Section 1.
Digital Communication and signal processing (30059)
- MSc assignment 2018-19
The assignment forms 50% of the final mark.
1. Each student should prepare a brief essay presented in a scientific paper format and style on a specific
topic of statistical signal generation and processing in communication systems. The format of the essay
is formulated in the Section 4 of this document
2. Each student will have an individual task, taken from the Section 2 of this document.
3. All the assignment shall have the same structure:
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4. Introduction: To formulate the gaol of the study and to draw the system/sub-system block diagram.
Section 1: To explain the system operational principles including a small literature review and
mathematical description of the signal and noise presented in your system as well as an analytical
equations for the system performance evaluation.
Section 2: To draw the system model chart and explain the meaning of all blocks in the chart as well
as show the main signals at the blocks input and output in time domain and frequency domains. For
all random signals shall be presented figures with their power spectral density and probability density
function. For all deterministic signals shall be presented graphs with their spectrum and time domain
waveform.
Section 3: Comparison of analytical and modelling results.
Conclusion 4: Based on Section 3 results.
Appendix: Appendix with the programme codes is compulsory for all students.
The main text of the essay length should be between 2000 (minimum) and 3000 (maximum) words
plus Tables (not more than 4), Figures (not more than 12) and, if necessary, appendixes which
should not exceed 3 pages in total. All shall be prepared in accordance to IEEE paper presentation
standard presented in the Section 4 of this document.
5. Students are expected to show their ability to understand the subject area and the specified problem as
well as to demonstrate their technical communication and computer modelling skills. The essay should
be self-sufficient for readers.
6. The assessment criteria are at the last page of this document
Plagiarism, which includes, but is not limited to, a failure to acknowledge sources will be penalised.
Submission: Please use an electronic submission. The assignment should be converted in PDF. Late
submission will be penalised at 5% per day late. A schedule for the demonstrations will be arranged to suit
each person once the summer term timetable for revision lectures has been published.
The main recommended book: “Wireless Communications – Principles and Practice”, T. Rappaport,
Prentice Hall, 1996 and later edition as well as the lecture notes.
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Section 2.
The topics are:
1. 1977317
Analysis and simulation of a communication system with 8-ary Quadrature Amplitude Modulation (QAM). BER vs
Bit/Noise ratio should be simulated for BER 10-2 and 10-3
for computer generated Additive White Gaussian Noise.
Symbol rate 4.8 KS/s.
2. 1906728
Analysis and simulation of a communication system with 16-ary Quadrature Amplitude Modulation (QAM). BER vs
Bit/Noise ratio should be simulated for BER 10-2 and 10-3
for computer generated Additive White Gaussian Noise.
Symbol rate 2.4 KS/s, carrier.
3. 1908270
Analysis and simulation of a communication system with 4-ary Phase Shift Keying (PSK) modulation. BER vs
Bit/Noise ratio should be simulated for BER 10-2 and 10-3
for computer generated Additive White Gaussian Noise.
Bit rate 16 Kbit/s.
4. 1891765
Analysis and simulation of a communication system with 8-ary Phase Shift Keying Modulation (PSK).
BER vs Bit/Noise ratio should be analytically obtained and be simulated for BER 10-3
for computer generated
Additive White Gaussian Noise; 16 K samples per second. It shall be generated the noise and shown its
characteristics in time and frequency domain at the input and output of matched filter. In addition the simulated 8-
ary PSK signal in time and frequency domain shall be shown for the sequence 0010 1110 0101 0100 01110.
5. 1918928
Analysis and simulation of a communication system with Minimum Phase Shift Keying (MSK) modulation. BER vs
Bit/Noise ratio should be simulated for BER 10-2 and 10-3
for computer generated Additive White Gaussian Noise
without pulse shaping. Bit rate 4.8 Kbit/s
6. 1971022
Analysis and simulation of a communication system with Quadrature Phase Shift Keying (QPSK) modulation.
BER vs Bit/Noise ratio should be simulated for BER 10-2 and 10-3
for computer generated Additive White
Gaussian Noise without pulse shaping. Bit rate 4.8 Kbit/s
7. 1887218
Analysis and simulation of a communication system with Gaussian pulse shaping technique for Minimum Phased
Shift Keying (MSK) modulation for the shape factors α=0.2. BER vs Bit/Noise ratio should be simulated for BER
10-2 and 10-3
for computer generated Additive White Gaussian Noise. Bit rate 24 Kbit/s
8. 1964710
Analysis and simulation of a communication system with Quadrature Phase Shift Keying (QPSK) modulation with
Raised Cosine Rolloff Filter with α=0.5. BER vs Bit/Noise ratio should be simulated for BER 10-2 and 10-3
for
computer generated Additive White Gaussian Noise. Bit rate 4.8 Kbit/s
9. 1967289
Analysis and simulation of a communication system with Code Division Multiple Access (CDMA). Simulate signal
reception at a background of N interferences using M-sequences for signal spreading with the length M=1023.
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BER vs N (Number of Interferences) should be simulated for BER 10-2 and 10-3
for computer generated Msequences,
presumably 4
Analysis and simulation of a communication system with Code Division Multiple Access (CDMA). Simulate signal
reception at a background of N interferences using M-sequences for signal spreading with the length M=511. BER
vs N (Number of Interferences) should be simulated for BER 10-2 and 10-3
for computer generated M-sequences,
presumably 2
Analysis and simulation of a communication system with Code Division Multiple Access (CDMA). Simulate signal
reception at a background of N interferences using M-sequences for signal spreading with the length M=255. BER
vs N (Number of Interferences) should be simulated for BER 10-2 and 10-3
for computer generated M-sequences,
presumably 1
Analysis and simulation of synchronization channel operating with 13 Barker code Phase Shifted Signal 0.02
microseconds per chip with 5 GHz carrier frequency at the background of Additive White Gaussian Noise for the
false alarm rate 10-3 and 10-4
.
13. 1950646
Analysis and simulation and of one channel of Direct Satellite TV systems. BER vs Bit/Noise ratio should be
simulated for BER 10-2 and 10-3
for computer generated Additive White Gaussian Noise.
14. 1971449
Analysis and simulation of one channel (satellite to ground) in Low Earth Orbiting Satellite mobile communication
system IRIDIUM. BER vs Bit/Noise ratio should be simulated for BER 10-2 and 10-3
for computer generated
Additive White Gaussian Noise.
15. 1692710
Analysis and simulation of spread spectrum technique in GPS navigation system. One channel with 1023 Msequence
spreading should be simulated at a background of Additive White Gaussian Noise and N=4
interferences for BER 10-2 and 10-3
.
16. 1906577
Analysis and simulation of one channel of Zig Bee transceivers. BER vs Bit/Noise ratio should be simulated for
BER 10-2 and 10-3
for computer generated Additive White Gaussian Noise.
17. 1964341
Analysis and simulation of a communication system with Differential Quadrature Phase Shift Keying (D-QPSK)
modulation. BER vs Bit/Noise ratio should be simulated for BER 10-2 and 10-3
for computer generated Additive
White Gaussian Noise without pulse shaping. Bit rate 2.4 Kbit/s
18. 1899925
Analysis and simulation and of one channel of Direct Satellite TV systems. BER vs Bit/Noise ratio should be
simulated for BER 10-2 and 10-3
for computer generated Additive White Noise with uniform probability density
function
19. 1904633
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Analysis and simulation of a communication system with Differential Binary Phase Shift Keying (DBPSK)
modulation. BER vs Bit/Noise ratio should be simulated for BER 10-2 and 10-3
for computer generated Additive
White Gaussian Noise without pulse shaping. Bit rate 4.8 Kbit/s
20. 1922963
Analysis and simulation of a communication system with Binary Amplitude Shift Keying (ASK) modulation and
coherent signal processing. BER vs Bit/Noise ratio should be simulated for BER 10-2 and 10-3
for computer
generated Additive White Gaussian Noise without pulse shaping. Bit rate 128 Kbit/s
21. 1800899
Analysis and simulation of one channel of Bluetooth wireless connection. BER vs Bit/Noise ratio should be
simulated for BER 10-2 and 10-3
for computer generated Additive White Gaussian Noise.
22. 1896859
Analysis and simulation of a communication system with Quadrature Amplitude Modulation (QAM) M=32. BER vs
Bit/Noise ratio should be simulated for BER 10-2 and 10-3
for computer generated Additive White Gaussian Noise.
Bit rate 32 Kbit/s.
23. NON – see example
Analysis and simulation of a communication system with Binary Amplitude Shift Keying (ASK) modulation and
non-coherent (post detector) signal processing. BER vs Bit/Noise ratio should be simulated for BER 10-2 and 10-3
for computer generated Additive White Gaussian Noise without pulse shaping. Bit rate 64 Kbit/s
24. 1721956
Analysis and modelling of a baseband communication system with Manchester - 2 coding – decoding. By means
of computer simulation evaluate the BER for computer generated Additive White Noise with uniform probability
density function. Data rate 1028 Kbit/s.
25. 1892829
Analysis and modelling of a baseband communication system with Manchester - 1 coding – decoding. By means
of computer simulation evaluate the BER for computer generated Additive White Gaussian Noise. Data rate 4.8
Kbit/s.
26. 1967052
Analysis and simulation of one channel (satellite to ground) in Inmarsat Satellite mobile communication system
IRIDIUM. BER vs Bit/Noise ratio should be simulated for BER 10-2 and 10-3
for computer generated Additive
White Gaussian Noise
27. 1902931
Analysis and simulation of one channel of Bluetooth transceivers. BER vs Bit/Noise ratio should be simulated for
BER 10-2
to 10-3
for computer generated Additive White Gaussian Noise.
28 1917093
Analysis and simulation of a communication system with 8-ary Phase Shift Keying (PSK) modulation. BER vs
Bit/Noise ratio should be simulated for BER 10-2 and 10-3
for computer generated Additive White Gaussian Noise.
Bit rate 32 Kbit/s.
29 1897594
Analysis and simulation of a communication system with 16-ary Quadrature Amplitude Modulation (QAM). BER vs
Bit/Noise ratio should be analytically obtained and be simulated for BER 10-3
for computer generated Additive
White Gaussian Noise; 4 M samples per second. It shall be generated the noise and shown its characteristics in
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time and frequency domain at the input and output of matched filter. In addition the simulated 16-ary QAM signal
in time and frequency domain shall be shown for the sequence 1100 0101 0010 1101 0101 0000 1100.
30 1883446
Analysis and modelling of a baseband communication system with Manchester - 2 coding – decoding. By means
of computer simulation evaluate the BER (10-3 – 10-4
) for computer generated Additive White Gaussian Noise.
Data rate 256 Kbit/s.
31 1891833
Analysis and simulation of a communication system with Quadrature Amplitude Modulation (QAM) M=64. BER vs
Bit/Noise ratio should be simulated for BER 10-2 and 10-3
for computer generated Additive White Gaussian Noise.
Bit rate 2048 Kbit/s.
32 1934273
Analysis and simulation of a communication system with π/2 Quadrature Phase Shift Keying (π/2-QPSK)
modulation. BER vs Bit/Noise ratio should be simulated for BER 10-2 and 10-3
for computer generated Additive
White Gaussian Noise without pulse shaping. Bit rate 1024 Kbit/s
33 1896155
Analysis and simulation of a communication system with Gaussian Minimum Shift Keying (GMSK). BER vs
Bit/Noise ratio should be analytically obtained and be simulated for BER 10-3
for computer generated Additive
White Gaussian Noise. It shall be generated the noise and shown its characteristics in time and frequency domain
at the input and output of matched filter. In addition the simulated GMSK signal in time and frequency domain
shall be shown for the sequence 1000 0101 1110 1101 0101 0101 1101.
34 1894313
Analysis and simulation of a communication system with Differential Binary Phase Shift Keying (DBPSK)
modulation. BER vs Bit/Noise ratio should be simulated for BER 10-2 and 10-3
for computer generated Additive
White Gaussian Noise without pulse shaping. Bit rate 64 Kbit/s. In addition the simulated DBPSK signal in time
and frequency domain shall be shown for the sequence 1110 1101 0101 0101 1101 1010 0001 1110.
35 1974007
Comparative analysis of spectrum and waveforms (time domain) of Binary Phase Shift Keying (BPSK) and Offset
Quadrature Shift Keying (QPSK) modulations. It shall be estimated BER vs Bit/Noise ratio computer simulated
for BER 10-3
for computer generated Additive White Gaussian Noise.
36 1903035
Analysis and simulation and of one channel of Direct Satellite TV systems. BER vs Bit/Noise ratio should be
simulated for BER 10-2 and 10-3
for computer generated Additive White Noise with Gaussian probability density
function and data rate 1,200 Kbit/sec
37 1874515
Analysis and simulation of a communication system with Code Division Multiple Access (CDMA). Simulate signal
reception at a background of N interferences using M-sequences for signal spreading with the length M=4,095.
BER vs N (Number of Interferences) should be simulated for BER 10-2 for computer generated M-sequences,
presumably 8
Analysis and simulation of a communication system with Binary Amplitude Shift Keying (ASK) and Raised Cosine
Rolloff Filter modulation (with α factor 0, 0.5 and 1) and coherent signal processing. BER vs Bit/Noise ratio
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should be simulated for BER 10-2
for computer generated Additive White Gaussian Noise without pulse shaping.
Bit rate 32 Kbit/s
39
Analysis and simulation of one channel of Bluetooth transceivers. BER vs Bit/Noise ratio should be simulated for
BER 10-2
for computer generated Additive White Gaussian Noise. Generate and show in time (waveform) and
frequency (spectrum) domain this signal for the code: 1110 1101 0101 0101 1101 1010 0001 1110.
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Section 3.
Example of the contents:
Typical example of an essay topic – "Analysis and simulation of communication system with Amplitude
Shift Keying modulation", which may include:
1. Definition of ASK and an area of applications
2. Analytical equations which describe ASK signal
3. Definition of baseband and bandpass signals in the system.
4. The modulation and demodulation processes description.
5. Examples of ASK signal with time domain and frequency domain presentations
6. Analytical equations which describe BER in ASK based systems.
7. Calculations of BER using the equations
8. Signal modelling (Signal generation using computer).
9. Show the signal waveform and spectrum
10. Noise modelling (Gaussian noise generation using computer).
11. Show the noise Power Spectral Density (PSD)
12. Signal and noise processing in the demodulator (with matched filter)
13. BER modelling for 10-2 and 10-3
14. Comparisons of modelling (m) and calculation (g) results
15. Conclusions
This is an example only!!! Students should not expect any detailed instruction and are free how
to present the specified problem.
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Section 4.
Template: (one column!) of the MSc assignment "Communication Signal Processing" – Principles of
communications, corresponds to the template of papers submission to IEEE transactions journal.
Abstract—(Arial 9) These instructions give you guidelines for preparing papers for IEEE TRANSACTIONS and JOURNALS. Use
this document as a template if you are using Microsoft Word 6.0 or later. Otherwise, use this document as an instruction set. The
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abstract. Do not delete the blank line immediately above the abstract; it sets the footnote at the bottom of this column.
Keywords – (Arial 9) e.g. communication systems, bit error rate, etc.
I Introduction (from this point all the text body is in Aerial 10, titles Aerial 11, bold, subtitles Aerial 11,
Italic )
HIS document is a template for Microsoft Word versions 6.0 or later.
If your paper is intended for a conference, please contact your conference editor concerning acceptable word
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Format and save your graphic images using a suitable graphics processing program that will allow you to create the
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Import your source files in one of the following: Microsoft Word, Microsoft PowerPoint, Microsoft Excel, or Portable
Document Format (PDF); you will be able to submit the graphics without converting to a PS, EPS, or TIFF files. Image
Manuscript received October 9, 2001. (Write the date on which you submitted your paper for review.) This work was supported in part by the U.S. Department of
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title. Full names of authors are preferred in the author field, but are not required. Put a space between authors’ initials.
F. A. Author is with the National Institute of Standards and Technology, Boulder, CO 80305 USA (corresponding author to provide phone: 303-555-5555; fax: 303-
555-5555; e-mail: author@ boulder.nist.gov).
S. B. Author, Jr., was with Rice University, Houston, TX 77005 USA. He is now with the Department of Physics, Colorado State University, Fort Collins, CO 80523
USA (e-mail: [email protected]).
T. C. Author is with the Electrical Engineering Department, University of Colorado, Boulder, CO 80309 USA, on leave from the National Research Institute for
Metals, Tsukuba, Japan (e-mail: [email protected]).
ASSIGNMENT TITLE
Student name, ID number and the date of submission
T
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IV MATH
If you are using Word, use either the Microsoft Equation Editor or the MathType add-on (http://www.mathtype.com) for
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equations in your paper (Insert | Object | Create New | Microsoft Equation or MathType Equation). “Float over text” should
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V Units
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).”
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density B or magnetic field strength symbolized as μ0H. Use the center dot to separate compound units, e.g., “A·m2
.”
VI Helpful Hints
A. Figures and Tables
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1, for example, write “Magnetization (A/m)” or “Magnetization (A
m1
),” not just “A/m.” Do not label axes with a ratio of
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Capitalize only the first word in a paper title, except for proper nouns and element symbols. For papers published in
translation journals, please give the English citation first, followed by the original foreign-language citation [8].
C. Abbreviations and Acronyms
Define abbreviations and acronyms the first time they are used in the text, even after they have already been defined in
the abstract. Abbreviations such as IEEE, SI, ac, and dc do not have to be defined. Abbreviations that incorporate periods
should not have spaces: write “C.N.R.S.,” not “C. N. R. S.” Do not use abbreviations in the title unless they are
1
It is recommended that footnotes be avoided (except for the unnumbered footnote with the receipt date on the first page). Instead, try to integrate the footnote
information into the text.
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unavoidable (for example, “IEEE” in the title of this article).
D Equations
Number equations consecutively with equation numbers in parentheses flush with the right margin, as in (1). First use
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of a sentence, as in
exp( | |) ( ) ( ) .
( , ) [ /(2 )]
(1)
Be sure that the symbols in your equation have been defined before the equation appears or immediately following.
Italicize symbols (T might refer to temperature, but T is the unit tesla). Refer to “(1),” not “Eq. (1)” or “equation (1),” except
at the beginning of a sentence: “Equation (1) is ... .”
VII Other Recommendations
Use one space after periods and colons. Hyphenate complex modifiers: “zero-field-cooled magnetization.” Avoid
dangling participles, such as, “Using (1), the potential was calculated.” [It is not clear who or what used (1).] Write instead,
“The potential was calculated by using (1),” or “Using (1), we calculated the potential.”
Use a zero before decimal points: “0.25,” not “.25.” Use “cm3
,” not “cc.” Indicate sample dimensions as “0.1 cm ? 0.2
cm,” not “0.1 ? 0.2 cm2
.” The abbreviation for “seconds” is “s,” not “sec.” Do not mix complete spellings and abbreviations
of units: use “Wb/m2
” or “webers per square meter,” not “webers/m2
.” When expressing a range of values, write “7 to 9” or
“7-9,” not “7~9.”
A parenthetical statement at the end of a sentence is punctuated outside of the closing parenthesis (like this). (A
parenthetical sentence is punctuated within the parentheses.) In American English, periods and commas are within
quotation marks, like “this period.” Other punctuation is “outside”! Avoid contractions; for example, write “do not” instead of
“don’t.” The serial comma is preferred: “A, B, and C” instead of “A, B and C.”
If you wish, you may write in the first person singular or plural and use the active voice (“I observed that ...” or “We
observed that ...” instead of “It was observed that ...”). Remember to check spelling. If your native language is not English,
please get a native English-speaking colleague to carefully proofread your paper.
VIII Some Common Mistakes
The word “data” is plural, not singular. The subscript for the permeability of vacuum μ0 is zero, not a lowercase letter
“o.” The term for residual magnetization is “remanence”; the adjective is “remanent”; do not write “remnance” or “remnant.”
Use the word “micrometer” instead of “micron.” A graph within a graph is an “inset,” not an “insert.” The word
“alternatively” is preferred to the word “alternately” (unless you really mean something that alternates). Use the word
“whereas” instead of “while” (unless you are referring to simultaneous events). Do not use the word “essentially” to mean
“approximately” or “effectively.” Do not use the word “issue” as a euphemism for “problem.” When compositions are not
specified, separate chemical symbols by en-dashes; for example, “NiMn” indicates the intermetallic compound Ni0.5Mn0.5
whereas “Ni–Mn” indicates an alloy of some composition NixMn1-x.
Be aware of the different meanings of the homophones “affect” (usually a verb) and “effect” (usually a noun),
“complement” and “compliment,” “discreet” and “discrete,” “principal” (e.g., “principal investigator”) and “principle” (e.g.,
“principle of measurement”). Do not confuse “imply” and “infer.”
Prefixes such as “non,” “sub,” “micro,” “multi,” and “ultra” are not independent words; they should be joined to the words
they modify, usually without a hyphen. There is no period after the “et” in the Latin abbreviation “et al.” (it is also italicized).
The abbreviation “i.e.,” means “that is,” and the abbreviation “e.g.,” means “for example” (these abbreviations are not
italicized).
An excellent style manual and source of information for science writers is [9]. A general IEEE style guide and an
Information for Authors are both available at http://www.ieee.org/web/publications/authors/transjnl/index.html
IX Publication Principles
The contents of IEEE TRANSACTIONS and JOURNALS are peer-reviewed and archival. The TRANSACTIONS publishes
scholarly articles of archival value as well as tutorial expositions and critical reviews of classical subjects and topics of
current interest.
P a g e | 12
Authors should consider the following points:
1) Technical papers submitted for publication must advance the state of knowledge and must cite relevant prior work.
2) The length of a submitted paper should be commensurate with the importance, or appropriate to the complexity, of the
work. For example, an obvious extension of previously published work might not be appropriate for publication or
might be adequately treated in just a few pages.
3) Authors must convince both peer reviewers and the editors of the scientific and technical merit of a paper; the
standards of proof are higher when extraordinary or unexpected results are reported.
4) Because replication is required for scientific progress, papers submitted for publication must provide sufficient
information to allow readers to perform similar experiments or calculations and use the reported results. Although not
everything need be disclosed, a paper must contain new, useable, and fully described information. For example, a
specimen’s chemical composition need not be reported if the main purpose of a paper is to introduce a new
measurement technique. Authors should expect to be challenged by reviewers if the results are not supported by
adequate data and critical details.
5) Papers that describe ongoing work or announce the latest technical achievement, which are suitable for presentation
at a professional conference, may not be appropriate for publication in a TRANSACTIONS or JOURNAL.
X Conclusion
A conclusion section is not required. Although a conclusion may review the main points of the paper, do not replicate
the abstract as the conclusion. A conclusion might elaborate on the importance of the work or suggest applications and
extensions.
APPENDIX
Appendixes, if needed, appear before the acknowledgment.
ACKNOWLEDGMENT
The preferred spelling of the word “acknowledgment” in American English is without an “e” after the “g.” Use the
singular heading even if you have many acknowledgments. Avoid expressions such as “One of us (S.B.A.) would like to
thank ... .” Instead, write “F. A. Author thanks ... .” Sponsor and financial support acknowledgments are placed in the
unnumbered footnote on the first page, not here.
REFERENCES
[1] G. O. Young, “Synthetic structure of industrial plastics (Book style with paper title and editor),” in Plastics, 2nd ed. vol. 3, J. Peters, Ed. New
York: McGraw-Hill, 1964, pp. 15–64.
[2] W.-K. Chen, Linear Networks and Systems (Book style). Belmont, CA: Wadsworth, 1993, pp. 123–135.
[3] H. Poor, An Introduction to Signal Detection and Estimation. New York: Springer-Verlag, 1985, ch. 4.
[4] B. Smith, “An approach to graphs of linear forms (Unpublished work style),” unpublished.
[5] E. H. Miller, “A note on reflector arrays (Periodical style—Accepted for publication),” IEEE Trans. Antennas Propagat., to be published.
[6] J. Wang, “Fundamentals of erbium-doped fiber amplifiers arrays (Periodical style—Submitted for publication),” IEEE J. Quantum Electron.,
submitted for publication.
[7] C. J. Kaufman, Rocky Mountain Research Lab., Boulder, CO, private communication, May 1995.
[8] Y. Yorozu, M. Hirano, K. Oka, and Y. Tagawa, “Electron spectroscopy studies on magneto-optical media and plastic substrate interfaces
(Translation Journals style),” IEEE Transl. J. Magn.Jpn., vol. 2, Aug. 1987, pp. 740–741 [Dig. 9th Annu. Conf. Magnetics Japan, 1982, p. 301].
[9] M. Young, The Technical Writers Handbook. Mill Valley, CA: University Science, 1989.
[10] J. U. Duncombe, “Infrared navigation—Part I: An assessment of feasibility (Periodical style),” IEEE Trans. Electron Devices, vol. ED-11, pp. 34–39,
Jan. 1959.
[11] S. Chen, B. Mulgrew, and P. M. Grant, “A clustering technique for digital communications channel equalization using radial basis function
networks,” IEEE Trans. Neural Networks, vol. 4, pp. 570–578, Jul. 1993.
[12] R. W. Lucky, “Automatic equalization for digital communication,” Bell Syst. Tech. J., vol. 44, no. 4, pp. 547–588, Apr. 1965.
[13] S. P. Bingulac, “On the compatibility of adaptive controllers (Published Conference Proceedings style),” in Proc. 4th Annu. Allerton Conf. Circuits
and Systems Theory, New York, 1994, pp. 8–16.
[14] G. R. Faulhaber, “Design of service systems with priority reservation,” in Conf. Rec. 1995 IEEE Int. Conf. Communications, pp. 3–8.
[15] W. D. Doyle, “Magnetization reversal in films with biaxial anisotropy,” in 1987 Proc. INTERMAG Conf., pp. 2.2-1–2.2-6.
[16] G. W. Juette and L. E. Zeffanella, “Radio noise currents n short sections on bundle conductors (Presented Conference Paper style),”
presented at the IEEE Summer power Meeting, Dallas, TX, Jun. 22–27, 1990, Paper 90 SM 690-0 PWRS.
[17] J. G. Kreifeldt, “An analysis of surface-detected EMG as an amplitude-modulated noise,” presented at the 1989 Int. Conf. Medicine and Biological
Engineering, Chicago, IL.
[18] J. Williams, “Narrow-band analyzer (Thesis or Dissertation style),” Ph.D. dissertation, Dept. Elect. Eng., Harvard Univ., Cambridge, MA, 1993.
[19] N. Kawasaki, “Parametric study of thermal and chemical nonequilibrium nozzle flow,” M.S. thesis, Dept. Electron. Eng., Osaka Univ., Osaka, Japan,
1993.
P a g e | 13
[20] J. P. Wilkinson, “Nonlinear resonant circuit devices (Patent style),” U.S. Patent 3 624 12, July 16, 1990.
[21] IEEE Criteria for Class IE Electric Systems (Standards style), IEEE Standard 308, 1969.
[22] Letter Symbols for Quantities, ANSI Standard Y10.5-1968.
[23] R. E. Haskell and C. T. Case, “Transient signal propagation in lossless isotropic plasmas (Report style),” USAF Cambridge Res. Lab., Cambridge,
MA Rep. ARCRL-66-234 (II), 1994, vol. 2.
[24] E. E. Reber, R. L. Michell, and C. J. Carter, “Oxygen absorption in the Earth’s atmosphere,” Aerospace Corp., Los Angeles, CA, Tech. Rep. TR-
0200 (420-46)-3, Nov. 1988.
[25] (Handbook style) Transmission Systems for Communications, 3rd ed., Western Electric Co., Winston-Salem, NC, 1985, pp. 44–60.
[26] Motorola Semiconductor Data Manual, Motorola Semiconductor Products Inc., Phoenix, AZ, 1989.
[27] (Basic Book/Monograph Online Sources) J. K. Author. (year, month, day). Title (edition) [Type of medium]. Volume (issue). Available:
http://www.(URL)
[28] J. Jones. (1991, May 10). Networks (2nd ed.) [Online]. Available: http://www.atm.com
[29] (Journal Online Sources style) K. Author. (year, month). Title. Journal [Type of medium]. Volume(issue), paging if given. Available:
http://www.(URL)
[30] R. J. Vidmar. (1992, August). On the use of atmospheric plasmas as electromagnetic reflectors. IEEE Trans. Plasma Sci. [Online]. 21(3). pp. 876–
880. Available: http://www.halcyon.com/pub/journals/21ps03-vidmar
First A. Author (M’76–SM’81–F’87) and the other authors may include biographies at the end of regular
papers. Biographies are often not included in conference-related papers. This author became a Member
(M) of IEEE in 1976, a Senior Member (SM) in 1981, and a Fellow (F) in 1987. The first paragraph may
contain a place and/or date of birth (list place, then date). Next, the author’s educational background is
listed. The degrees should be listed with type of degree in what field, which institution, city, state, and
country, and year degree was earned. The author’s major field of study should be lower-cased.
The second paragraph uses the pronoun of the person (he or she) and not the author’s last
name. It lists military and work experience, including summer and fellowship jobs. Job titles are
capitalized. The current job must have a location; previous positions may be listed without one.
Information concerning previous publications may be included. Try not to list more than three books or
published articles. The format for listing publishers of a book within the biography is: title of book (city,
state: publisher name, year) similar to a reference. Current and previous research interests end the
paragraph.
The third paragraph begins with the author’s title and last name (e.g., Dr. Smith, Prof. Jones,
Mr. Kajor, Ms. Hunter). List any memberships in professional societies other than the IEEE. Finally, list
any awards and work for IEEE committees and publications. If a photograph is provided, the biography
will be indented around it. The photograph is placed at the top left of the biography. Personal hobbies
will be deleted from the biography.
PHOTO
The photo is
not
compulsory.
P a g e | 14
30059 Section 5.
Digital communication and signal processing
Prof M Cherniakov and Prof M Gashinova
Student: Mark Max
Demonstration of the problem and the concept understanding as a part of the broader
concept of Digital Communication. Ability to specify the problem and define the proper
way of the problem investigation
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Distinct.
Merit
Pass
Fail
/ 20
Creativity of the material presentation, i.e. original approach, graphs, figures,
examples, etc. Understanding of how to select a proper literature and use of the
literature.
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Distinct.
Merit
Pass
Fail
/ 20
Proper and clear explanation and presentation of the specified problem.
Technical communication skills, i.e. clarity of the mathematical presentation, the
introduction and conclusion of arguments, correspondence to the recommended to
the assignment template.
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Distinct.
Merit
Pass
Fail
/ 20
Demonstration of computer modelling skills, that include the model flow chart,
language (software package) selection and the modelling simulation skills application
to the given problem solution
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Distinct.
Merit
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Fail
/ 20
Ability to draw and clearly formulate conclusions which are essentially based on the
results comparison with the known from literature as well as the results
correspondence to general knowledge obtained by the students from the lecture
course as well as other related disciplines.
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Distinct.
Merit
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Fail
/ 20
Marker name: Professor M. Cherniakov / M. Gashinova December 2018
/100
Any evidence of plagiarism YES NO
Comments:
P a g e | 15
Good Practice
Example of a similar assignment but not for Communication
Signal Processing
This is an example how the essay shall look like
NON-COHERENT BINARY ASK COMMUNICATION SYSTEM
Abstract— This report demonstrates a non-coherent binary amplitude shift keying communication system with a data rate
of 64Kbps. In detailed analysis of binary ASK system is presented followed by the design, simulation and modelling of the
system in MATLAB and Simulink. To observe the effect of variable channel noise in the overall performance of system,
designed model is simulated in the presence of AWGN with an Eb/ No of 1-15dB. Noise analysis has also been performed to
demonstrate the parameters of white Gaussian noise. Comparison between simulation results and theoretical results show
that the designed system performs well in the presence of AWGN noise.
Keywords – binary ASK, non-coherent, BER, AWGN, digital modulation
I. INTRODUCTION
Digital modulation is advantageous over the analog counterpart because of its high noise immunity, high spectral
efficiency, efficient multiplexing, software implementation and greater security.
Basic aim of this research is to demonstrate a binary amplitude shift keying (BASK) communication system in the
medium with an additive white Gaussian noise having various values of Eb/No (Energy per bit to noise power) thereby,
demonstrating the variation in BER with Eb/No as the BASK signal propagates.
BASK is digital modulation technique in which, data communication is performed using two amplitude levels i.e. 1 and
0. The carrier is transmitted when the bit is 1 whereas, no transmission is done for bit 0. As the modulated signal is
transmitted through the medium, the effect of channel noise is introduced in the transmitted signal. BASK modulation
scheme is comparatively simpler in comparison to other digital modulation schemes; therefore, the effect is channel noise
is prominent. Because of this, the bit error rate for a binary amplitude shift keying system is more in comparison to FSK,
PSK, QAM modulation schemes. Due to an intrinsic high bit error rate (BER), when a BASK system is designed, it is
essential to have an efficient detection of the input bits at the receiver due to the effect of a dominant channel noise.
In the designed system, to pass the required signal bandwidth and to limit the channel noise (AWGN) bandwidth, a
band-pass and a low-pass filter is used in first stage of receiver. BPF suppresses AWGN at the receiver thereby,
improving the overall bit error rate. Whereas the LPF is used for envelop detection. The designed LPF has a cut off
frequency of 5Hz with an out of band rejection of 30dB. If the cutoff frequency is reduced, the performance of LPF in
suppressing the noise enhances. However, there is a practical limitation on the cut off frequency of a LPF because of
which, the frequency cannot be further reduced from 5Hz. Sampling frequency also affects the performance of filter. The
higher the sampling frequency, better is the performance of filter in terms of noise removal. However, there is again a limit
up to how much the sampling frequency of filter can be increased. Higher sampling frequency makes the overall design of
communication system complex. In the designed filter for the BASK system, sampling frequency is set at 100Hz.
P a g e | 16
Generic block level diagram of ASK communication system in Figure 1 consists of a transmitter where BASK
modulation is performed on the input bit stream, a transmission medium where noise is added to the system and a
receiver where demodulation is performed to retrieve the transmitter bit stream. Comparison of transmitted and detected
bit stream of performed to determine the BER.
II. LITERATURE REVIEW
A. Digital Modulation
Modulation is a process in which the information from source is encoded by up converting it to a band pass signal with
a frequency higher than the baseband signal. Modulation is performed by translating or keying the amplitude, frequency or
phase of the carrier having higher frequency according to the amplitude of baseband signal. To extract baseband signal
from the continuous carrier signal, demodulation is performed.
B. Digital Modulation Schemes
Different types of digital modulation schemes are shown in Figure 2.
C. Maximum Data Rate
The maximum possible data rate in any transmission medium is given by Shannon’s channel capacity equation [1].
(1)
Where,
C= Channel Capacity in bps
B= Signal Bandwidth
S/N= Signal to noise ratio
D. Binary Amplitude Shift Keying
Figure 1: Block Diagram of a generic Binary ASK Communication System
Figure 2: Types of Digital Modulation Schemes
P a g e | 17
BASK commonly known as on-off keying (OOK) is modulation scheme in which a digital signal is expressed as carrier
amplitude’s variation. It is narrow band modulation in which amplitude of a continuous high frequency carrier is varied
according to amplitude of input binary data.
i.Modulation
In ASK system, baseband information is unipolar binary data with information as 0’s and 1’s. Bit 1 is transmitted with a
high frequency carrier whereas for bit 0 no transmission is done. ASK waveform can be mathematically represented as:
(2)
The input bit stream with 16 symbols, sinosoidal carrier and ASK modulated signal to be transmitted is shown in Figure
3.
ii.Transmission Medium
Transmission medium constitutes of various types of noise, which affects the modulated signal. If the strength of noise
if large, received signal is corrupted thereby, giving errors. There are different types of noise as shown below.
Band limited white noise
The PSD of this noise is constant over the defined bandwidth. The signal is corrupted when noise level is greater than
the decision threshold leading to bit error.
Additive White Gaussian Noise
AWGN replicates the effect of random processes occurring in the medium.
o Additive: Noise is added to the transmitted signal
o White: Flat spectrum for all frequencies
o Gaussian: Noise follows Gaussian probability distribution [2]
Figure 3: Input bit stream, carrier signal and BASK modulated signal
P a g e | 18
(3)
With μ=0 and
iii. Demodulation
Received signal can now be represented as:
Rx = Tx + No (4)
Where,
Rx = Received signal
Tx = Transmitted modulated signal
No = Channel noise
Demodulator reduces the channel corrupted waveform to a series of symbols which estimates the transmitted data
bits. On the basis of a threshold, it maps the received signal to digital bits. Demodulator only needs to determine the
presence or absence of carrier therefore, it’s a simple process. Signal detection is of two main types [3]:
Coherent Detection (Synchronous Detection)
o Receiver’s carrier and transmitter carrier are phase locked
o Correlation between received noisy signal and locally generated signal detects the transmitted signal
o Expensive and complex carrier recovery required
o Improved BER
Non-coherent Detection (Asynchronous Detection)
o Phase locking not required between transmitter and receiver carrier
o Simpler signal recovery process
o High probability of BER
E. Bit error rate (BER)
It is the ratio of total error bits and the transmitted bits, affected by the following factors:
o Channel noise
o Inter symbol interference
o Distortion
o Bit synchronization
o Signal attenuation
o Multi path Fading
BER is expressed as normalized signal to noise ratio or Eb/No. BER vs SNR (Eb/No) curves are plotted to express the
performance of a digital system.
The received signal is represented by:
Y=s1+n : bit 1 transmitted (s1=1)
Y=so+n : bit 1 transmitted (so=0)
P a g e | 19
The two conditional probabilities for bit detection can be represented by [4]:
(5)
(6)
If magnitude of received signal Y is greater than the threshold, the detected bit is 1 whereas, if the magnitude of
received signal Y is less than threshold, it is expected that the transmitted bit is 0. The amplitude of modulated symbol is
represented as:
Hence,
(7)
(8)
The signal space of binary ASK system is in single dimension.
The distance between two signal points is represented by:
Therefore, the probability of error is:
BER of non-coherent ASK is mathematically represented as [5]:
(9)
BER of coherent ASK is mathematically represented as:
(10)
F. BASK Constellation Diagram
P a g e | 20
Constellation diagram of an ASK signal can be represented as:
The x-axis is reference for the in phase signal whereas, y-axis displays the
quadrature component. As the quadrature component is absent in BASK system,
so the constellation diagram shows only the in-phase component along x-axis.
G. Power Efficiency
It is the ability of modulation scheme to preserve signal with low power levels and is expressed as [1]:
H. Bandwidth Efficiency
It is the capacity of modulation technique to limit data within a defined band and is represented as:
Where,
Rb: bit rate in bps
B: bandwidth of modulated RF signal
I. Power Spectral Density (PSD)
PSD demonstrates signal’s frequency response by plotting the frequency vs power. It shows the spectral power of all
the frequency contents within a signal.
J. Pulse Shaping
It is performed using specialized pulse shaping filters in the transmitter to decrease the interference between the
signals by increasing the channel bandwidth. It helps to filter out the spectrum’s side lobes as shown in Figure 4.
K. Comparison
Figure 4: Signal Spectrum before and after pulse shaping
P a g e | 21
An efficient modulation technique should exhibit following characteristics:
Low BER at less SNR
Power and bandwidth efficiency
Good performance in the presence of multipath fading
Utilize less bandwidth
Less complex and cost effective
L. Applications of ASK System
The applications of an ASK communication system are mentioned below:
Transmission of digital information in an optical fiber
Short range military communication
Early telephone modem up to 1200bps on voice grade lines
Used in RF systems for the transmission of Morse code
III. BASK SYSTEM
A. Systematic Block Diagram
P a g e | 22
The detailed block diagram is ASK communication system is shown in Figure 5.
B. Signal Modelling
System modelling is performed in Matlab and Simulink. The Matlab code is attached in Appendix A. ASK system is
composed of a transmitter, transmission medium and a receiver described below.
i. Transmitter
Band Pass
Filter
Figure 5: Systematic Block Diagram of ASK Communication System
P a g e | 23
BASK modulation is performed in the transmitter through the steps mentioned below. The ASK modulated waveform is
shown in Figure 3.
a) Signal Generation
Modulating baseband signal is expressed as a series of symbols or bits in the time domain. Each symbol represents
the information of n bits where,
N = log2m bits/symbol (11)
For the ease of representation, 16 symbols are considered in the design with 4000 bits in each symbol to achieve a
data rate of 64Kbps.
b) Carrier Generation
A continuous high frequency sinusoidal carrier is generated. The frequency of carrier should be greater than that of
baseband signal otherwise, the signal detection results in large BER at the receiver.
c) ASK Modulation
ASK modulation can be performed using a switch which only passes the carrier when the input bit is 1. When the input
bit is 0, no carrier is passed. The spectrum of ASK transmitted signal is shown in Figure 6.
ii. Channel
AWGN is added in the transmission medium. The system’s performance is analyzed in three scenarios.
a) No AWGN
When no noise is added to the system the received waveform is exactly like the transmitted waveform.
b) A constant AWGN with Eb/ No or SNR of 10dB
c) A variable AWGN with Eb/ No or SNR of 1-15dB
Figure 6: Spectrum of transmitted ASK waveform before and after AWGN
P a g e | 24
The received waveform after adding the AWGN with SNR of 1-15dB is shown in Figure 7.
iii. Receiver
In the BASK receiver, signal detection is performed to retrieve the transmitter bit information.
a) Band Pass Filtration
Band pass filter is used as the first stage of receiver to reduce the noise effects.
b) Rectification
The input signal to rectifier is multiplied with itself which rectifies the output. Therefore, only the positive side of
waveform is received at the output of rectifier.
c) Filtration
A low pass filter reduces the effect of noise from rectified signal. A least square FIR filter is designed for the removal of
noise. LPF suppresses the higher noise frequency. Rectification and filtration combines to detect the envelop of received
signal.
d) Comparator
The comparator delivers a digital output of the envelop detected signal on the basis of a threshold value. If the value of
signal is below threshold, the output is 0 whereas, the output is 1 is the value of signal is above threshold. The received
bit steam for AWGN with SNR 1-15dB is shown in Figure 8.
Figure 7: Received Signal after adding AWGN from Eb/ No = SNR 1=15dB and
filtration
P a g e | 25
e) BER
The transmitted bit stream is compared with detected bit stream to find the BER. Simulation results are then plotted
against the theoretical bit error rate for a non-coherent BASK system as shown in Figure 9. Analysis has been done for
BER 10-2 and 10-3
.
1.1.Simulink Model
Figure 8: BASK received Bit Stream with AWGN having Eb/ No = SNR 1-15dB
Figure 9: BER analysis for 10 -2 and 10-3 between theoretical and calculated results
P a g e | 26
The system modelling of ASK system is done in Simulink. Threshold for signal detection is set at 0.5. The Simulink
model is presented in Figure 10a whereas, the simulation results are presented in Figure 10b.
C. Noise Modelling
AWGN is represented by a random process with a PDF having a Gaussian distribution and a constant PSD with a
value equivalent to noise power or variance. Noise has a constant mean and covariance is time invariant making it a wide
sense stationary process. The histogram of white noise is plotted to determine its PDF. The PDF is nearly equal to the
theoretical PDF represented by the following equation with a Gaussian distribution [4].
(12)
Figure 10a: Simulink Model of ASK communication system
Figure 10b: Simulation results of ASK system in Simulink
P a g e | 27
Autocorrelation function is a scaled signal with magnitude equal to the variance. MATLAB code for the noise modelling
is attached in Appendix B. Simulation results of noise modelling are shown in Figure 11.
PSD of a white noise shows that it has nearly fixed power in the entire band with a value equal to 6dB. Thereby, it is
confirmed that the generated white noise has a constant PSD.
Power = 10log10 (σ2
) =10log10 (4) =6 dB
IV. DESIGN ANALYSIS
A. BER Comparison
The comparison of BER calculated using theoretical formula in equation 10 and the simulated results is shown in Table
1. It is found that the BER of designed BASK system is nearly equal to the theoretical results. The results can also be
verified from Figure 9.dB
TABLE I
COMPARISON OF THEORETICAL AND CALCULATED BER FOR SNR 1-15 DB
Eb/ No or SNR
(dB)
BER Theoretical BER Calculated
1 0.331902666542877 0.527366314920639
2 0.278382207307438 0.4330396525850132
3 0.223823897295794 0.353271833286657
4 0.170651194356157 0.258898845230837
Figure 11: Noise Modelling of AGWN in MATLAB showing generated noise, PDF, ACF and PSD of noise
P a g e | 28
5 0.121709824615639 0.180549318689371
6 0.079814667661548 0.111318237100481
7 0.047093102397304 0.06586618958376
8 0.024325941089215 0.034328134289297
9 0.010627897188806 0.015034552398623
10 0.003760324064043 0.005151674628544
11 0.001020091579789 0.001287084315818
12 0.000198042813939 0.000250194125872
13 0.000025228735034 0.000032213359232
14 0.000001890569040 0.000002305326446
15 0.000000072627681 0.000000085308201
It is determined that for SNR from 1-6dB there is more difference between the simulated and theoretical results.
However, if SNR is increased further, the calculated results are almost equal to the theoretical results.
When the value of SNR is less, the signal to noise ratio is less which means that the difference between desired signal
and noise energy is quiet less therefore, it becomes difficult to distinguish the data bits from noise. As a result of this, the
BER is more when SNR is less.
B. BER for Different Modulation Schemes
An ASK system with non-coherent detection has high probability of error as compared to other digital modulation
schemes. Although it is a bandwidth efficient system, but its power efficiency is low resulting in poor noise immunity
thereby, high BER.
Table 2 shows the comparison of E0/ No (dB) values of different digital modulation schemes needed to achieve a BER
of 10-6
[6].
TABLE II
EB/ NO FOR DIGITAL MODULATION TECHNIQUES TO ACHIEVE BER OF 10-6
Modulation Scheme Eb/ No (dB)
BPSK 10.6
QPSK 10.6
4-QAM 10.6
D-BPSK 11.2
D-QPSK 12.7
8-PSK 14
BASK 14
16-QAM 14.5
16-PSK 18.3
64-QAM 18.8
P a g e | 29
32-PSK 23.3
C. BASK System
ASK transmitters are simple and efficient since power is not consumed for bit 0. Receiver complexity can be reduced
by using non-coherent detection.
As BER is high with an abrupt change in the amplitude of carrier at bit transition, therefore BASK is not spectrally
efficient and is limited to low or moderate data rates as compared to other digital modulation techniques. The threshold
detection depends upon the received signal’s amplitude, so BASK has poor performance in presence of fading. This limits
the BASK communication range.
D. BASK Spectral Efficiency
The PSD of binary ASK signal is of the form of which has distribution on both sides of the vertical axis.
Therefore, the bandwidth of a binary ASK system is double than the baseband bit stream’s bandwidth. Therefore,
B= =
The bandwidth of BASK system can be verified from the generalized spectrum shown in Figure 12. This is also called
the null to null bandwidth of an ASK modulated signal. As the quadrature component is wasted in an ASK modulation
scheme, therefore the spectral efficiency is half than that of the baseband unipolar signal. The spectrum is in the form of
sinc2
, which is similar to the one obtained for the designed system shown in Figure 6.
Spectrum of ASK modulated signal is centered on the carrier frequency whereas the spectrum of bit stream is spread
along the frequency band.
E. System Limitation
The noncoherent BASK system receiver often uses a band pass filter at the first stage of receiver with a bandwidth of
2/Tb Hz centered on the carrier frequency fC Hz. However, as the data rate is very high (64Kbps), the bit duration is quiet
low. Therefore, the design of such a band pass filter is a very tedious task for the required results. An increase in the data
rate reduces the symbol’s pulse width thereby, increasing signal bandwidth.
A half wave rectifier together with a LPF forms an envelope detector. The bandwidth of low pass filter is 2/Tb Hz. This
configuration is used to detect bit stream. In the Matlab code, an envelope command is used for half wave rectification
whereas, in the Simulink model, signal is multiplied with itself for rectification. Design of low pass filter is again a limitation.
A higher cutoff frequency is used to design a more practical filter with good results.
Figure 12: Bandwidth of an ASK signal
P a g e | 30
An analog comparator with a specific threshold voltage outputs the estimate of the received binary data. At low SNR,
the received signal has more BER because of the reason that it has high false detections. If the threshold is increased to
reduce the BER for low SNR, the BER of signal with high SNR is affected. Therefore, threshold is selected to maximize
the performance of the system for wide range of SNR values.
This noncoherent BASK demodulator is not optimal because the envelope detector and comparator are not equivalent to
correlation performed in coherent detection.
For Gaussian case Matched Filter detection is optimal because it maximizes the SNR of received signal and making it
apt for detection. Matched filter allows the detection of bits which are below the threshold. But for the matched filter, the
signal that is being detected should be known. Therefore, the coherent detection provides better BER as compared to
non-coherent detection without the use of a matched filter.
F. System Improvement
To enhance the performance of communication system, digital error control codes are often used to detect and correct
the error bits [7]. The system uses complex signal processing techniques like source coding, encryption and equalization
thereby, reducing the bit error rate. This is however out of scope for this research document. The system can be improved
by following techniques:
Increase in SNR by reducing the communication distance
Decrease in data rate
Decrease in bandwidth which reduces the data rate
Use of pulse-shaping filter which reduces the sharp amplitude transition among different bits
Band limiting the transmitted ASK thereby, reducing the bandwidth
G. Advantages and Disadvantages
1. Advantages
Employed in control applications due to simple architecture and cost effectiveness
Less power consumption as the transmitter is practically off during bit 0
Simple transmitter and receiver design
2. Disadvantages
Sharp discontinuities at the transition points between binary 1 and 0
Can be easily corrupted by noise
High BER
Low SNR
Inefficient to use for multiplexing
V. CONCLUSION
A binary ASK communication system with non-coherent detection is designed using MATLAB and Simulink. The
simulation results are presented in the report. It is observed that as the signal in an ASK signal is only transmitted for half
the time if there is a 50% probability for bit 1, therefore, there is a 3dB degradation in BER as compared to that in BPSK
system where the transmission is for complete communication duration.
P a g e | 31
The designed system is analyzed for various values of Eb/No and it is examined that the performance of system at high
Eb/No is nearly similar to the theoretical results. The data rate of assigned task is quiet high for an ASK non-coherent
system therefore, at low bit energy to noise ratio, there are more deviations in the system performance as compared to
the analytical results. This can be improved by using coherent detection and reducing the data rate.
As there are sharp discontinuities in the received ASK waveform, therefore it is implied that the bandwidth is high. This
might increase the BER. However, if a band limiting or pulse shaping of the message signal is done before modulation,
the sharp discontinuities can be avoided.
Noise Analysis performed shows that the PDF and ACF of the generated white noise are in accordance to the
theoretical results with a Gaussian PDF and an even ACF centered about 0. The PSD of noise is constant over the entire
band with a level of 6dB.
ASK systems are preferred in low cost systems with a short communication distance such as RFID. Pulse shaping by
the use of a band limited filter can improve the bit error rate. The side bands in spectrum can be eliminated by using a
pulse shaping filter.
APPENDIX A
Signal modelling m.file
clc; clear all; close all;
%% ----- BASEBAND SIGNAL PARAMETERS -----%%
D_R=64e3; %Data Rate = 64Kbps
P_D=1/D_R; %Pulse duration
%%% TRANSMITTER %%%%
% SIGNAL GENERATION
bits=16;
Input=rand(1,bits)>0.5;
Input=repmat(Input',1,4000)';
Input=Input(:)';
t=linspace(0,bits,numel(Input));
figure('Name','Transmitted Data')
subplot(3,1,1);
plot(t,Input,'r');
title('INPUT BIT STREAM');
xlabel('Samples');
ylabel('Amplitude');
grid on
% CARRIER GENERATION
DC=1/2;
Ao=3;
F=10;
Carrier=Ao.*sin(2*pi*F*t)+DC;
subplot(3,1,2);
plot(t,Carrier,'b');
title('CARRIER');
xlabel('Samples');
ylabel('Amplitude');
grid;
% ASK MODULATION
ModSig=Carrier.*Input;
subplot (3,1,3);
plot(t,ModSig);
title('BASK MODULATED SIGNAL');
xlabel('Samples');
ylabel('Amplitude');
grid;
P a g e | 32
% POWER SPECTRAL DENSITY:
[Pxx,F] = periodogram(ModSig,[],length(ModSig),D_R);
figure;
plot(F,10*log10(Pxx));
xlim ([0 500]);
%%%% TRANSMISSION MEDIUM %%%%
% ZERO NOISE
No=0;
RxSig_1=ModSig+No;
% FIXED AWGN
SNRdB_C=10;
RxSig_2=awgn(ModSig,SNRdB_C,'measured',10);
% MULTIPLE AWGN
for SNRdB_=1:1:15
RxSig_3=awgn(ModSig,SNRdB_,'measured',10);
end
L1=length(RxSig_1); L2=length(RxSig_2); L3=length(RxSig_3);
%%%% RECEIVER %%%%%
% LOW PASS FILTER TO REDUCE THE EFFECT OF NOISE
LPF = fdesign.lowpass('Fp,Fst,Ap,Ast',5,20,1,30,100);
lowpass = design(LPF,'equiripple');
%BAND PASS FILTER
[ A B C D] = butter(10,[1 5]/50);
d=designfilt('bandpassfir'
,'FilterOrder',20, ...
'CutoffFrequency1',1,'CutoffFrequency2',5, ...
'SampleRate',100);
% RECEIVED BIT STREAM WITHOUT NOISE
% RECEIVED SIGNAL
figure ('Name'
,'Received Bit Stream Without AWGN');
subplot (2,1,1);
plot(t,RxSig_1);
title('BASK RECEIVED SIGNAL WITH ZERO NOISE');
xlabel('Samples');
ylabel('Amplitude');
% COMPARATOR
for a=1:1:L1
if RxSig_1(a)==0
R1(a)=0;
else
R1(a)=1;
end
end
subplot(2,1,2)
plot(t,R1);
title('RECEIVED BIT STREAM WITHOUT NOISE');
xlabel('Samples'); ylabel('Amplitude');
% RECEIVED BIT STREAM WITH CONSTANT NOISE
% RECEIVED SIGNAL
figure('Name'
,'Received Bit Stream for Fixed Noise');
subplot (4,1,1);
plot(t,RxSig_2);
legend('Signal with fixed AWGN:SNR=10dB');
title('BASK MODULATED SIGNAL WITH FIXED AWGN OF 10dB');
xlabel('Samples'); ylabel('Amplitude');
% BAND PASS FILTER
R2_F1=filter(d,R2_R);
% RECTIFICATION
R2_R=envelope(R2_F1)
;
subplot(4,1,2)
plot(t,R2_R);
P a g e | 33
% FILTERATION
R2_F=filter(lowpass,R2_R);
subplot(4,1,3)
plot(t,R2_F);
% COMPARATOR
for b=1:L2
if R2_F(b)>2
R2(b)=1;
else
R2(b)=0;
end
end
subplot(5,1,5)
plot(t,R2);
%RECEIVED BIT STREAM WITH MULTIPLE AWGN: SNR IN dB=1
-15dB
figure('Name'
,'Received Signal After Multiple AWGN');
title('BASK RECEIVED SIGNAL WITH MULTIPLE AWGN');
for SNR_dB=1:1:15
% ADDING NOISE
RxSig3=awgn(ModSig,SNR_dB,'measured',10);
% FILTERATION
R3F1= filter(d,RxSig3);
R3F=filter(lowpass,R3F1);
subplot(4,4,SNR_dB)
plot(t,RxSig3,'g'
,'LineWidth',2);
hold on
;
plot(t,R3F,'b');
title(['SNR: ',num2str(SNR_dB),'dB']);
xlim([0 16]); ylim( [
-8 8]);
xlabel('Samples'); ylabel('Amplitude');
end
legend('Signal with AWGN'
,'Signal After Filteration');
h=1; i=1; j=1; k=1; l=1; m=1;
figure('Name'
,'RECEIVED BITS AFTER AWGN: SNR=1
-15dB');
title('BASK RECEIVED BIT STREAM WITH VARIABLE NOISE');
for SNR=1:1:15
snrlin=10.^(SNR./10);
RxSig_3=awgn(ModSig,SNR,'measured',10);
R3_F=filter(lowpass,RxSig_3);
% RECTIFICATION
R3_R=envelope(R3_F);
% COMPARATOR
for Sample=1:L3
if R3_R(Sample)>2
Rx_Bits(Sample)=1;
else
Rx_Bits(Sample)=0;
end
end
subplot(5,3,SNR)
plot(t,Rx_Bits);
title(['SNR: ',num2str(SNR),'dB']);
xlabel('Samples'); ylabel('Amplitude');
xlim( [0 16]);
%%%%% BER %%%%%
error=length(find(Rx_Bits~=Input));
cber(h)=error/64000;
h=h+1;
tber(i) = 0.5*exp(
-0.5*snrlin)+0.5*qfunc(sqrt(snrlin));
snrdb(j)=SNR;
P a g e | 34
j=j+1;
end
legend('BASK Received BITSTREAM with different AWGN');
%Plotting the theoretical and calculated BER
figure ('Name','Comparison B/W Theoretical & Calculated BER');
semilogy(snrdb,cber,'-bo',snrdb,tber,'-mh')
title('BER vs Eb/No or SNR in dB');
xlabel('Signal to noise ratio'); ylabel('Bit error rate');
APPENDIX B
Noise modelling m.file
clear all; clc; close all;
Length = 64000; % Gaussian Noise Signal Length
% WHITE NOISE
n_mean = 0; % Mean
SD = 2; % Standard Deviation
W_Noise = SD * randn (Length,1) + n_mean; %White Noise
figure;
subplot(4,1,1)
plot(W_Noise);
title(['White noise : \mu_x=',num2str(n_mean),' \sigma^2=',num2str(SD^2)])
xlabel('No. of Samples'); ylabel('Sample Value'); xlim ([0 64000]); grid on;
% NOISE PDF
subplot(4,1,2)
n = 200; %Total Histrogram Bins in the noise PDF
[f,x] = hist (W_Noise,n);
Bar (x,f/trapz(x,f)); hold on;
%Theoretical PDF of Gaussian Random Variable
T_PDF_WN = (1/(sqrt(2*pi)*SD)) * exp (-((x-n_mean).^2) / (2*SD^2));
plot (x,T_PDF_WN);hold off; grid on;
title ('Theoretical PDF and Simulated PSD of White Gaussian Noise');
legend ('Histograms','Theoretical PDF'); xlabel ('Histogram'); ylabel ('PDF f_x(x)');
% NOISE ACF
subplot (4,1,3)
ACF_W_N = 1/Length * conv (flipud(W_Noise), W_Noise);
lag = (-Length+1):1:(Length-1);
plot(lag , ACF_W_N);
title('ACF of White Noise'); xlabel('Lag'); ylabel('Auto-Correlation');
xlim ([-200 200]); grid on;
% VERIFICATION OF CONSTANT PSD
n_mean = 0;
SD = 2;
S_L = 1024;
% Random White Gaussian Noise
Avg_Mean = n_mean * ones(1,S_L);
Co_Var = (SD^2) * diag(ones(S_L,1));
Chol_Cov_M = chol(Co_Var);
% Multivariate Gaussian Distribution
z = repmat(Avg_Mean,Length,1) + randn(Length,S_L)* Chol_Cov_M;
S = 1/sqrt(S_L)*fft(z,[],2);
P_Avg = mean(S.*conj(S));
Norm_Freq = [-S_L/2:S_L/2-1]/S_L;
P_Avg = fftshift(P_Avg);
subplot (4,1,4)
P a g e | 35
plot (Norm_Freq,10*log10(P_Avg),'m');
axis ([-0.5 0.5 0 10]); grid on;
ylabel('PSD in dB/Hz'); title('PSD of AWGN');
xlabel ('Normalized Frequency');
ACKNOWLEDGMENT
I wish to express my sincere gratitude to Prof. Mike Cherniakov for providing me with an opportunity to work on this
research project and sincerely thank him and Emidio Marchetti for their guidance and encouragement in carrying out this
research project.
REFERENCES
[1] “Wireless Communications- Principles and Practice”, T. Rappaport, Prentice Hall, 1996
[2] Athanasios Papoulis, Probability, Random Variables, and Stochastic Processes, 3rd ed. WCB/McGraw-Hill, 1991
[3] “Coherent and Non-coherent Receivers”, Professor Sheng Chen, School of Electronics and Computer Science, University of Southampton.
[4] “Mobile Communication Systems” Professor Z Ghassemlooy Electronics & IT Division Scholl of Engineering, Sheffield Hallam University U.K.
[5] Y. Kim, S.-W. Tam, G.-S. Byun, H. Wu, L. Nan, G. Reinman, J. Cong, and M.-C. F. Chang, “Analysis of noncoherent ASK modulation-based RFinterconnect
for memory interface,” IEEE J. Emerg. Sel. Topics Circuits Syst., vol. 2, no. 2, pp. 200–209, Jun. 2012
[6] “Digital Communications” by John G.Proakis, Chapter 7: Channel Capacity and Coding
[7] “Error Control Techniques and Their Applications”, Chaudhary, Rubal & Gupta, Vrinda, International Journal of Computer Applications in
Engineering Sciences, Vol I, Issue II, June 2011
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