1 Introduction
Communication Systems Coursework
The purpose of this coursework is to introduce some of the important tools in communication systems. In particular we will concentrate on modelling AWGN, modulation schemes and baseband transmission of data using different modulation schemes. This coursework will be performed using MATLAB software on a PC.
2 Getting Started
Before you can start MATLAB for windows, you must ensure that you are in the windows environment. Now double clicking on the MATLAB icon will launch MATLAB and cause a Command window to be opened with aprompt. Theprompt sign means MATLAB is waiting for your input and you can type the required commands for execution.
For example to enter a matrix A, simply type in the Command Window
A16 3 2 13; 5 10 11 8; 9 6 7 12; 4 15 14 1
MATLAB displays the matrix you just entered:
A
16 3 2 13
5 10 11 8 9 6 7 12 4 15 14 1
When you want to leave MATLAB, type exit. However if you want to stop but would like your results to be saved for the next session you need to use save to store all your variables. See Matlab help for further details on save and load.
save FILENAME saves all workspace variables to the binary MATfile named FILENAME.mat.
3 Demo
An interesting way to learn the features of MATLAB is through the MATLAB demonstration. Type demo and the demo menu will be displayed. You can select the demos of interest and follow the instructions.
4 Graphical Output
MATLAB graphics system provides a variety of sophisticated techniques for visualising data. The basic syntax is plotx,y,linetype which plots vector y against vector x with the specified linetype colour and marker.
For example to plot the first 100 elements of s type
srandn100,1;
plots1:100
The plot appears in a separate graphics window. We can add labels and title to this plot by typing xlabelSample , ylabelAmplitude , titleA random signal
semilogy is a Semilog scale plot. For example you can use it later on to plot BER curves: semilogyEbNo,ber,; Type help semilogy for more information
5 AWGN
There are a number of ways to add awgn to your simulation. Below are some useful functions:
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randn creates normally distributed random numbers.
Example nsigma randn50000,1jrandn50000,1; where sigma is the standard deviation of the noise
Example: sigmasqrt12SNR; standard deviation of AWGN
awgn adds white Gaussian noise to a signal. Type help awgn
berawgn gives the Bit error rate BER for uncoded AWGN channels theoretical curve. The berawgn function returns the BER of various modulation schemes over an additive white Gaussian noise AWGN channel. The first input argument, EbNo, is the ratio of bit energy to noise power spectral density, in dB. If EbNo is a vector, the output ber is a vector of the same size, whose elements correspond to the different EbNo levels.
Syntax
berberawgnEbNo,qam,M. Type help berawgn
6 Random Data
randint generates a matrix of uniformly distributed random integers. This will be useful to create your random data example 10000 data bits. You can then modulate the data BPSK or QPSK. For example a QPSK symbol might be 1j1.
Syntax
outrandint1,m where m is the number of random integeres
7 Rayleigh fading
berfading gives the theoretical Bit error rate BER for Rayleigh and Rician fading channels. See Matlab help for further details.
8 Coursework assignment using Matlab
a Plot the theoretical error probability for BPSK, QPSK and 16QAM in AWGN for different EbNo values. Explain why the performance of 16QAM is worse than QPSK. Comment on the data ratesspectral efficiency they can provide
Note: For this part, you can use the functions provided by Matlab see above or write your own code based on the equations for the theoretical error probability that can be found in your notes and a number of books on Communication Systems.
b Write a program in Matlab to perform a baseband simulation of a QPSK communication system in AWGN and compare the performance with the theoretical curves above create some random data to be transmitted. Explain the structure of the code and justify the matlab functions and parameters used.
c Plot the theoretical error probability for QPSK and 16QAM in Rayleigh fading.
d Discuss your results and suggest methods to improve the performance in AWGN or Rayleigh
fading environments.
9. Submission
You are required to submit a technical note report on the Matlab exercises detailed in section 8. In your report you should give detailed answers for all parts ad. The report must also include an appendix with your matlab programs.
Please submit your report by midday 12:00 on Friday 6th December 2019 via the letterbox in the School Office in 2.19 MVB.
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