1. 64-QAM Communications System Design and Characterization
Project #1
EE283

2. What you need to do (red)
Assignments:
1. Data Source (0)
Propose a data source that you will use for your communication system. Discuss the randomness of data.
2. 64-QAM Memoryless Channel Coder (25)
Design a channel coder with a code rate 1. The designed data source feeds the channel coder. The coder outputs are 64-QAM in-phase and quadrature-phase data. For example, with 6-bits taken from data source, an in-phase and a quadrature-phase amplitudes are produced.
3. QAM Base Band Modulation (25)
Design a QAM modulator. Modulator inputs are the output of 64-QAM channel coder and the modulation frequency, etc. The output is a modulated QAM waveform. Show unit in-phase, unit quadrature-phase, and random data waveforms in a fine time resolution (for readability).
4. Channel Modeling (0)
Design a channel module that adds Gaussian noise to the modulated data with a given noise intensity. Show a 64-QAM eye diagram.
5. QAM Base Band Demodulation (25)
Design a QAM demodulator. Assume that full phase information is given and the phase is locked. The demodulator outputs are in-phase and quadrature-phase amplitudes. Show a demodulated 64-QAM constellation with noise.
6. 64-QAM Channel Decoder (25)
Design a QAM decoder that performs the inverse of the designed 64-QAM channel coder.
7. BER Measurements (0)
Design a module calculates bit-error-rate with the original data source and the decoded data stream. Discuss how many measurements are required to get 95% or 99% confidence. Make a plot of BER vs SNR. All the numbers, such as signal power and noise power, must be obtained from simulation.
8. Bandwidth Efficiency (0)
Calculate the bandwidth efficiency with a given BER. All the numbers, such as bandwidth must be obtained from simulation. Discuss the definition of bandwidth of your baseband waveform.

3. Outline 64-QAM communications system Testing and measurements
Tools, grading, etc.

4. 64-QAM Communications System Design
Signal source and source coding
Channel coding
Baseband modulation
Channel modeling
Baseband demodulation
Channel decoding
Source decoding and signal sink
Simplified 64-QAM
communications system

5. Signal source and source coding
Ideal source coded data
“Random”
Memoryless source
Equiprobable
Spectrum and autocorrelation
A randomly generated data
What if the data is not random?

6. An example of 16-QAM mapping
64-QAM Channel Coding
2^6=64
Use rate 1 code
Map a sequence of 6-bits to 64 symbols
Symbol error
Bit error
An example of 16-QAM mapping

7. Baseband Modulation (1)
In-phase
Quadrature-phase

8. Baseband Modulation (2)
(-1,-1)
(-1,+1)
(+1,-1)
(+1,+1)

9. Baseband Modulation (3)
64-QAM waveform with random data

10. Baseband Modulation (4)
Sampling of waveform
Minimum samples per symbol
Number of waves per symbol
Orthogonal signals
[1 1] vs. [1 -1]
[ ] vs. [ ]

11. Channel Modeling Noise Additive White Gaussian
Contaminated baseband signal

12. Eye Diagram

13. Baseband Demodulation
Correlative receiver
Matched filter receiver
64-QAM Demodulated Data

14. Clock Recovery and Phase Locking
Clock recovery from baseband signal
Phase locking
Maintain constant clock and locked phase
Clock synchronization pilot signal
Assume perfect clock recovery and phase locking
64-QAM Demodulated with
perfect phase and 2.5% phase lag

15. Channel Decoding and Signal Sink
Inverse of channel coding
Simple hard decision
Signal Sink
Compare received and decoded data with signal source

16. Testing and Measurements
Obtain
64-QAM waveform
Eye diagram
Bit error rate
Bandwidth efficiency

17. Signal Power and SNR

18. Symbol / Bit Error Rate S/BER=Symbol or Bit Error / Tx-Rx Bits
How many symbols/bits to test for a given BER
How many measurements for a given BER
95% or 99% confidence interval
t-test
BER
SNR(dB)
An example of 64-QAM BER plot

19. Channel Bandwidth 3-dB bandwidth Or your definition and justification
Modulated 64-QAM spectrum

20. Theory vs. Practice Given BER plot vs. experimented BER plot
Given bandwidth efficiency vs. experimented bandwidth efficiency

21. Tools Any tools supported by ECE MATLAB recommended
C, C++, Java, Visual Basic, Perl, PHP…
Simulink ?

22. MATLAB (1) >> A=[0 1 2; 3 4 5] A = 0 1 2 3 4 5
>> A=(0:0.2:1)'
0.2000
0.4000
0.6000
0.8000
1.0000
>> plot(A,cos(2*pi*A))
>> ta=1:-0.01:0;
>> tb=(0:.01:1)';
>> ta+tb';
>> ta'.*tb;
>> ta.^2;
>> ta(1:10)=tb(11:20)’;
>> help
>> help elfun
>> lookfor signal
>> demo

23. MATLAB (2) Function call Flow control for N=1:10,
---;
end
if <true/false>,
else,
switch <var>
case <cond1>
case <cond2>
otherwise
Function call
function [Y,Z]=Name(X)
%Name.m
%Usage
%function Y=Name(X)
<Commands>
Y=1;
Z=2;
return;
>> Y=Name(1);
>> [Y,Z]=Name(2);

24. Matlab (3) Useful functions mean semilogx sum semilogy size loglog
length
zeros
ones
rand
randn
figure
plot
xlabel
ylabel
title
semilogx
semilogy
loglog
log10
log i j pi
round
ceil
floor
sgn
fft
spectrum

25. MATLAB (4) Vector operation vs. scalar operation
>> A=1:1e4; MeanSquare=mean(A.^2);
>> A=1:1e8;
Vector preparation before usage
>> A=zeros(1,100); for k=1:100, A(k)=k+1; end
>> for k=1:100, A(k)=k+1; end
>> A=[]; for k=1:100, A=[A k+1]; end

26. Things to submit Documentation Scripts
An electronic copy in PDF of PS format
IEEE journal format
Scripts execution methods
Scripts
“tar”ed and compressed scripts
“lastname_firstname.tar.gz” or “.tar.Z”
All scripts should be in “lastname_firstname” directory
Script execution must be one-step, i.e. ‘filename’+’enter’

27. Deadline Submit to dkim@ee.duke.edu 9/24 (Fri) 11:00pm
Time marked by the recipient server (ee.duke.edu)
Penalty for late submission without permission (-20% per a day)
No virus (frown per a virus)