Simple Code for VLC (Visible Light Communications)

how can i write simple code for SNR distribution for indoor VLC

[Walter Roberson]

Which meaning of VLC is intended for this question?

[Désiré_RM]

Hello everybody. Hope all of you're doing well? I'm working on VLC combinate with NOMA. Can you help me with Matlab code for to estimate the indoor coverage with VLC and allocate ressources with NOMA?

Answer 1

[pratik panchal]

I hope it is useful for you.

clear all;

clc;

close all;

% SNR Performance For VLC SYSTEM %

% Coded BY Er. PANCHAL PRATIK

% [e-mail]

% Easy USe Consider Following Example

%

%

% BASIC PARAMETER REQUIRED %

Incidence = 70*pi/180;

TX_FOV = 70;                % Transmitter Field Of View

RX_FOV = 90;                % Receivers Field Of View

Tx = [2,2,2];               % Transmitter Location

%Rxp = [2,2];               % Receiver Location

W_Room = 4;                 % Width of Room

L_Room = 4;                 % Length of Room

H_Room = 2;                 % Height Between Transmitter and Receiver

R = 1;                      % Responsivity of Photodiode

Apd = 1e-4;                 % Area of PhotoDetector

Rb = 1e6;                   % Data rate of system

Iamp = 5e-12;               % Amplifier Current

q = 1.6e-19;                % Electron Charge

Bn = 50e6;                  % Noise Bandwidth

I2 = 0.562;                 % Noise Bandwidth Factor

PLED = 1;                   % Power Emitted by LED

index =1;

HLED = 1;

[W L] = meshgrid(-(W_Room/2) : 0.50 : (W_Room/2));      % Consideer Length of BLock for Room

xydist = sqrt((W).^2 + (L).^2);

hdist = sqrt(xydist.^2 + HLED.^2);

%D = Tx - Rx;

%d = norm(D);

%Incidence = acos()

A_Irradiance = ((Tx(3)-HLED)./hdist);

%I(index) = Irradiance*180/pi;

%if abs(Incidence <= RX_FOV)

      p = TX_FOV ;

      Tx_FOV = (TX_FOV*pi)/180;

      % BASIC CALCULATION IN VLC SYSTEM %

      % Lambertian Pattern 

      m = real(-log(2)/log(cos(Tx_FOV))); 

      % Radiation Intensity at particular point

      Ro = real(((m+1)/(2*pi)).*A_Irradiance^m);

      % Transmitted power By LED

      Ptx = PLED .* Ro;

      % Channel Gain ( Channel Coefficient Of LOS Channel )

      %Theta=atand(sqrt(sum((Tx-Rx).^2))/H_Room);

      HLOS = (Apd./hdist.^2).*cos(Incidence).*Ro;

      % Received Power By PhotoDetector

      Prx = HLOS.*Ptx;

      % Calculate Noise in System

      Bs = Rb*I2;

      Pn = Iamp/Rb;

      Ptotal = Prx+Pn;

      new_shot = 2*q*Ptotal*Bs;

      new_amp = Iamp^2*Bn;

      % Calculate SNR

      new_total = new_shot + new_amp;

      SNRl = (R.*Prx).^2./ new_total;

      SNRdb = 10*log10(SNRl);

%             else

%                     SNRl = 0;

%                     SNRdb = 0;

%             end

index = index + 1;

%     Plot Graph %

figure;

mesh(W,L,SNRdb);

%mesh(SNRdb);

%ylim([0 30]);

title('SNR Distribution in Room');

xlabel('Length of Room');

ylabel('Width of Room');

zlabel('SNR in dB');

[Muso]

Thanks you so much, it was helpful

[abdullah qasim]

thank u

[pratik panchal]

if this helpful for you upvote my answer

[Rashi Gautam]

Can you please help me with code for outdoor VLC as in for vehicle to vehicle will be more helpful but at this point anything related to VLC outdoor or if any minor changes in this code

[Shimelis Abebe]

Hello Dear, I truly need your help on a Machine Learning-based Hybrid VLC/RF networks implementation code, which I need to resolve by these months.

Sincerely,

Shimelis.

[abdullah qasim]

he fact that I do not have it but I hope to learn it if you get it please send it to me

[e-mail]

and if I got it I will send it to you

[pratik panchal]

Hi guys thank you for your responce. But i left this Application now. So cant give you update more.

[sarah ayashm]

sorrry, but what's the HLED?

[Walter Roberson]

Good question @sarah ayashm . It is not at all obvious to me what any of the h* variables refer to.

[pratik panchal]

HLED is height of LED.

[Alessandro Petroni]

%% clear environment
clc; clear all; close all;
%% parameters setting
Psi     = 70;               % LED half-power semiangle [degree]
rho     = 0.95;             % Reflection coefficient
A_pd    = 1e-04;            % Physical area of the PD [m^2]     % [C2022]
T_of    = 1;                % Optical Filter Gain
a       = 1.5;              % Refractive index
Phi_FoV = 70;               % Field of view [degree]
B       = 20e3;             % System bandwidth [Hz]
R_pd    = 0.53;             % Responsivity [A][m^2] / [W] -> %R_pd    = 0.53; %(Sensitivity) [A/W]
q       = 3;                % Conversion ration of optical-to-electrical power
N       = 10e-21;           % Power spectral density [A^2/Hz]
%p       = 5;               % transmission power [Watt]   % [SAA+2022]%[SCA+2022]
p       = 8.78;             % transmission power 6000 [Lumens] -> [Watt] ???????????????????????
% noise parameter
q_0     = 1.602e-19;        % electronic charge [Coulombs]
I_bg    = 84e-6;            % background light current [A] -> 84 [µA]
k_B     = 1.38064852e-23;   % Boltzmann constant [Joule/Kelvin]
T_k     = 295;              % absolute temperature [K]
G_0     = 10;               % open-loop voltage gain
eta     = 1.12e-6;          % fixed capacitance of photo detector per unit area [F/m^2]
Gamma   = 1.5;              % FET channel noise factor
g_m     = 0.030;            % FET transconductance [Siemens] [mS]
I_2     = 0.562;            % noise BW factor
I_3     = 0.0868;           % noise BW factor
% room size
x_max       = 4;            % room size x-axis         % [SCA+2022]
y_max       = 4;            % room size y-axis         % [SCA+2022]
z_max       = 3;            % room size z-axis         % 3 in [SCA+2022]
granularity = 0.1;          % plot accuracy
number_of_samples = 150;
% plot info
PLOT3D_enabled              = 0;
PLOT2D_enabled              = 1;
single_entity_d_estimation  = 0;
Entity_enabled              = [1 0 0 0 0]; % LED - RIS - RIS2 - RIS3 - RIS4
estimate_position_section   = 1;
number_of_plot_needed       = 18;
% tilt info
alpha   = 0;
beta    = 0;
%% set entities position
LED     = [x_max/2     , y_max/2      , z_max  ];
RIS1    = [x_max/2      , 0            , z_max/2+0.3*z_max];
RIS2    = [0            , y_max/2      , z_max/2+0.3*z_max];
RIS3    = [x_max        , y_max/2      , z_max/2+0.3*z_max];
RIS4    = [x_max/2      , y_max        , z_max/2+0.3*z_max];
%% Estimate light power
matrix_size = [length(0:granularity:x_max), length(0:granularity:y_max), length(0:granularity:z_max)];
distance_error_check = struct();
distance_error_check.LED = struct();
distance_error_check.RIS1 = struct();
impulseMatrix = zeros(matrix_size);
overlap_info =  zeros(matrix_size);
%dataRateMatrix = zeros(matrix_size);
x_probe = 0:granularity:x_max;
y_probe = 0:granularity:y_max;
z_probe = 0:granularity:z_max;
x_len = length(x_probe);
y_len = length(y_probe);
z_len = length(z_probe);
tic;
%PDect = struct();
%data rate (scelto da me)
R_b1 = 35560; %espresso in bit/s
R_b2 = 266600;   
%esprimo in questo modo queste matrici, perchè "NaN" è un valore speciale utilizzato per rappresentare dati mancanti o non validi in Matlab.
%Queste matrici possono poi essere utilizzate per memorizzare e manipolare i dati in un contesto specifico all'interno dello script.
%receivedPowerMatrix         = nan(x_len, y_len, z_len);
%noiseMatrix                 = nan(x_len, y_len, z_len);
SNR1                        = nan(x_len, y_len, z_len);
SNR2                        = nan(x_len, y_len, z_len);
lowerBoundDataRateMatrix    = nan(x_len, y_len, z_len);
for x_index = 1:x_len
    for y_index = 1:y_len
        for z_index = 1:z_len
            PDect = [x_probe(x_index), y_probe(y_index), z_probe(z_index)];
            
            % se attivato rallenta di molto il processo di calcolo
            if PLOT3D_enabled
                plotCube(LED, RIS1, RIS2, RIS3, RIS4, PDect, x_max, y_max, z_max);
            end
            
            [impulseMatrix(x_index,y_index,z_index), overlap_info(x_index,y_index,z_index)] = ...
                drawChannelResponse...
                (Psi, LED, RIS1, RIS2, RIS3, RIS4, PDect, Phi_FoV, A_pd, T_of, rho, a, Entity_enabled, alpha, beta );
            %potenza ricevuta 
            receivedPowerMatrix(x_index,y_index,z_index) = impulseMatrix(x_index,y_index,z_index) * (R_pd) * p;
            
            %rumore
            [n_shoot, n_thermal, var_shoot, var_thermal] = noiseEstimation(receivedPowerMatrix(x_index,y_index,z_index), q_0, R_pd, k_B, T_k, eta, I_2, I_3, Gamma, A_pd, g_m, I_bg, G_0, B);
            potenza = receivedPowerMatrix(x_index,y_index,z_index)
            noise = sqrt(var_shoot + var_thermal)
            noiseMatrix(x_index,y_index,z_index) = sqrt(var_shoot + var_thermal); %assegnamento del valore di noise alla posizione specificata
            
            % nuova matrice delle potenze (potenza ricevuta) = potenza (p) * R_pd * impulseMatrix //numeratore della funzione SNR 
            % per ogni valore contenuto nella matrice delle potenze
            % calcolare il rumore
            % esempio calcolo rumore: 
            % noiseEstimation(potenza_ricevuta, q_0, R_pd, k_B, T_k, eta,I_2, I_3, Gamma, A_pd, g_m, I_bg, G_0, B);
            % ci servono i primi 2 output della funzione, cioè shoot noise
            % e termhal noise e questo rappresenta N0
            %
            % SNR = log10(Potenza/rumore) 
            %
            % plot SNR in 3D
            % plot DataRate in 3D
            lowerBoundDataRateMatrix(x_index,y_index,z_index) = lowerBoundDataRate(impulseMatrix(x_index,y_index,z_index), B, p, R_pd, q, N);
        end
    end
end

Unrecognized function or variable 'drawChannelResponse'.

%rapporto segnale rumore
SNR1 = (receivedPowerMatrix) ./ (R_b1 * noiseMatrix(x_index,y_index,z_index));
SNR2 = (receivedPowerMatrix) ./ (R_b2 * noiseMatrix(x_index,y_index,z_index));
%disp(SNR1);
%disp(SNR2);
toc;

%plot section
% Crea una griglia tridimensionale per gli assi x, y e z
[x, y, z] = meshgrid(x_probe, y_probe, z_probe);

% Visualizza SNR1
figure;
mesh(x, y, z, SNR1);
xlabel('X');
ylabel('Y');
zlabel('Z');
title('SNR1');

% Visualizza SNR2
figure;
mesh(x, y, z, SNR2);
xlabel('X');
ylabel('Y');
zlabel('Z');
title('SNR2');

[Alessandro Petroni]

Hi, I have a similar problem to solve for my studio. I calculated my SNR from an online formula. But what I'm focusing on and would like some help is the 3D plot of the result of the 2 calculated SNRs (SNR1 e SNR2). In the plot section, after the run of the script, matlab gives me an error and doesn't plot the 3D graph I need. I share the whole script to better understand everything.

[Alessandro Petroni]

@pratik panchal can you help me with my problem?

[Alessandro Petroni]

or someone else? @Walter Roberson

[Walter Roberson]

@Alessandro Petroni we do not have your drawChannelResponse() to test with.

SNR1 = (receivedPowerMatrix) ./ (R_b1 * noiseMatrix(x_index,y_index,z_index));
SNR2 = (receivedPowerMatrix) ./ (R_b2 * noiseMatrix(x_index,y_index,z_index));

Those statements are after all three for loops, so the values of x_index, y_index, z_index will be whatever they were last set to -- x_len, y_len, z_len in this case. So you would be dividing the matrix by a scalar.

If you were to calculate

temp = receivedPowerMatrix) ./ noiseMatrix(x_index,y_index,z_index);

then you would have

SNR1 = temp ./ R_b1;
SNR2 = temp ./ R_b2;

Are you sure that is correct, that the two are linear scalings of each other?

[Alessandro Petroni]

@Walter Roberson yes, the applied formula and calculations for the SNR are correct and already checked.

the problem remains the plot of that SNR, being a 41x41x31 three-dimensional matrix. How can I model this matrix to be able to display correctly with the mesh function?

[Walter Roberson]

@Alessandro Petroni

See volshow and https://www.mathworks.com/help/images/ref/volumeviewer-app.html

That is, in order to plot 3 independent variables and one dependent variable, you are probably getting into volume viewing techniques, unless you want to draw isosurface

Answer 2

[Désiré_RM]

Hello dears. I sincerely need your help on NOMA-VLC code for power allocation and number of users considered to complete my work.

Sincerely!