# BER output problem for Radio over Fiber system/Optical Comm

• thavamaran
In summary, the conversation is about the speaker's first work in optical and first simulation in MATLAB. They apologize if there are any mistakes and mention that they are new to this. The speaker explains that they are simulating an entire Radio Over Fiber system with MATLAB, specifically using a linear system. They also mention the code they used for defining constant parameters and filters. They ask for clarification on the use of match filtering in their code and how it relates to the output they obtained.
thavamaran
Hi guys, this is my first work in optical and first simulation in matlab. I am sorry if there is mistake and I am really new to this.

Here is what I did, I am simulation an entire Radio Over Fiber system with Matlab, linear system.

Let me insert my code first,
Code:
%*****************************Defining constant parameter****************
%Rb = 1e+6; %bit rate
%Tb = 1/Rb; %bit duration / period
Num_bits = 1e4; %number of bits

nsamp = 20; %samples per symbols
%Tsamp = Tb/nsamp; %sampling rate, fsamp = 20MHz.
a = 0.2; %channel attenuation, dB/km
L = 20; % Length of fiber
Gain = 10; %Gain in dB

%*****************************Filter definations************************

snr_dB=0:20; %SNR in dB from 0 to 20

SNR=10.^(snr_dB./10); %SNR in linear scale

Tx_filter = ones(1,nsamp); %transmitter filter, in terms of
% h(t),match filter
Rx_filter = fliplr(Tx_filter/nsamp); % receiver filter (matched filter),
% flip from left to right to make
% it h(T-t), match filter

Tx_OOK = randint(1,Num_bits); % randomly generating 1 and 0 in a
% row of matrix for 1000
% column,basically ON-OFF keying
% with random bits

%*****************************Channel input*****************************
Tx_OOKin = 0+Tx_OOK; % Tx+with power, 0dBm,ideal.

%*****************************Channel properties************************

Txch = Tx_OOKin -(a*L); %Signal in channel, deducting with
%channel attenuation=4dB

Txout = 10.^(Txch./10); %Changing back the signal to linear
%scale

Tx_signal = rectpulse(Txout,nsamp); % generate rectpulse for nsamp time
% per symbol

for i=1:length(snr_dB)
Rx_signal = awgn(Tx_signal,snr_dB(i)+3-10*log10(nsamp),'measured');

%*****************************Match filtering***************************
MF_out = conv(Rx_signal,Rx_filter); %equivalent to y(t)=x(t)*h(t)

MF_out_downsamp = MF_out(nsamp:nsamp:end); %sampling and hold

%try without truncation

%*****************************Thresholding*******************************

Rxth = zeros(1,Num_bits); %Reset receiver before thresholding

Rxth(find(MF_out_downsamp>0.45))=1; %value above 0.45 equivalent to one

%*****************************BER CALC**********************************
ber(i) = biterr(Tx_OOK,Rxth); %Matlab function for ber
%******************Theoritical BER CALC**********************************
ber_pr(i) = Qfunct(sqrt(SNR(i))); %theoritical for ber
end

figure;
semilogy(snr_dB,ber,'b'); %Simulation
hold on;
semilogy(snr_dB,ber_pr,'r');
xlabel('SNR(dB)');
ylabel('BER');[/CODE]

Above is my entire code, the part i bold, i dun really get the idea, i took it from my friend cause at the receiver part, i don't really have an idea of how to receive the signal for at least with 10 different SNR rate and plot BER. My friend used the Match filter, but i don't really have the exact idea how match filter works.

The Tx_filter and Rx_filter part i got it where we flip the entire input from transmitter and at the receiver. which is h(t) from transmitter becomes h(-t).

I have uploaded the output and the blue line on the plot is the output that i got

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. So, i would like to ask what is the part i bold in my code, and how do i use match filtering to get the output that i got? I would highly appreciate if anyone could help me out and explain the concept behind in detail so that i can understand it better. Thank you very much in advance!

## 1. What is BER and why is it important in Radio over Fiber systems/Optical Comm?

BER stands for Bit Error Rate, and it is a measure of the error rate in a digital communication system. In Radio over Fiber systems/Optical Comm, BER is important because it helps determine the quality of the transmitted signal and the overall performance of the system. A lower BER indicates a better quality signal and a more reliable communication system.

## 2. What are the main causes of BER in Radio over Fiber systems/Optical Comm?

The main causes of BER in Radio over Fiber systems/Optical Comm include noise, distortion, and interference in the communication channel. These can be caused by factors such as imperfect components, environmental conditions, and system design. It is important to minimize these factors in order to reduce the BER and improve system performance.

## 3. How is BER measured in Radio over Fiber systems/Optical Comm?

BER is typically measured by sending a known sequence of bits through the system and comparing the received sequence with the transmitted one. The number of errors in the received sequence is counted and divided by the total number of bits to calculate the BER. This process is repeated multiple times to get an average BER value.

## 4. How can the BER output problem be mitigated in Radio over Fiber systems/Optical Comm?

There are several ways to mitigate the BER output problem in Radio over Fiber systems/Optical Comm. These include using high-quality components, optimizing the system design, implementing error control coding techniques, and using signal processing algorithms to reduce noise and distortion. Regular maintenance and monitoring of the system can also help identify and address any potential issues that may cause a high BER.

## 5. What is the acceptable BER threshold in Radio over Fiber systems/Optical Comm?

The acceptable BER threshold in Radio over Fiber systems/Optical Comm varies depending on the specific application and system requirements. In general, a BER of 10^-9 (one error every billion bits) is considered acceptable for most digital communication systems. However, for high-speed or critical applications, a lower BER of 10^-12 (one error every trillion bits) may be required.

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