itgd3101modern telecommunications lecture-1- pulse code modulation week 1- s1/ 2009-2010 dr. anwar...
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ITGD3101Modern Telecommunications
Lecture-1- Pulse Code Modulation
week 1- S1/ 2009-2010
Dr. Anwar Mousa
University of PalestineFaculty of Information Technology
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DATE TOPICSWeek 1 Course description-Sampling Theorem
Week 2 Pulse Code Modulation
Week 3 Pulse Code Modulation
Week 4 Principles of Data transmission- Digital communications systems
Week 5 Line coding
Week 6 Line coding
Week 7 Pulse shaping
Week 8 Mid-Term Exam
Week 9 Detection-Error Probability
Week 10 M-ary communications
Week 11 Optimum Threshold Detection
Week 12 Signal space
Week 13 Optimum receiver
Week 14 Error Correcting Codes Linear Block Codes
Week 15 FINAL EXAM
Week 16 FINAL EXAM
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Instructor InformationOffice location:
Office hours:Email: [email protected]
Phone: 1115
Research interests:
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Textbook and SoftwareRequire textbook:
B.P. Lathi, Modern Digital and Analog Communication Systems, 3rd edition, Oxford University Press, 1998
Recommended readings Digital communications: J. Proakis, Digital Communications
Random process: G.R. Grimmett and D.R. Stirzaker, Probability and Random Processes
Estimation and detection: H.V. Poor, An introduction to Signal Detection and Estimation
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Homework, Project, and ExamHomework
1 assignment per week
Exams Two exams: Midterm and Final
Participations Attendance and Feedback
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Teaching StylesSlides plus Whiteboard
Slides can convey more information in an organized way
Whiteboard is better for equations and prevents you from not coming.
Course Website
Print handouts with 3 slides per page before you come
Homework assignment and solutions
Feedback
Too fast, too slow
Presentation
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Course Outline
(Chapter 6) Sampling and Pulse Code Modulation Sampling Theorem
Pulse Code Modulation (PCM)
(Chapter 7)
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Course Outline
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Course Outline
(Chapter 13) Behavior of Digital communication
systems in the presence of Noise Optimum Threshold Detection
Optimum Binary Receiver
M-ary Communications
(Chapter 14)
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Course Outline
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Course Outline
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Contents
Sampling theoremQuantization Pulse Code Modulation
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Aperiodic signal representation by Fourier Transform
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Today, we are going to talk about:
The first important step in any DCS:
Transforming the information source to a form compatible with a digital system
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EncodeTransmit
PulsemodulateSample Quantize
Demodulate/Detect
Channel
ReceiveLow-pass
filterDecode
PulsewaveformsBit stream
Format
Format
Digital info.
Textual info.
Analog info.
Textual info.
Analog info.
Digital info.
source
sink
Formatting and transmission of baseband signal
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Format analog signals
To transform an analog waveform into a form that is compatible with a digital communication, the following steps are taken:
1. Sampling
2. Quantization and encoding
3. Baseband transmission
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Sampling theorem
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Sampling theorem
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Sampling theorem
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Sampling theorem
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Sampling theorem
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Sampling theorem
Sampling theorem: A bandlimited signal with no spectral components beyond , can be uniquely determined by values sampled at
uniform intervals of
The sampling rate, is called Nyquist rate.
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Sampling theorem
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Sampling theorem
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Pulse Code Modulation (PCM).
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Pulse Code Modulation (PCM).
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Pulse Code Modulation (PCM).
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Quantization example
t
Ts: sampling time
x(nTs): sampled valuesxq(nTs): quantized values
boundaries
Quant. levels
111 3.1867
110 2.2762
101 1.3657
100 0.4552
011 -0.4552
010 -1.3657
001 -2.2762
000 -3.1867
PCMcodeword 110 110 111 110 100 010 011 100 100 011 PCM sequence
amplitudex(t)
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Pulse Code Modulation (PCM).
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Pulse Code Modulation (PCM).
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Pulse Code Modulation (PCM).
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Advantages of Digital Communications
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Advantages of Digital Communications
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Advantages of Digital Communications
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Summary
We have studies the following topics:Sampling theoremQuantization Pulse Code Modulation