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**ME502 Overview of Digital Communication - Melbourne Institute of technology**

**Learning Outcomes**

**e. **Evaluate multiuser communication and resource sharing techniques;

**f. **Apply the techniques of, and report on, digital communication applications using Matlab and hardware devices.

**PART A**

**1.1. Scope**

Communication seems to be one of the most demanding as well as the modern part of the science. LTE-advanced seems one of the best 4G technology. It is modern technology which has the capability to fulfill all the service demands of the multi-users. This can include heterogeneous traffic environment with the high data rate. All the operations of 4G technology are achieved with the help of intelligent implementation. The implementation is done through the main layer known as the radio resource management layer. LTE system consists of three types of levels. These are the admission layer, packet layer, and class level. OFDMA is the Orthogonal Frequency Division Multiple Accesses [2]. It is the multi-carrier scheme which helps in allocating the resources to various multiple users. OFDM method is mainly used by OFDMA whereas the SC-FMDA method seems to be for the 3GPP LTE transmission technique. It is the most modified technique when it is compared to OFDMA. SC-FMDA technique is having the same complexity level as OFDMA. For avoiding the interference, an only a single user is provided at single RB. In the process of transmission, the maximum range of the power is always present at the mobile users as well as the base station.

Multi-user downlink: There are various theoretical as well as experimental research was done on various multi-user downlink. All the research have shown that the multiplexing gains are available in the downlink multi-user MIMO. The technique which is used to distinguish the serve multiple users with the user channels is known as Transmit beamforming.

**1.2. Requirement**

LTE systems are the system which includes the latency, cell capacity, peak data rate, extended, and flexibility of the spectrum. The maximum data rate must be downlink at 100 Mbps and uplink at 50 Mbps and bandwidth at 20 MHz. Within a 5 MHz, bandwidth, cell capability must sustain 200 active customers. In the client, plane latency must be 5ms and movement needs to be optimized to sustain 0-15 km per h. The flexibility of the spectrum must range from 1.25 to 20 MHz. Key components in LTE schemes are broader bandwidth up to 20 MHz, plain IP architecture supporting immediate interaction between base stations, MIMO promotes various transmissions of information as well as the reception. This also helps in enhancing the overall quality of the signal and the data reception quality. The recent spectrum range of the flexibility of the LTE is 1.25 and 2.25 MHz. The current peak of the data rate in case of the downlink is 326.4 Mbps and in case of uplink, it is 86.4 Mbps.

**1.3. Critical Review**

LTE is the Long Term Evolution Network. The major approach in this is to develop the LTE advanced system which is used in providing the facility for the fourth generation wireless system. This system can be used in mobile services. In the current scenario, D2D (Device-to-Device) communication seems to be the most promising technique. This technique helps in improving the overall utilization of the spectrum and it provides the wireless service of a peer to peer connection. In the earlier times, for the communication between the UEs (User Equipment's) the user need to build both the Uplink as well as the downlink communication with the help of the BS (Base Stations) but nowadays the D2D communication method is the technique in which one user equipmentdirectly converses with the other equipment. This can be easily done by reusing the cellular resources. There were two major challenges that were faced by the users when they were enabling the D2D technique of communication in the cellular network. The first major challenge is due to the quality of the service provided by the D2D communication technique. The least quality of the service must be guaranteed. The other challenge is related to the overall performance of cellular devices. This is affected by some of the obstruction in the D2D device which is caused by cellular users.

In order to solve the above problems, one of the joint schemes which is related to the block scheduling as well as the power control scheme is introduced for the D2D communication in case of the LTE-Advanced networks. This will help in addressing the above challenges and it also helps in maximizing the spectrum utilization.

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**1.4. Research Depth**

Taha [1] have provided the survey which is related to the multicarrier transmission techniques which are OFDM and another one is the combination of the OFDM with the CDMA (Code Division Multiple Access). In this survey, they have tried to provide an explanation on the usage of the DWT-OFDM (Discrete Wavelet Transform based OFDM). The combination of these two techniques (OFDMA and CDMA) helps in providing the great advantage which further helps in lowering the symbol rate for each subcarrier. The longer duration of the symbol helps in easy synchronizing during transmission.

LTE is perceived by the Third Generation Partnership Project (3GPP) with a mean to let down the dormancy, convey high all through and upgrade ghostly proficiency as for past 3G systems. 3GPP versatile systems changes moved the utilization of Code Division Multiple Access (CDMA) to OFDMA. OFDMA is an incredible method to determine the ISI issues as it streamlines the channel equalizers. The idea of asset portion in LTE systems is critical to comprehend as it incorporates calculation for both uplink and downlink booking.The first calculation was intended to work in the downlink. For ongoing application in LTE systems, downlink calculation is planned for two phases. In the primary stage, advanced channel hypothesis dependent on asset allotment instrument is introduced. This is called as moving normal scheduler (MAS). This moving normal scheduler characterizes testing time, the measure of information for every genuine stream to satisfy the necessities of the nature of administration of each stream. The second stage is identified with the assignment of assets. This stage utilizes expert reasonableness (PF) scheduler. The second calculation is identified with the uplink work and it is reliant on the Genetic Algorithms (GA). This instrument is planned particularly for dealing with the mind-boggling streamlining issues. Genetic Algorithms (GA) is a significant apparatus presently utilized for asset appropriation for the LTE uplink.

They have studied quite a number Uplink multi-user selection scheme in a Multicell environment especially for MIMO structures and they proposed an Interference Aware User Selection Scheme (IAR) for this system. This scheme works in a disbursed manner. The Author has centered on the uplink multiuser MIMO systems in multicell surroundings and tried to construct up a consumer selection scheme. For the development of the user selection scheme, they proposed two steps. The first step is associated with the beamforming a vector of every more than one cellular station. In the subsequent step, every base station chooses a set of customers for serving them at the identical time to analyze the multiuser range and the interference of neighboring cells on them. The improvement of user decision scheme is indispensable to get the preferred hyperlink performance. The necessities for the development of multiuser selection scheme are extensive to analyze in order to obtain the highest sum charge and to embody comparative fairness among the users.

**1.5. Recent Developments**

The new method which was described by the Yaacoub includes the wireless technologies which are the continuous method for overcoming the demands of the users for the high-speed mobile internet services. OFDMA seems to be the new technique which is the best for the multiple access scheme. The major reason for choosing this method is to satisfy the overall demand for the high-speed reliable data services. There is a great need for the delay sensitive applications. This need to be done with the high-speed internet data so that the user can play games on mobile and can have video conferencing. There is a need for updating the state of OFDMA which is based on the wireless communication system. In earlier times, the downlink and the uplink were considered as the independent systems for the resource allocation. In recent times, the QARAS (Queue Aware Resource Allocation Schemes) is considered as the anticipated scheme for providing the delay guarantees.

This plot has been considered for both uplink and downlink headings autonomously. Great quality is required in both the bearings to attain conclusion client fulfillment. When coupling is performed between the downlink and uplink bearings in arrange to decide the quality of benefit of a specific client, in this circumstance the issue objective and detailing changes appropriately. For case when a client employments a mobile diversion application it features a great channel circumstance within the uplink heading but downlink course goes in awful channel condition. In this circumstance organize endure from awful quality. This circumstance happens since information is sent at a really tall speed whereas accepting speed is exceptionally which outstandingly influences the benefit interactivity.

Understand the importance of multiuser resource allocation techniques employed in the uplink of modern digital communication networks using wireless medium for information transmission. Students also develop skills in information gathering and technical documentation.

**Question 1: Amplitude Modulation** (AM)

In this part, we are given with the modulating as well as the carrier signal. The modulating signal is having the frequency as 60 Hz with the amplitude of 4V. The carrier signal is having the voltage amplitude as 1V and frequency as 800 MHz. The frequency is got converted to the Hz which is equivalent to 800*10^6 Hz. The carrier signal is having the phase as pi/4. In this, we have compared the suppressed carrier AM (SC-AM) and full-carrier AM (FCAM).

u(t)=m(t)c(t)

v(t)=[1+m(t)/Ac]c(t)

**(a) **Using Matlab, sketch the waveforms of m(t), u(t)=m(t)c(t) and v(t)=[1 + m(t)/Ac]*c(t) in one figure. Explain what you observe from the figures.

**Part a:**

In this part, we have plotted the waveforms of m (t), u (t), and v (t). MATLAB Code for the ‘part a' is as below:

% To close and clear all the previous work

clear all

close all

clc

% Modulating Signal

% Modulating Frequency

f_0 = 60;

% Amplitude

A_m = 4;

% Carrier Signal

% Volatage Amplitude

A_c = 1;

% Carrier Frequency

f_c = 800*10^6;

% Phase

phi = pi./4;

% Time period of modulating signal

t_m=1/f_0;

% Total time for overall simulation

t=0:t_m/100:2*t_m;

% Modulating Signal Equation:

m_t = A_m.*cos(2.*pi.*f_0.*t);

% Carrier Signal Equation

c_t = A_c.*cos(2.*pi.*f_c.*t+phi);

% DSB-SC AM signal:

u_t = m_t.*c_t;

% DSB-FC AM signal:

v_t = [1 + m_t./A_c].*c_t;

figure

subplot(311)

plot(t,m_t,'b','linewidth',1)

grid on

xlabel ( 'time(sec)');

ylabel ('Amplitud(volt)');

title ('Modulating Signal');

subplot(312)

plot(t,u_t,'r','linewidth',1)

grid on

xlabel ( 'time(sec)');

ylabel ('Amplitud(volt)');

title ( 'DSB-SC AM signal');

subplot(313)

plot(t,v_t,'k','linewidth',1)

grid on

xlabel ( 'time(sec)');

ylabel ('Amplitud(volt)');

title ( 'DSB-FC AM signal');

From the above results, we have found that waveforms of the DSB-SC AM and DSB-FC AM signals are almost equal. This is due to the value of the voltage amplitude of the carrier signal. The value of the voltage amplitude is 1 V. If the value is other than 1 V then the results will vary.

(b) Using Matlab sketch the spectra of m(t), u(t)=m(t)c(t) and v(t)=[1 + m(t)/Ac]*c(t) in one figure.

**Part b:**

In this part, we have plotted the spectra of m (t), u (t), and v (t). MATLAB Code for the ‘part b' is as below:clear all

close all

clc

% Modulating Frequency

f_0 = 60;

% Amplitude

A_m = 4;

% Carrier Signal

% Volatage Amplitude

A_c = 1;

% Carrier Frequency

f_c = 800*10^6;

% Phase

phi = pi./4;

% Time period of modulating signal

t_m = 1/f_0;

% Total time for overall simulation

t = 0:t_m/100:2*t_m;

N = size(t,2);

%Frequency specifications:

dF = f_0/N;

f = -f_0/2:dF:f_0/2-dF;

% Modulating Signal Equation:

m_t = A_m.*cos(2.*pi.*f_0.*t);

% Carrier Signal Equation

c_t = A_c.*cos(2.*pi.*f_c.*t+phi);

% DSB-SC AM signal:

u_t = m_t.*c_t;

% DSB-FC AM signal:

v_t = [1 + m_t./A_c].*c_t;

%Fourier Transform: Modulating Signal Equation:

m_t_1 = fftshift(fft(m_t));

%Fourier Transform: DSB-SC AM signal Equation:

u_t_1 = fftshift(fft(u_t));

%Fourier Transform: DSB-FC AM signal Equation:

v_t_1 = fftshift(fft(v_t));

%Plot the spectrum:

figure;

subplot(311)

plot(f,abs(m_t_1)/N);

grid on

xlabel('Frequency (in hertz)');

ylabel('Magnitude');

title('Magnitude Response');

subplot(312)

plot(f,abs(u_t_1)/N);

grid on

xlabel('Frequency (in hertz)');

ylabel('Magnitude');

title('Magnitude Response');

subplot(313)

plot(f,abs(v_t_1)/N);

grid on

xlabel('Frequency (in hertz)');

ylabel('Magnitude');

title('Magnitude Response');

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**Question 2: Huffman coding**

Consider a source with the seven symbols in its alphabet s = {'s0' 's1' 's2' 's3' 's4' 's5' 's6'} which has the probabilities p = [0.18 0.21 0.2 0.26 0.03 0.05 0.07].

In this, we are given with the seven symbols in its alphabet s = {‘s0' ‘s1' ‘s2' ‘s3' ‘s4' ‘s5' ‘s6'} with the given probabilities as [0.18 0.21 0.2 0.26 0.03 0.05 0.07].

(a) Write a MATLAB function ‘entropy' to compute the entropy of the source.

**Part a: **In this part, we have presented the MATLAB function which is used in computing the entropy of the source.

%% Question 2: Huffman coding

% Entropy Function

function H_value = entropy(prob)

%ENTROPY

prob = double(prob);

val = hist(prob(:),256);

val = val / sum(val(:));

% Make mask to eliminate 0's

mask1 = find(val);

% Compute entropy

H_value = -sum(val(mask1) .* log2(val(mask1)));

(b) Use your function ‘entropy' to find the entropy of the given source.

**Part b: **In this part, we have used the entropy function to evaluate the entropy of the given source.

%% Entropy of the given source

clear all

close all

clc

prob = [0.18 0.21 0.2 0.26 0.03 0.05 0.07];

H_value = entropy(prob);

fprintf('\nEntropy of given source is %.2f\n',H_value)

(c) Write a MATLAB program to generate a Huffman code for the source.

**Part c: **In this part, we have represents the MATLAB code for generating the Huffman code for the sources.%% Huffman Function

function [code_out]=huffman_function(prob)

prob=prob(:)/sum(prob);

value_1=cell(length(prob),1);

for loop=1:length(prob)

value_1{loop}=loop;

end

b=2;

while size(value_1)-b

[prob,loop]=sort(prob);

value_1=value_1(loop);

value_1{2}={value_1{1},value_1{2}};value_1(1)=[];

prob(2)=prob(1)+prob(2);prob(1)=[];

end

code_out=char(code1(value_1,length(prob)));

function y = code1(val_n,n)

global y

y=cell(n,1);

code2(val_n,[])

%----------------------------------------------------------------

function code2(var,var1)

global y

if isa(var,'cell')

code2(var{1},[var1 0]);

code2(var{2},[var1 1]);

else

y{var}=setstr(48+var1);

end

clear all

clc

prob = [0.18 0.21 0.2 0.26 0.03 0.05 0.07];

% call the huffman function

[code_out]=huffman_function(prob);

disp('Huffman code for the source is:')

code_out

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