ctr0)=sum21; ctr0=ctr0+1; ptr0=0; if sum21>0 % s(ptr1)=0; else s(ptr1)=1; end s(ptr1); ptr1=ptr1+1; sum21=0; end ptr0=ptr0+1; end %
%
%
Sum prod x20-x21
Detect '0' bit %
Detect '1' bit
For diagnostic purposes, the difference in correlation
for k=1:ptr1-1 s_diff(k)=s21(k); end s_diff';
within a bit-
4. Codin Coding g for for test_ test_noi noise_ se_ISI ISI % %
Program to test the BER and packet-error rate for binary sequences. function test_noise_ISI
function test_noise_ISI() A=1 fsamp=12 bit_rate=4 npack=1000; ndelay=0; knoise=0.9; Loop=10; h = [1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0];
%ISI problem
bit_error=0; packet_error=0; energy_bit=(A^2)*fsamp/bit_rate; power_noise=knoise^2; N0=power_noise*bit_rate/fsamp; gamma=(A^2)/(N0); SNR=energy_bit/power_noise; SNR_dB=10*log10(SNR) BER_theory=Q_function(sqrt(gamma)); for l=1:Loop s0=rand_seq1(npack); %s0
%Generate sequence
y=binseq_tx(fsamp,bit_rate,s0); %transmitted signal %y % introduce ISI y = filter(h,1,y); y=A*y; y_lng=length(y); %y_lng ns=randn(1,y_lng); for k=1:y_lng y0(k)=y(k)+knoise*ns(k); end %y0
%Signal + noise
[s1]=binseq_det(fsamp,bit_rate,y0,ndelay); using Matched Filter %s0 transmitted and detected data %s1 %Calculate number of error
%
%decode received signal %Use to observe
k=1; ctr_bit_error=0; ctr_packet_error=0; while (k<=length(s0)) if s0(k)~=s1(k) ctr_bit_error=ctr_bit_error+1; ctr_packet_error=1; end k=k+1; end bit_error=bit_error+ctr_bit_error; packet_error=packet_error+ctr_packet_error; end bit_error packet_error Total_bits=Loop*npack BER_theory BER_measured=bit_error/Total_bits PER_measured=packet_error/Loop
5. Coding for Plotting BER versus Varying ParameterGraph:
% Graph plotting for Varying Parameter for Amplitude, Frequency & Bit Rate x=1:5; y=[2.2100e-004
1.0530e-012 2.7973e-026 3.6111e-045 2.1579e-069];
subplot(3,1,1); plot(x,y,'-ro' plot(x,y, '-ro', ,'linewidth' 'linewidth',2); ,2); axis([0 6 -1e-4 3e-4 ]) title('BER title('BER versus Amplitude Graph', Graph' ,'FontWeight' 'FontWeight', ,'bold' 'bold', ,'horizontalAlignment' , 'center' 'center') ) xlabel('Voltage xlabel( 'Voltage Amplitude,A /V' ,'Fontsize' 'Fontsize',8) ,8) ylabel('Bit ylabel( 'Bit Error Rate, BER') BER' ) grid on
x1=[2 6 10 20 24]; y1=[0.0581 0.0032 2.2100e-004 1.6095e-005 3.3643e-007]; subplot(3,1,2); plot(x1,y1,'-bo' plot(x1,y1, '-bo', ,'linewidth' 'linewidth',2); ,2); axis([0 25 -0.05 0.1]) title('BER title('BER versus Frequency Graph', Graph' ,'FontWeight' 'FontWeight', ,'bold' 'bold', ,'horizontalAlignment' , 'center' 'center') ) xlabel('Frequency xlabel( 'Frequency Sampling,fsamp /Hz' ,'Fontsize' 'Fontsize',8) ,8) ylabel('Bit ylabel( 'Bit Error Rate, BER') BER' ) grid on y2=[2.2100e-004 0.0065 0.0131 0.0271 0.0581]; subplot(3,1,3); plot(x,y2,'-go' plot(x,y2, '-go', ,'linewidth' 'linewidth',2); ,2); axis([0 6 -0.01 0.07]) title('BER title('BER versus Bit Rate Graph', Graph' ,'FontWeight' 'FontWeight', ,'bold' 'bold', ,'horizontalAlignment' , 'center' 'center') ) xlabel('Bit xlabel( 'Bit Rate, /bps', /bps' ,'Fontsize' 'Fontsize',8) ,8) ylabel('Bit ylabel( 'Bit Error Rate, BER') BER' ) grid on
6. Coding for Plotting BER versus SNR(dB)Graph for Varying Parameter: Parameter: %Graph plotting for BER(theoretical, measured) versus SNR(db) x=[10.9151 16.9357 20.4576 22.9563 24.8945]; y=[2.2100e-004 1.0530e-012 2.7973e-026 3.6111e-045 2.1579e-069]; y1=[0.0420 0.0038 3.0000e-004 0 0]; subplot(3,1,1); plot(x,y,'-ro' plot(x,y, '-ro', ,'linewidth' 'linewidth',2); ,2); hold on plot(x,y1,'-bo' plot(x,y1, '-bo', ,'linewidth' 'linewidth',2); ,2); title('BER title('BER versus SNR(dB)Graph for Varying Amplitude', Amplitude' ,'FontWeight' 'FontWeight', ,'bold' 'bold', ,'horizontalAlignment' , 'center' 'center') ) xlabel('SNR xlabel( 'SNR (dB)', (dB)' ,'Fontsize' 'Fontsize',8) ,8) ylabel('Bit ylabel( 'Bit Error Rate, BER') BER' ) legend('Theoretical legend( 'Theoretical BER', BER' ,'Measured BER') BER' ) axis([10 26 -0.01 0.05]) grid on
x1=[3.9254 8.6967 10.9151 12.3764 13.9254]; y1=[0.0581 0.0032 2.2100e-004 1.6095e-005 3.3643e-007]; y2=[0.1735 0.1488 0.0425 9.0000e-004 0]; subplot(3,1,2); plot(x1,y1,'-ro' plot(x1,y1, '-ro', ,'linewidth' 'linewidth',2); ,2); hold on plot(x1,y2,'-bo' plot(x1,y2, '-bo', ,'linewidth' 'linewidth',2); ,2); title('BER title('BER versus SNR(dB)Graph for Varying Frequency', Frequency' ,'FontWeight' 'FontWeight', ,'bold' 'bold', ,'horizontalAlignment' , 'center' 'center') ) xlabel('SNR xlabel( 'SNR (dB)', (dB)' ,'Fontsize' 'Fontsize',8) ,8) ylabel('Bit ylabel( 'Bit Error Rate, BER') BER' ) legend('Theoretical legend( 'Theoretical BER', BER' ,'Measured BER') BER' ) axis([3 15 -0.1 0.2]) grid on x2=[10.9151 7.9048 6.1439 4.8945 3.9254]; y3=[2.2100e-004 0.0065 0.0131 0.0271 0.0581]; y4=[0.0413 0.1310 0.1484 0.1233 0.0870]; subplot(3,1,3); plot(x2,y3,'-ro' plot(x2,y3, '-ro', ,'linewidth' 'linewidth',2); ,2); hold on plot(x2,y4,'-bo' plot(x2,y4, '-bo', ,'linewidth' 'linewidth',2); ,2); title('BER title('BER versus SNR(dB)Graph for Varying Frequency', Frequency' ,'FontWeight' 'FontWeight', ,'bold' 'bold', ,'horizontalAlignment' , 'center' 'center') ) xlabel('SNR xlabel( 'SNR (dB)', (dB)' ,'Fontsize' 'Fontsize',8) ,8) ylabel('Bit ylabel( 'Bit Error Rate, BER') BER' ) legend('Theoretical legend( 'Theoretical BER', BER' ,'Measured BER') BER' ) axis([3 11 -1e-2 0.16]) grid on
RESULT Part 1: Basic transmission
A) Funct Functio ion n Files Files i. ii. iii.
Test_noise = to test the BER and packet-error rate for binary sequences. Binseq_text = to get the sequence for ASK Binseq_det = to implement coherent ASK detection for 1 packet
B) Main Main speci specifi ficati cations ons.. i. Bit Bit Rate Rate = 1 bits bits/s /sec ec ii.
Sampling fr frequency, cy, fs fsamp = 10 Hz Hz
iii.
Voltage Am Amplitude, A = 1V 1V
iv.
Num Number ber of of bit bits in a pack packet et = 1000 1000 bit bits
v.
Number of of pa packets = 10 pa packets
C) 1. Pseudorandom Binary sequence Coding
%
Function to generate a byte of pseudorandom binary sequence
function x=rand_seq1(npack) x0=rand(1,npack); for k=1:npack if x0(k)>0.5 x(k)=1; else x(k)=0; end end
2. Q-Function Coding %
An approximation for the Q function, Gaussian distribution.
function [y]=Q_function(x) y=qfunc(x);
Varying the following parameter, knoise = 0 h = [0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0];
1) Volt Voltag agee Amp Ampli litu tude, de, A
PARAMETER
Voltage Amplitude, (V) Sampling Frequency,(Hz) Bit Rate (Bits/sec)
VALUES
1 10 1
2 10 1
3 10 1
4 10 1
5 10 1
SNR (dB) 10.9151 16.9357 20.4576 22.9563 Bit Error 3 0 0 0 Packet Error 2 0 0 0 Total Bits 10000 10000 10000 10000 Theoretical BER 2.2100e-4 1.0530e-12 2.7973e-26 3.6111e-45 Measured BER 3.0000e-4 0 0 0 PER 0.2000 0 0 0 Table 1: Varying the Following Parameter for Voltage Amplitude
24.8945 0 0 10000 2.1579e-69 0 0
2) Sampli Sampling ng frequen frequency, cy, fsamp fsamp
PARAMETER
VALUES
Voltage Amplitude, (V) Sampling Frequency,(Hz) Bit Rate (Bits/sec) SNR (dB)
1 1 1 1 1 2 6 10 14 20 1 1 1 1 1 3.925 8.696 10.9151 12.3764 13.9254 4 7 Bit Error 543 31 2 0 0 Packet Error 10 10 2 0 0 Total Bits 10000 10000 10000 10000 10000 Theoretical BER 0.058 0.003 2.21 2.2100 00ee-00 004 4 1.60 1.6095 95ee-00 005 5 3.36 3.3643 43ee-00 007 7 1 2 Measured BER 0.054 0.003 2.0000e-004 0 0 3 1 PER 1 1 0.2000 0 0 Table 2: Varying the Following Parameter for Sampling Frequency
3) Bit Rate
PARAMETER
Voltage Amplitude, (V) Sampling Frequency,(Hz) Bit Rate (Bits/sec) SNR (dB)
VALUES
1 10 1 10.9151
1 10 2 7.904 8
1 12 3 6.143 9
1 12 4 4.894 5
1 10 5 3.9254
Bit Error Packet Error Total Bits Theoretical BER
2 2 10000 2.2100e-004
65 144 261 585 10 10 10 10 10000 10000 10000 10000 0.006 0.013 0.027 0.0581 5 1 1 Measured BER 2.0000e-004 0.006 0.014 0.026 0.0585 5 4 1 PER 0.2000 1 1 1 1 Table 3: Varying the Following Parameter for Bit Rate
Figure 1: BER versus Varying Parameter
Figure 2: BER (Theoretically, measured) Versus SNR (dB)
Comment: 1.
In figure 1, when amplitude and frequency increasing, the bit error rate (BER) has decreasing exponentially approximate to zero. But for the changing in the bit rate, the bit error rate (BER) increasing.
2. In figure 2, 2, BER versus versus SNR graph shows shows that that all varying varying parameters parameters for both theory and measured are almost the same.
Part 2: Under the Influence of Inter-Symbol Interference (ISI) only.
Varying the following parameter, knoise = 0 h = [1 0 0 0 1/2 0 0 0 1/2 0 0 0 0 1/2 0 0];
1) Volt Voltag agee Amp Ampli litu tude, de, A PARAMETER
Voltage Amplitude, (V) Sampling Frequency, (Hz) Bit Rate (Bits/sec) SNR (dB) Bit Error Packet Error Total Bits
VALUES
1 10
2 10
3 10
4 10
5 10
1 1 1 1 1 ∞ ∞ ∞ ∞ ∞ 0 0 0 0 0 0 0 0 0 0 1000 1000 1000 1000 10000 0 0 0 0 Theoretical BER 0 0 0 0 0 Measured BER 0 0 0 0 0 PER 0 0 0 0 0 Table 4: Varying the Following Parameter for Voltage Amplitude
2) Sampli Sampling ng frequen frequency, cy, fsamp fsamp
PARAMETER
Voltage Amplitude, (V) Sampling Frequency,(Hz) Bit Rate (Bits/sec) SNR (dB) Bit Error Packet Error Total Bits
VALUES
1 1 1 1 1 2 6 10 14 20 1 1 1 1 1 ∞ ∞ ∞ ∞ ∞ 0 0 0 0 0 0 0 0 0 0 1000 1000 1000 1000 10000 0 0 0 0 Theoretical BER 0 0 0 0 0 Measured BER 0 0 0 0 0 PER 0 0 0 0 0 Table 5: Varying the Following Parameter for Sampling Frequency
3) Bit Rate
PARAMETER
VALUES
Voltage Amplitude, (V) Sampling Frequency,(Hz) Bit Rate (Bits/sec) SNR (dB) Bit Error Packet Error Total Bits
1 1 1 1 1 10 10 10 10 10 1 2 3 4 5 ∞ ∞ ∞ ∞ ∞ 0 0 0 0 0 0 0 0 0 0 1000 1000 1000 1000 10000 0 0 0 0 Theoretical BER 0 0 0 0 0 Measured BER 0 0 0 0 0 PER 0 0 0 0 0 Table 6: Varying the Following Parameter for Bit Rate
Figure 3: BER versus Varying Parameter
Figure 4: BER (Theoretically, measured) Versus SNR (dB)
Comment: 1.
In figure 1, all BER for all varying parameter have same value that is zero because there are no noise introduce in the signal.
2.
In figure 2, all BER for theoretical and measured have same value that is zero because there are no noises introduce in the signal and produce SNR infinity.
Part 3: Under the Influence of Inter-symbol Interference (ISI) With Corrupted By Noise.
Varying the following parameter, knoise = 0.9 h = [1 0 0 0 1/2 0 0 0 1/2 0 0 0 0 1/2 0 0];
1) Volt Voltag agee Amp Ampli litu tude, de, A PARAMETER
VALUES
Voltage Amplitude, (V) 1 2 3 4 Sampling Frequency,(Hz) 10 10 10 10 Bit Rate (Bits/sec) 1 1 1 1 SNR (dB) 10.9151 16.9357 20.4576 22.9563 Bit Error 420 38 0 0 Packet Error 10 1 0 0 Total Bits 10000 10000 10000 10000 Theoretical BER 2.2100e-004 1.0530e-012 2.7973e-026 3.6111e-045 Measured BER 0.0420 0.0038 3.0000e-004 0 PER 1 0.8000 0.3000 0 Table 7: Varying the Following Parameter for Voltage Amplitude
5 10 1 24.8945 0 0 10000 2.1579e-069 0 0
2) Sampli Sampling ng frequen frequency, cy, fsamp fsamp
PARAMETER
VALUES
Voltage Amplitude, (V) 1 1 1 1 Sampling Frequency,(Hz) 2 6 10 14 Bit Rate (Bits/sec) 1 1 1 1 SNR (dB) 3.9254 8.6967 10.9151 12.3764 Bit Error 1735 1488 425 9 Packet Error 10 10 10 6 Total Bits 10000 10000 10000 10000 Theoretical BER 0.0581 0.0032 2.2100e-004 1.6095e-005 Measured BER 0.1735 0.1488 0.0425 9.0000e-004 PER 1 1 1 0.6000 Table 8: Varying the Following Parameter for Sampling Frequency
1 20 1 13.9254 0 10 10000 3.3643e-007 0 0
3) Bit Rate
PARAMETER
Voltage Amplitude, (V) Sampling Frequency,(Hz) Bit Rate (Bits/sec) SNR (dB)
VALUES
1 10 1 10.9151
1 1 1 1 10 12 12 10 2 3 4 5 7.904 6.935 4.894 3.9254 8 7 5 Bit Error 413 1303 1484 1233 870 Packet Error 10 10 10 10 10 Total Bits 10000 10000 10000 10000 10000 Theoretical BER 2.2100e-004 0.006 0.013 0.027 0.0581 5 1 1 Measured BER 0.0413 0.131 0.148 0.123 0.0870 0 4 3 PER 1 1 1 1 1 Table 9: Varying the Following Parameter for Bit Rate
Figure 5: BER versus Varying Parameter
Figure 6: BER (Theoretically, measured) Versus SNR (dB)
Comment: 1.
In figure 1, when amplitude and frequency increasing, the bit error rate (BER) has decreasing exponentially approximate to zero. But for the changing in the bit rate, the bit error rate (BER) increasing. It’s because this part using BER theory where it is not affected by Influence of Inter-symbol Interference (ISI).
2.
In figure 2, BER versus SNR graph shows that all varying parameters for both theory and measured are not the same because the measured BER not affected by Influence of Inter-symbol Interference (ISI).
DISCUSSION:
1. In this lab lab session session students students were introduce introduced d on how measures measures the performanc performancee for a digital system corrupted by noise using the Matlab system. The performances of a digital system have probability of error of the output signal in communications systems.
2. Noise Noise is corrupte corrupted d multip multiplic licati ative ve in the process process of being transm transmitt itted ed from the channel due to turbulence in the air reflection and refractions. So, it limits ability to communicate. If the noise is increasing, the output signal will become error.
3. In transmis transmission sion of communi communicatio cation n signal, signal, the channel channel bandwidth bandwidth is require required. d. The receiver input consists of the transmitted signal plus channel noise. For baseband signaling, the processing circuit in the receiver consists of low-pass filtering with appropriate amplification.
4. From this this lab session session as well it is learned learned that in in Amplitude Amplitude Shift Shift Keying Keying (ASK). It is a form form of modu modula lati tion on that that repr repres esen ents ts digi digita tall data data as vari variat atio ions ns in the the amplitude of a carrier wave. With running all there M-file coding, the value of bit rate rate sampli sampling ng frequen frequency, cy, voltag voltagee amplit amplitude ude,, number number of bits bits in a packet packet and number of packet will measured.
5. Durin During g exper experim imen entt runs runs,, all all the the codi coding ng must save save in same same fold folder er.. If not, the measure value can’t get the value almost with the theory value.
6. In part part 1 (e), (e), the value value of frequenc frequency y samplin sampling g for bit 3 and bit 4 has been change change to 12 in test_noise command because the value measure must become an integer number. If the value of bit 3 & bit 4 is not changing, the value measures have become to decimal number and make additional error in Binseq_tx coding file.
7. In part part 2, the value value of bit rate become become to infini infinity ty (∞). (∞). With using using influe influence nce of Inter-sysmbol Interference (ISI), Knoise = 0 and h=(10001/2 0001/2 001/2 ). Inter-symbol Interference is not affect the bit error. So the noise becomes equal to zero (0).
8. In part 3, the value value of error is increa increasin sing. g. That becaus becausee when the Inter-s Inter-sym ymbol bol Interf Interfere erence nce (ISI) (ISI) was corrup corrupted ted by noise, noise, the tail tail of energy energy was create created d in tran transm smis issi sion on medi medium um.. The The ener energy gy has has been been inte interf rfer eres es with with one one or more more subsequent symbol as Figure 1 in below. In receiver, the value the particular symbol is more susceptible to noise and incorrect interpretation.
Figure 7: Symbol is spread by the medium
9. To reduce the the noise in in transmissi transmission, on, the frequency frequency must must be increasin increasing g to make the bit rate be reducing. For to mitigate the detrimental effect of ISI, the band limited pulse which minimize the effect of ISI and channel impulse response has been cancel the ISI introduced in filter the receiver signal.
10. 10. By compar comparin ing g all all the the resu result lt,, part part 2 syst system em that that only only ISI ISI has a much much bett better er performance compare to the system with under influence noise.
CONCLUSION:
In this lab session, students were given a brief introduction towards the coding of Matlab Based Function and from here students were needed to alter this coding to solve problems given in the exercises of lab sheet. Moreover, Students indeed were
able to understanding of the concepts of digital communication systems. Besides that, Stud Studen entt can can
able able to unde unders rsta tand ndin ing g
the the
diff differ eren ence ce perf perfor orma manc ncee
of digi digita tall
communication system when it is under the influence of Intersymbol Interference (ISI) and when it is both under the influence of Intersymbol Interference (ISI) with corrupted by noise.
