I have a control loop such that:
The loop starts by calculating the error between the desired and measured temperature.
The relay block turns the heating system on or off based on this error, with a hysteresis of ±5 degrees to prevent frequent switching.
The output from the relay (on/off signal) is passed through a transfer function to simulate the dynamics of the system (introducing a delay or lag in the heating response).
The scaled output from the transfer function (now a power signal) is converted into a physical signal.
Finally, the physical signal controls the heat source, which in turn affects the system’s temperature.
I want to use PID controller block instead of this, how can I achieve that?I have a control loop such that:
The loop starts by calculating the error between the desired and measured temperature.
The relay block turns the heating system on or off based on this error, with a hysteresis of ±5 degrees to prevent frequent switching.
The output from the relay (on/off signal) is passed through a transfer function to simulate the dynamics of the system (introducing a delay or lag in the heating response).
The scaled output from the transfer function (now a power signal) is converted into a physical signal.
Finally, the physical signal controls the heat source, which in turn affects the system’s temperature.
I want to use PID controller block instead of this, how can I achieve that? I have a control loop such that:
The loop starts by calculating the error between the desired and measured temperature.
The relay block turns the heating system on or off based on this error, with a hysteresis of ±5 degrees to prevent frequent switching.
The output from the relay (on/off signal) is passed through a transfer function to simulate the dynamics of the system (introducing a delay or lag in the heating response).
The scaled output from the transfer function (now a power signal) is converted into a physical signal.
Finally, the physical signal controls the heat source, which in turn affects the system’s temperature.
I want to use PID controller block instead of this, how can I achieve that? simulink, pid, simscape MATLAB Answers — New Questions

​

Hello everyone,
I am currently working on a logic circuit in MATLAB Simulink that involves a Multiplexer (MUX) and an XOR gate. I would like to measure the power consumption (current) of both the MUX and XOR components, but I’m not sure how to go about it in Simulink.

Here are some details about my setup:
I have a 4-to-1 MUX and an XOR gate in my design.
I am looking to measure the dynamic power consumption for each gate during operation.
Could anyone provide guidance on:
How to model or simulate the power consumption for logic components like MUX and XOR gates in Simulink?
Any recommended blocks or libraries to use?
Approaches for accurately measuring the current drawn by these components?
Any tips or examples would be greatly appreciated!Hello everyone,
I am currently working on a logic circuit in MATLAB Simulink that involves a Multiplexer (MUX) and an XOR gate. I would like to measure the power consumption (current) of both the MUX and XOR components, but I’m not sure how to go about it in Simulink.

Here are some details about my setup:
I have a 4-to-1 MUX and an XOR gate in my design.
I am looking to measure the dynamic power consumption for each gate during operation.
Could anyone provide guidance on:
How to model or simulate the power consumption for logic components like MUX and XOR gates in Simulink?
Any recommended blocks or libraries to use?
Approaches for accurately measuring the current drawn by these components?
Any tips or examples would be greatly appreciated! Hello everyone,
I am currently working on a logic circuit in MATLAB Simulink that involves a Multiplexer (MUX) and an XOR gate. I would like to measure the power consumption (current) of both the MUX and XOR components, but I’m not sure how to go about it in Simulink.

Here are some details about my setup:
I have a 4-to-1 MUX and an XOR gate in my design.
I am looking to measure the dynamic power consumption for each gate during operation.
Could anyone provide guidance on:
How to model or simulate the power consumption for logic components like MUX and XOR gates in Simulink?
Any recommended blocks or libraries to use?
Approaches for accurately measuring the current drawn by these components?
Any tips or examples would be greatly appreciated! simulink, mux, xor, current-power MATLAB Answers — New Questions

​

I experience this error when using HDL Verifier on a Linux machine (RedHat 7)
ERROR: ld.so: object ‘/tools/matlab/R2023bU1/bin/glnxa64/glibc-2.17_shim.so’ from LD_PRELOAD cannot be preloaded: ignored.
Do you know how I can overcome this issue?I experience this error when using HDL Verifier on a Linux machine (RedHat 7)
ERROR: ld.so: object ‘/tools/matlab/R2023bU1/bin/glnxa64/glibc-2.17_shim.so’ from LD_PRELOAD cannot be preloaded: ignored.
Do you know how I can overcome this issue? I experience this error when using HDL Verifier on a Linux machine (RedHat 7)
ERROR: ld.so: object ‘/tools/matlab/R2023bU1/bin/glnxa64/glibc-2.17_shim.so’ from LD_PRELOAD cannot be preloaded: ignored.
Do you know how I can overcome this issue? hdlverifier, simulink, linux, redhat MATLAB Answers — New Questions

​

I need a program with a triangular Bezier patch in matlabI need a program with a triangular Bezier patch in matlab I need a program with a triangular Bezier patch in matlab bezier -patch -triangular-surf MATLAB Answers — New Questions

​

Hello, while attempting to use SIMULINK in MATLAB 2024a for my training, the above message was seen. Any help?Hello, while attempting to use SIMULINK in MATLAB 2024a for my training, the above message was seen. Any help? Hello, while attempting to use SIMULINK in MATLAB 2024a for my training, the above message was seen. Any help? simulink, matlab MATLAB Answers — New Questions

​

Hi,

Matlab suggested me to create a more efficient code: what i am trying to do is to create 12 holes vertically in a strip of wire and repeat it 7x times over a 0.2 distance: i started with this code:

model = createpde;

%Define a circle in a rectangle, place these in one matrix, and create a set formula that subtracts the circle from the rectangle.
rectx=0;
recty=0;
rect_width=1.38;
rect_height=0.2;

x_start=0.1;%starting position x circle
y_start=0.2;%starting position y circle
radius=0.005;%radius holes
num_holes_y=12;%number of repitition in the y
num_rep_x=7;%number of repitition in the x
y_interval=0.0183; %distance between the holes in the y;
x_interval=0.2; % distance between the holes in the x;
pderect([rectx rect_width recty,rect_height] )

%create multiple holes in a strip and draw it into the pde modeler
for j=0:(num_rep_x-1)
for i=0:(num_holes_y-1)
%calculate the x and y position for the current hole
x_center=x_start+j*x_interval;
y_center=y_start-i*y_interval;

pdecirc(x_center, y_center,radius)

hold on;

end
end
axis equal;
hold off;

better code as matlab suggested: but get stuck with an error:
Error in TestSkript2 (line 38)
ns(idx+1)=[‘C’,num2str(idx)];

please advise.

model = createpde;

%Define a circle in a rectangle, place these in one matrix, and create a set formula that subtracts the circle from the rectangle.

rectx=0;
recty=0;
rect_width=1.38;
rect_height=0.2;

x_start=0.1;%starting position x circle
y_start=0.2;%starting position y circle
radius=0.005;%radius holes
num_holes_y=12;%number of repitition in the y
num_rep_x=7;%number of repitition in the x
y_interval=0.0183; %distance between the holes in the y;
x_interval=0.2; % distance between the holes in the x;
R1=[3,4,rectx, rectx+rect_width,rectx+rect_width,rectx,recty,recty,recty+rect_height,recty+rect_height]’;
%preallocating the arrays(more efficient for matlab CHAT GPT)
num_circles = num_holes_y * num_rep_x;
gd = zeros(10, 1 + num_circles);
gd(:, 1) = R1;
ns = cell(1+num_circles,1);
ns{ones}=’R1′;
sf=’R1′;

%create multiple holes in a strip and draw it into the pde modeler
for j=0:(num_rep_x-1)
for i=0:(num_holes_y-1)
%calculate the x and y position for the current hole
x_center=x_start+j*x_interval;
y_center=y_start-i*y_interval;

C=[1,x_center, y_center,radius]’;
idx=j*num_holes_y+i+1;
gd(1:4,idx+1)=C;
ns{idx+1}=[‘C’,num2str(idx)];
sf=[sf,’C’,num2str(idx)];

end
end
ns=char(ns);
g=decsg(gd,sf,ns);
axis equal;
hold off;Hi,

Matlab suggested me to create a more efficient code: what i am trying to do is to create 12 holes vertically in a strip of wire and repeat it 7x times over a 0.2 distance: i started with this code:

model = createpde;

%Define a circle in a rectangle, place these in one matrix, and create a set formula that subtracts the circle from the rectangle.
rectx=0;
recty=0;
rect_width=1.38;
rect_height=0.2;

x_start=0.1;%starting position x circle
y_start=0.2;%starting position y circle
radius=0.005;%radius holes
num_holes_y=12;%number of repitition in the y
num_rep_x=7;%number of repitition in the x
y_interval=0.0183; %distance between the holes in the y;
x_interval=0.2; % distance between the holes in the x;
pderect([rectx rect_width recty,rect_height] )

%create multiple holes in a strip and draw it into the pde modeler
for j=0:(num_rep_x-1)
for i=0:(num_holes_y-1)
%calculate the x and y position for the current hole
x_center=x_start+j*x_interval;
y_center=y_start-i*y_interval;

pdecirc(x_center, y_center,radius)

hold on;

end
end
axis equal;
hold off;

better code as matlab suggested: but get stuck with an error:
Error in TestSkript2 (line 38)
ns(idx+1)=[‘C’,num2str(idx)];

please advise.

model = createpde;

%Define a circle in a rectangle, place these in one matrix, and create a set formula that subtracts the circle from the rectangle.

rectx=0;
recty=0;
rect_width=1.38;
rect_height=0.2;

x_start=0.1;%starting position x circle
y_start=0.2;%starting position y circle
radius=0.005;%radius holes
num_holes_y=12;%number of repitition in the y
num_rep_x=7;%number of repitition in the x
y_interval=0.0183; %distance between the holes in the y;
x_interval=0.2; % distance between the holes in the x;
R1=[3,4,rectx, rectx+rect_width,rectx+rect_width,rectx,recty,recty,recty+rect_height,recty+rect_height]’;
%preallocating the arrays(more efficient for matlab CHAT GPT)
num_circles = num_holes_y * num_rep_x;
gd = zeros(10, 1 + num_circles);
gd(:, 1) = R1;
ns = cell(1+num_circles,1);
ns{ones}=’R1′;
sf=’R1′;

%create multiple holes in a strip and draw it into the pde modeler
for j=0:(num_rep_x-1)
for i=0:(num_holes_y-1)
%calculate the x and y position for the current hole
x_center=x_start+j*x_interval;
y_center=y_start-i*y_interval;

C=[1,x_center, y_center,radius]’;
idx=j*num_holes_y+i+1;
gd(1:4,idx+1)=C;
ns{idx+1}=[‘C’,num2str(idx)];
sf=[sf,’C’,num2str(idx)];

end
end
ns=char(ns);
g=decsg(gd,sf,ns);
axis equal;
hold off; Hi,

Matlab suggested me to create a more efficient code: what i am trying to do is to create 12 holes vertically in a strip of wire and repeat it 7x times over a 0.2 distance: i started with this code:

model = createpde;

%Define a circle in a rectangle, place these in one matrix, and create a set formula that subtracts the circle from the rectangle.
rectx=0;
recty=0;
rect_width=1.38;
rect_height=0.2;

x_start=0.1;%starting position x circle
y_start=0.2;%starting position y circle
radius=0.005;%radius holes
num_holes_y=12;%number of repitition in the y
num_rep_x=7;%number of repitition in the x
y_interval=0.0183; %distance between the holes in the y;
x_interval=0.2; % distance between the holes in the x;
pderect([rectx rect_width recty,rect_height] )

%create multiple holes in a strip and draw it into the pde modeler
for j=0:(num_rep_x-1)
for i=0:(num_holes_y-1)
%calculate the x and y position for the current hole
x_center=x_start+j*x_interval;
y_center=y_start-i*y_interval;

pdecirc(x_center, y_center,radius)

hold on;

end
end
axis equal;
hold off;

better code as matlab suggested: but get stuck with an error:
Error in TestSkript2 (line 38)
ns(idx+1)=[‘C’,num2str(idx)];

please advise.

model = createpde;

%Define a circle in a rectangle, place these in one matrix, and create a set formula that subtracts the circle from the rectangle.

rectx=0;
recty=0;
rect_width=1.38;
rect_height=0.2;

x_start=0.1;%starting position x circle
y_start=0.2;%starting position y circle
radius=0.005;%radius holes
num_holes_y=12;%number of repitition in the y
num_rep_x=7;%number of repitition in the x
y_interval=0.0183; %distance between the holes in the y;
x_interval=0.2; % distance between the holes in the x;
R1=[3,4,rectx, rectx+rect_width,rectx+rect_width,rectx,recty,recty,recty+rect_height,recty+rect_height]’;
%preallocating the arrays(more efficient for matlab CHAT GPT)
num_circles = num_holes_y * num_rep_x;
gd = zeros(10, 1 + num_circles);
gd(:, 1) = R1;
ns = cell(1+num_circles,1);
ns{ones}=’R1′;
sf=’R1′;

%create multiple holes in a strip and draw it into the pde modeler
for j=0:(num_rep_x-1)
for i=0:(num_holes_y-1)
%calculate the x and y position for the current hole
x_center=x_start+j*x_interval;
y_center=y_start-i*y_interval;

C=[1,x_center, y_center,radius]’;
idx=j*num_holes_y+i+1;
gd(1:4,idx+1)=C;
ns{idx+1}=[‘C’,num2str(idx)];
sf=[sf,’C’,num2str(idx)];

end
end
ns=char(ns);
g=decsg(gd,sf,ns);
axis equal;
hold off; pde modeler script. MATLAB Answers — New Questions

​

Hi everybody,
I want to simulate an elastic tooth mesh within my simscape multibody model. The model is very simple and consists only two gears. The model works fine with the "Common Gear Constraint" block, but I want to simulate spring and damping effects. Therefore I added a Torsional Spring-Damper which I connected to the model via a Rotational Multibody Interface.

Error:An error occurred during simulation and the simulation was terminated
Caused by:
[‘Test_ElastischerZahneingriff_1/Solver Configuration’]: Initial conditions solve failed to converge.
Nonlinear solver: Linear Algebra error. Failed to solve using iteration matrix.
The model may not give enough information to make it possible to solve for values of some of its variables. Specific advice is given below.

all components and nodal across variables involved
Tie variable ‘Torsional_Spring_Damper.R.w’ (Rotational velocity) to a definite value, for example by connecting an appropriate domain reference block.

Dependency found among topology equations. Check for missing reference node.

Is anybody out there who can help me fixing this error?
You can see the model in the pictures.

Thank’s everybody for any helpful comment….

Kind regards,
ThomasHi everybody,
I want to simulate an elastic tooth mesh within my simscape multibody model. The model is very simple and consists only two gears. The model works fine with the "Common Gear Constraint" block, but I want to simulate spring and damping effects. Therefore I added a Torsional Spring-Damper which I connected to the model via a Rotational Multibody Interface.

Error:An error occurred during simulation and the simulation was terminated
Caused by:
[‘Test_ElastischerZahneingriff_1/Solver Configuration’]: Initial conditions solve failed to converge.
Nonlinear solver: Linear Algebra error. Failed to solve using iteration matrix.
The model may not give enough information to make it possible to solve for values of some of its variables. Specific advice is given below.

all components and nodal across variables involved
Tie variable ‘Torsional_Spring_Damper.R.w’ (Rotational velocity) to a definite value, for example by connecting an appropriate domain reference block.

Dependency found among topology equations. Check for missing reference node.

Is anybody out there who can help me fixing this error?
You can see the model in the pictures.

Thank’s everybody for any helpful comment….

Kind regards,
Thomas Hi everybody,
I want to simulate an elastic tooth mesh within my simscape multibody model. The model is very simple and consists only two gears. The model works fine with the "Common Gear Constraint" block, but I want to simulate spring and damping effects. Therefore I added a Torsional Spring-Damper which I connected to the model via a Rotational Multibody Interface.

Error:An error occurred during simulation and the simulation was terminated
Caused by:
[‘Test_ElastischerZahneingriff_1/Solver Configuration’]: Initial conditions solve failed to converge.
Nonlinear solver: Linear Algebra error. Failed to solve using iteration matrix.
The model may not give enough information to make it possible to solve for values of some of its variables. Specific advice is given below.

all components and nodal across variables involved
Tie variable ‘Torsional_Spring_Damper.R.w’ (Rotational velocity) to a definite value, for example by connecting an appropriate domain reference block.

Dependency found among topology equations. Check for missing reference node.

Is anybody out there who can help me fixing this error?
You can see the model in the pictures.

Thank’s everybody for any helpful comment….

Kind regards,
Thomas simscape, multibody, gear, elastic tooth mesh MATLAB Answers — New Questions

​

Post Content Post Content ccs ti MATLAB Answers — New Questions

​

clear all
close all
Data_Seq=[1,1,1,0,0,0,1,0]

stem(Data_Seq)
bitrate= 1000000;
SR=1/bitrate;
ylim([-1 1])
t=0:0.01:length(Data_Seq)
Data_Seq2=[1,1,1,-1,-1,-1,1,-1]
stem(Data_Seq2)
A = Data_Seq2(1:2:end,:) %
B = Data_Seq2(2:2:end,:)
stem(A)
even = Data_Seq(2:2:end);
odd = Data_Seq(1:2:end);

stem(even)
// i Want to seperate even and odd signal but not undrstanding how to plotclear all
close all
Data_Seq=[1,1,1,0,0,0,1,0]

stem(Data_Seq)
bitrate= 1000000;
SR=1/bitrate;
ylim([-1 1])
t=0:0.01:length(Data_Seq)
Data_Seq2=[1,1,1,-1,-1,-1,1,-1]
stem(Data_Seq2)
A = Data_Seq2(1:2:end,:) %
B = Data_Seq2(2:2:end,:)
stem(A)
even = Data_Seq(2:2:end);
odd = Data_Seq(1:2:end);

stem(even)
// i Want to seperate even and odd signal but not undrstanding how to plot clear all
close all
Data_Seq=[1,1,1,0,0,0,1,0]

stem(Data_Seq)
bitrate= 1000000;
SR=1/bitrate;
ylim([-1 1])
t=0:0.01:length(Data_Seq)
Data_Seq2=[1,1,1,-1,-1,-1,1,-1]
stem(Data_Seq2)
A = Data_Seq2(1:2:end,:) %
B = Data_Seq2(2:2:end,:)
stem(A)
even = Data_Seq(2:2:end);
odd = Data_Seq(1:2:end);

stem(even)
// i Want to seperate even and odd signal but not undrstanding how to plot qpsk modulation MATLAB Answers — New Questions

​

% Parameters
M = 4; % MQAM order (e.g., 16-QAM)
N = 1e5; % Number of transmit symbols

% Define SNR range
SNR_dB_range = 0:10;
num_SNR_points = length(SNR_dB_range);

% Initialize SER array
SER_values = zeros(num_SNR_points, 1);

% Create MQAM constellation
constellation = createMQAM(M);
% Loop over each SNR value
for idx = 1:num_SNR_points
SNR_dB = SNR_dB_range(idx);

% Generate transmit symbols
transmitSymbols = generateSymbols(constellation, N);

% Transmit through AWGN channel
receivedSymbols = transmitSymbolsThroughAWGN(transmitSymbols, SNR_dB);

% Demodulate symbols
decodedSymbols = demodulateSymbols(receivedSymbols, constellation);

% Compute Symbol Error Rate
SER = computeSER(transmitSymbols, decodedSymbols);

% Store SER value
SER_values(idx) = SER;

% Compute Theoretical SER
SER_theoretical = computeTheoreticalSER(M, SNR_dB_range);
SER_theoretical_values = SER_theoretical;
end

% Plot SER vs SNR
figure;
semilogy(SNR_dB_range, SER_values, ‘o-‘, ‘DisplayName’, ‘Simulated SER’);
hold on;
semilogy(SNR_dB_range, SER_theoretical_values, ‘r–‘, ‘DisplayName’, ‘Theoretical SER’);
xlabel(‘SNR (dB)’);
ylabel(‘Symbol Error Rate (SER)’);
title(‘SER vs. SNR for MQAM’);
legend;
grid on;

function constellation = createMQAM(M)
% Create an MQAM constellation manually
% M: Number of symbols (e.g., 16, 64, etc.)

% Check that M is a perfect square
k = sqrt(M);
if mod(k,1) ~= 0
error(‘M must be a perfect square’);
end

% Generate constellation points
k = round(k); % Number of points per side
[X, Y] = meshgrid(linspace(-k+1, k-1, k), linspace(-k+1, k-1, k));
constellation = X(:) + 1i*Y(:);
end

function symbols = generateSymbols(constellation, N)
% Generate N random transmit symbols
% constellation: The MQAM constellation points
% N: Number of symbols to generate

numPoints = length(constellation);
indices = randi([1 numPoints], [N, 1]); % Randomly choose indices
symbols = constellation(indices); % Select symbols from the constellation
end

function received = transmitSymbolsThroughAWGN(symbols, SNR_dB)
% Transmit symbols through a SISO AWGN channel
% symbols: Transmit symbols
% SNR_dB: Signal-to-noise ratio in dB

% Convert SNR from dB to linear scale
SNR_linear = 10^(SNR_dB / 10);

% Calculate noise variance
noise_variance = 1 / SNR_linear;

% Generate noise
noise = sqrt(noise_variance / 2) * (randn(size(symbols)) + 1i*randn(size(symbols)));

% Received symbols
received = symbols + noise;
end

function decodedSymbols = demodulateSymbols(received, constellation)
% Demodulate symbols using minimum distance decoding
% received: Received symbols
% constellation: MQAM constellation points

numSymbols = length(received);
numPoints = length(constellation);

% Initialize decoded symbols
decodedSymbols = zeros(size(received));

for i = 1:numSymbols
% Compute distances to all constellation points
distances = abs(received(i) – constellation).^2;
% Find the closest constellation point
[~, idx] = min(distances);
decodedSymbols(i) = constellation(idx);
end
end

function SER = computeSER(originalSymbols, decodedSymbols)
% Compute symbol error rate
% originalSymbols: Transmit symbols
% decodedSymbols: Received and decoded symbols

numErrors = sum(originalSymbols ~= decodedSymbols);
totalSymbols = length(originalSymbols);

SER = numErrors / totalSymbols;
end

function SER_theoretical = computeTheoreticalSER(M, SNR_dB)
% Compute the theoretical SER for MQAM in AWGN
% M: Number of symbols (e.g., 16, 64, etc.)
% SNR_dB: SNR in dB

% Convert SNR from dB to linear scale
SNR_linear = 10.^(SNR_dB / 10);

% Compute theoretical SER
k = sqrt(M); % Number of points per side
if mod(k,1) ~= 0
error(‘M must be a perfect square’);
end
% Calculate SER using the Q-function
SER_theoretical = 4*(1-1./sqrt(M))*qfunc(sqrt(3./(M-1)*SNR_linear));
end

In the above code when I plot the SER v/s SNR and compare the simulation and analytical values don’t match. Can someone tell me what is the error in my code and how can I match the curves ?% Parameters
M = 4; % MQAM order (e.g., 16-QAM)
N = 1e5; % Number of transmit symbols

% Define SNR range
SNR_dB_range = 0:10;
num_SNR_points = length(SNR_dB_range);

% Initialize SER array
SER_values = zeros(num_SNR_points, 1);

% Create MQAM constellation
constellation = createMQAM(M);
% Loop over each SNR value
for idx = 1:num_SNR_points
SNR_dB = SNR_dB_range(idx);

% Generate transmit symbols
transmitSymbols = generateSymbols(constellation, N);

% Transmit through AWGN channel
receivedSymbols = transmitSymbolsThroughAWGN(transmitSymbols, SNR_dB);

% Demodulate symbols
decodedSymbols = demodulateSymbols(receivedSymbols, constellation);

% Compute Symbol Error Rate
SER = computeSER(transmitSymbols, decodedSymbols);

% Store SER value
SER_values(idx) = SER;

% Compute Theoretical SER
SER_theoretical = computeTheoreticalSER(M, SNR_dB_range);
SER_theoretical_values = SER_theoretical;
end

% Plot SER vs SNR
figure;
semilogy(SNR_dB_range, SER_values, ‘o-‘, ‘DisplayName’, ‘Simulated SER’);
hold on;
semilogy(SNR_dB_range, SER_theoretical_values, ‘r–‘, ‘DisplayName’, ‘Theoretical SER’);
xlabel(‘SNR (dB)’);
ylabel(‘Symbol Error Rate (SER)’);
title(‘SER vs. SNR for MQAM’);
legend;
grid on;

function constellation = createMQAM(M)
% Create an MQAM constellation manually
% M: Number of symbols (e.g., 16, 64, etc.)

% Check that M is a perfect square
k = sqrt(M);
if mod(k,1) ~= 0
error(‘M must be a perfect square’);
end

% Generate constellation points
k = round(k); % Number of points per side
[X, Y] = meshgrid(linspace(-k+1, k-1, k), linspace(-k+1, k-1, k));
constellation = X(:) + 1i*Y(:);
end

function symbols = generateSymbols(constellation, N)
% Generate N random transmit symbols
% constellation: The MQAM constellation points
% N: Number of symbols to generate

numPoints = length(constellation);
indices = randi([1 numPoints], [N, 1]); % Randomly choose indices
symbols = constellation(indices); % Select symbols from the constellation
end

function received = transmitSymbolsThroughAWGN(symbols, SNR_dB)
% Transmit symbols through a SISO AWGN channel
% symbols: Transmit symbols
% SNR_dB: Signal-to-noise ratio in dB

% Convert SNR from dB to linear scale
SNR_linear = 10^(SNR_dB / 10);

% Calculate noise variance
noise_variance = 1 / SNR_linear;

% Generate noise
noise = sqrt(noise_variance / 2) * (randn(size(symbols)) + 1i*randn(size(symbols)));

% Received symbols
received = symbols + noise;
end

function decodedSymbols = demodulateSymbols(received, constellation)
% Demodulate symbols using minimum distance decoding
% received: Received symbols
% constellation: MQAM constellation points

numSymbols = length(received);
numPoints = length(constellation);

% Initialize decoded symbols
decodedSymbols = zeros(size(received));

for i = 1:numSymbols
% Compute distances to all constellation points
distances = abs(received(i) – constellation).^2;
% Find the closest constellation point
[~, idx] = min(distances);
decodedSymbols(i) = constellation(idx);
end
end

function SER = computeSER(originalSymbols, decodedSymbols)
% Compute symbol error rate
% originalSymbols: Transmit symbols
% decodedSymbols: Received and decoded symbols

numErrors = sum(originalSymbols ~= decodedSymbols);
totalSymbols = length(originalSymbols);

SER = numErrors / totalSymbols;
end

function SER_theoretical = computeTheoreticalSER(M, SNR_dB)
% Compute the theoretical SER for MQAM in AWGN
% M: Number of symbols (e.g., 16, 64, etc.)
% SNR_dB: SNR in dB

% Convert SNR from dB to linear scale
SNR_linear = 10.^(SNR_dB / 10);

% Compute theoretical SER
k = sqrt(M); % Number of points per side
if mod(k,1) ~= 0
error(‘M must be a perfect square’);
end
% Calculate SER using the Q-function
SER_theoretical = 4*(1-1./sqrt(M))*qfunc(sqrt(3./(M-1)*SNR_linear));
end

In the above code when I plot the SER v/s SNR and compare the simulation and analytical values don’t match. Can someone tell me what is the error in my code and how can I match the curves ? % Parameters
M = 4; % MQAM order (e.g., 16-QAM)
N = 1e5; % Number of transmit symbols

% Define SNR range
SNR_dB_range = 0:10;
num_SNR_points = length(SNR_dB_range);

% Initialize SER array
SER_values = zeros(num_SNR_points, 1);

% Create MQAM constellation
constellation = createMQAM(M);
% Loop over each SNR value
for idx = 1:num_SNR_points
SNR_dB = SNR_dB_range(idx);

% Generate transmit symbols
transmitSymbols = generateSymbols(constellation, N);

% Transmit through AWGN channel
receivedSymbols = transmitSymbolsThroughAWGN(transmitSymbols, SNR_dB);

% Demodulate symbols
decodedSymbols = demodulateSymbols(receivedSymbols, constellation);

% Compute Symbol Error Rate
SER = computeSER(transmitSymbols, decodedSymbols);

% Store SER value
SER_values(idx) = SER;

% Compute Theoretical SER
SER_theoretical = computeTheoreticalSER(M, SNR_dB_range);
SER_theoretical_values = SER_theoretical;
end

% Plot SER vs SNR
figure;
semilogy(SNR_dB_range, SER_values, ‘o-‘, ‘DisplayName’, ‘Simulated SER’);
hold on;
semilogy(SNR_dB_range, SER_theoretical_values, ‘r–‘, ‘DisplayName’, ‘Theoretical SER’);
xlabel(‘SNR (dB)’);
ylabel(‘Symbol Error Rate (SER)’);
title(‘SER vs. SNR for MQAM’);
legend;
grid on;

function constellation = createMQAM(M)
% Create an MQAM constellation manually
% M: Number of symbols (e.g., 16, 64, etc.)

% Check that M is a perfect square
k = sqrt(M);
if mod(k,1) ~= 0
error(‘M must be a perfect square’);
end

% Generate constellation points
k = round(k); % Number of points per side
[X, Y] = meshgrid(linspace(-k+1, k-1, k), linspace(-k+1, k-1, k));
constellation = X(:) + 1i*Y(:);
end

function symbols = generateSymbols(constellation, N)
% Generate N random transmit symbols
% constellation: The MQAM constellation points
% N: Number of symbols to generate

numPoints = length(constellation);
indices = randi([1 numPoints], [N, 1]); % Randomly choose indices
symbols = constellation(indices); % Select symbols from the constellation
end

function received = transmitSymbolsThroughAWGN(symbols, SNR_dB)
% Transmit symbols through a SISO AWGN channel
% symbols: Transmit symbols
% SNR_dB: Signal-to-noise ratio in dB

% Convert SNR from dB to linear scale
SNR_linear = 10^(SNR_dB / 10);

% Calculate noise variance
noise_variance = 1 / SNR_linear;

% Generate noise
noise = sqrt(noise_variance / 2) * (randn(size(symbols)) + 1i*randn(size(symbols)));

% Received symbols
received = symbols + noise;
end

function decodedSymbols = demodulateSymbols(received, constellation)
% Demodulate symbols using minimum distance decoding
% received: Received symbols
% constellation: MQAM constellation points

numSymbols = length(received);
numPoints = length(constellation);

% Initialize decoded symbols
decodedSymbols = zeros(size(received));

for i = 1:numSymbols
% Compute distances to all constellation points
distances = abs(received(i) – constellation).^2;
% Find the closest constellation point
[~, idx] = min(distances);
decodedSymbols(i) = constellation(idx);
end
end

function SER = computeSER(originalSymbols, decodedSymbols)
% Compute symbol error rate
% originalSymbols: Transmit symbols
% decodedSymbols: Received and decoded symbols

numErrors = sum(originalSymbols ~= decodedSymbols);
totalSymbols = length(originalSymbols);

SER = numErrors / totalSymbols;
end

function SER_theoretical = computeTheoreticalSER(M, SNR_dB)
% Compute the theoretical SER for MQAM in AWGN
% M: Number of symbols (e.g., 16, 64, etc.)
% SNR_dB: SNR in dB

% Convert SNR from dB to linear scale
SNR_linear = 10.^(SNR_dB / 10);

% Compute theoretical SER
k = sqrt(M); % Number of points per side
if mod(k,1) ~= 0
error(‘M must be a perfect square’);
end
% Calculate SER using the Q-function
SER_theoretical = 4*(1-1./sqrt(M))*qfunc(sqrt(3./(M-1)*SNR_linear));
end

In the above code when I plot the SER v/s SNR and compare the simulation and analytical values don’t match. Can someone tell me what is the error in my code and how can I match the curves ? communication, plot MATLAB Answers — New Questions

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