UEE3504: Introduction to Communication Systemsshannon.cm.nctu.edu.tw/comtheory/background.pdf · 1...

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UEE3504: Introduction to Communication Systems

Po-Ning Chen, Professor Dept. of Electrical and Computer Eng. National Chiao Tung University

Background and Preview

To give you a basic understanding of communications

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© Po-Ning [email protected] Background 3

Figure-1 Theory

o  The next figure is always the “Figure 1” in every book regarding communications.


Communications

o What is communication (or more specifically, communication engineering)? n  The transmission of information from one point to

another through a succession of certain processes.

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Basic Elements Regard Communications

o  Source of information n  Voice, music, picture, or computer data



o  Transmitter n  Source → Source Symbol (i.e., Source Word)

o  Symbolize the information from a source n  Source Symbol → Code Word

o  Encode the source symbol so that the other sources (i.e., noise and interfering signal) can hardly interfere the information transmission.

n  Code Word → Channel Symbol (i.e., Transmitted Signals) o  Modulate the code word into a form that is suitable for

transmission over the channel, which involves varying some parameter of a carrier wave in accordance with the message signal.

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o Noise/Interference n  Unwanted waves that tend to disturb the

transmission and processing of messages. n  Could be internal or external to the system. n  Could be additive or multiplicative (or both) to the

information-bearing signals.



o  Receiver n  Hard Decision

o  Channel Symbol → Code Bit o  Decode from Code Bits to Code Word o  Code Word → Source Symbol → Source

n  Soft Decision o  Decode from Channel Symbol to Code Word o  Code Word → Source Symbol → Source

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Example: Basic Elements Regard Communications

o  Source = An alphabet “A”


Example : Basic Elements Regard Communications

o  Transmitter n  Source “A” → Binary Source Symbol (01000001)

o  Symbolize the information from a source n  Source Symbol (01000001) → Code Word (000 111 000

000 000 000 000 111) o  Encode the source symbol by the three-times repetition code

so that the other sources (i.e., noise and interfering signals) can hardly interfere the information transmission.

o  001, 010, 011, 100, 101, 110 are not code words. Hence, their appearance is possible only when noise is introduced.

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n  Code Word (000 111 000 000 000 000 000 111) → Channel Symbol (000 555 000 000 000 000 000 555 ) o  Modulate the code word into some channel-permissible

(physical-medium permissible) symbols.

n  Due to Channel Interference, we receive: 010 442 222 033 011 020 032 434



o  Receiver n  Hard Decision

o  Channel Symbol 010 442 222 033 011 020 032 434 → Code Bit (Threshold 2.5) 000 110 000 011 000 000 010 111

o  Decode from Code Bits to Code Word (Majority Rule) 000 111 000 111 000 000 000 111

o  Code Word 000 111 000 111 000 000 000 111 → Source Symbol 01010001 → Source “Q”

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o  Receiver n  Soft Decision

o  Decode from Channel Symbol 010 442 222 033 011 020 032 434 to (channel-symbolized) Code Word 000 555 000 000 000 000 000 555 n  By finding the minimum distance to legitimate codewords

000 and 111. n  E.g., d(033, 000) = (0-0)2+(3-0)2+(3-0)2 = 18 d(033, 555) = (0-5)2+(3-5)2+(3-5)2 = 33

o  Code Word 000 111 000 000 000 000 000 111 → Source Symbol 01000001→ Source “A”


Basic Modes of Communications o  Broadcasting

n  Often, uni-directional. n  A single powerful transmitter to numerous

(inexpensive) receivers n  Example. Radio and TV.

o  Point-to-point communication n  Often, bi-directional. n  Two entities exchange information. n  Example. Telephone.

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Feature of Communications

o  Statistics n  The source is statistical in nature. n  The noise and interference are naturally random. n  Principles of Communication Engineering: How to

design a communication system only based on the knowledge of the statistics of the source and interferences (without knowing exactly what the true source and interference are)?


Feature of Communications o  Example

n  Source o  We do not know if the next source symbol is 0 or 1. o  But, we do know the probability of the next source

symbol being 0, and also, the probability of the next source symbol being 1.

n  Noise/Interference o  We do not know what value the noise/interference will

take? o  But, we do know the noise is, say, Gaussian

distributed.

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Feature of Communications

o  This is the reason why “Probabilities” (Chapter 1) is considered an important background to communication study.


Primary Communication Resources

o  Primary Communication Resources are something “known” at the design stage. n  As aforementioned, source and noise/interference

are (often) something “unknown” at the design stage.

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Primary Communication Resources o  Examples of Primary Communication Resources

n  Transmission Power o  Specifically, it’s the average power of the transmitted

signals. o  A more useful measure than the absolute transmission

power is the signal-to noise (power) ratio (SNR), defined as the ratio of the average signal power to the average noise power. This quantity is often expressed in decibel (dB), which is defined as 10 log10(SNR).

n  Channel Bandwidth o  The band of frequencies for use of transmitting

messages.


Primary Communication Resources

o Design principle of a communication system n  How to efficiently use (usually in a tradeoff

fashion) the communication resources!

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Sources of Information

o  “Sources” can sometimes be viewed as one kind of Communication Resources. n  For example, there are systems designed

specifically for “exchanging voices.” n  Such a system may not be apt to transmit computer

data. n  This introduces the subjects of “Source-Specific

Communication.” n  Next, we brief several sources commonly seen in

the literature.


Sources of Information: (1) Speech

o  Features n  Voice spectrum extends well beyond 10kHz. n  Most of the average power is concentrated in the

range of 100 to 600 Hz.

n  A band of 300 to 3100 Hz gives good articulation. n  The sound wave propagates through the air at a

speed of 300 meter/second.

Do Re Mi Fa So La Si Do 261.6 293.7 329.6 349.2 392.0 440 493.9 523 Freq (Hz)

Pitch Name

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Schematic representation of the vocal system



Sources of Information: (1) Speech o  The speech-production process may be viewed

as a form of filtering: n  A sound source excites a vocal tract filter.

D

D

a1

a9

a10

+

Excitation Speech

+

+

+

Lips

Vocal Tract

Glottal Volume

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Sources of Information: Speech

o As the sound propagates along the vocal tract, the spectrum (i.e., frequency content) is shaped by the frequency selectivity of the vocal tract —a resonance phenomenon observed in organ pipe.

o  So the hearing mechanism is (and should be) sensitive to frequency.


Source of Information: Music o Originate from musical instruments, such as

piano, violin, and flute. o  It consists of:

n  Melody: A time sequence of sounds. n  Harmony: A set of simultaneous sounds.

o Different from speech, the spectrum of a music source may extend up to about 15 KHz. n  Accordingly, a much wider bandwidth resource is

demanded.

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Source of Information: Pictures

o  Two dimensional information. o  Classifications

n  Dynamic pictures – Video, such as North American Audio TV (NAA-TV)

n  Still pictures – Facsimile. o  To transmit still picture over a telephone channel.


Source of Information: NAA-TV o North American Analog TV

n  525 horizontal lines, decomposed into two 262.5 line interlaced fields (See the next slide.)

n  Completion of each interlaced field takes 1/60 second o  Horizontal line-scanning frequency is 262.5/(1/60) =

15.75 KHz. n  Hence, 30 still pictures are shown per second. n  The human “persistence of vision” phenomenon

will perceive these still pictures to be moving pictures.

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Source of Information: NAA-TV

Interlaced raster scan.


Source of Information: NAA-TV n  In the NTSC (National Television System

Committee) system, a total of 4.2 MHz bandwidth is demanded for TV transmission.

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Source of Information: Computer Data

o  The first code developed specifically for computer communication (1967) – ASCII (American Standard Code for Information Interchange).



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o ASCII (American Standard Code for Information Interchange)

n  7-bit code for alphabetic numerical characters n  Bit 8 is sometimes used as parity-check bit or used

to form the extended ASCII code o  Even parity: Total number of 1’s is even. o  Odd parity: Total number of 1’s is odd.

n  Extended ASCII code can be displayed but cannot necessarily be printed out.

Bit originates from “Binary Digit.”



o  Since ASCII is defined for communication, it also includes some symbols for communication purpose such as n  ENQ (enquiry) – 05X n  ETB (end of transmission block) – 17X

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o  RS (Recommended Standard) -232 Transmission n  Synchronous n  Asynchronous



o Asynchronous Serial Data n  No clock or timing signal required. n  ST : start bit n  S : stop bit n  P : parity bit n  D6~D0 : data bits (often, exact one ASCII character) n  Usually, 10 bit frame with even-parity/7-data-bit or

no-parity/8-data-bit.

S ST D0 D1 D2 D3 D4 D5 D6 P S ST D0 D1 D2 D3 D4 D5 D6 P S

frame

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o  Synchronous Serial Data n  No start and stop bits required. n  P : parity bit n  D6~D0 : data bits (ASCII) n  Clock : Timing signal. n  Note that it requires sync character (after a certain

number of frames) to avoid losing synchronization. If two sync characters are used. it is called bi-sync.

D0 D1 D2 D3 D4 D5 D6 P D0 D1 D2 D3 D4Data Clock



o  Windows 98 n  Baud rate : 110 baud~921600

baud (The # is different for different computers)

n  (E)ven parity, (O)dd parity, (N)one-parity, Mark, Space

n  4~8 Data-bit n  1, 1.5, 2 Stop-bit

The name of “mark” and “space” for 1 and 0 comes from the days of telegraphy.

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o  The computer data stream so formed is then applied to a device called a modem (modulator-demodulator).

o Unlike source traffic from speech or video, the computer data is often bursty rather than continuous.


Missed Part of Figure-1 in Textbook

o  Source before entering the transmitter is often compressed (in order to save time or space).

o  This part is missing in Figure 1 of the textbook.

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With a source encoder, a digital communication system (rather than an analog communication system) is formed.


Data Compression o  Lossless Data Compression (or Data

Compaction) n  Completely reversible (or asymptotically

reversible). n  E.g., Lempel-Ziv algorithm (PKZIP, compress, etc),

which will be introduced in Chapter 9. o  Lossy Data Compression

n  Non-reversible with loss of information in a controlled manner.

n  E.g., JPEG, MPEG, etc.

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Lossy Data Compression for Images

o  JPEG (Joint Photographic Experts Group) n  An image coding standard n  Pixels are grouped in 8-by-8 block. n  DCT (discrete cosine transform) is then applied to

each block. n  Quantize each of the 64 DCT coefficients according

to a pre-specified table. n  Huffman-encode (introduced in Chapter 9) the

quantization results.


Lossy Data Compression for Images n  DCT

∑∑

∑∑

= =

= =

⎟⎠

⎞⎜⎝

⎛ +⎟⎠

⎞⎜⎝

⎛ +=

⎟⎠

⎞⎜⎝

⎛ +⎟⎠

⎞⎜⎝

⎛ +=

7

0

7

0

7

0

7

0

16)12(cos

16)12(cos),()()(

41),(

16)12(cos

16)12(cos),()()(

41),(

u v

x y

vyuxvuFvCuCyxf

vyuxyxfvCuCvuF

ππ

ππ

where

⎪⎩

⎪⎨⎧ =

=otherwise1

0for ,2

1)( uuC

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Lossy Data Compression for Video

o MPEG-1 (Motion Photographic Experts Group) video coding standard n  A video coding standard primarily for 30 fps

(frames per second) video n  Result in a bit-stream rate of 1.5 megabits per

second


Lossy Data Compression for Video n  Design objective : To reduce four kinds of

redundancies: o  Interframe (temporal) redundancy

n  Its reduction is achieved through the use of prediction to estimate each frame from its neighbors.

n  The resulting prediction error is transmitted for motion estimation and compensation.

o  Interpixel redundancy within a frame o  Psychovisual redundancy o  Entropic coding redundancy

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Lossy Data Compression for Video n  As with JPEG, the last three redundancies are

reduced through the combined use of DCT, quantization and lossless entropic coding.


Lossy Data Compression for Audio

o MPEG-1 audio coding standard n  A perceptual (waveform) coder, as contrary to a

vocoder o  The amplitude-time waveform of the decoded audio

signal closely approximates that of the original audio signal.

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Lossy Data Compression for Audio n  Encoding process

o  Time-Frequency Mapping (sub-band decomposition) o  Psychoacoustic modeling (operates according to the

psychoacoustic behavior of the human auditory system)

o  Quantization and coding o  Frame-packing (format the quantized audio samples

into a decodable bit stream)


Lossy Data Compression for Audio n  Why Psychoacoustic modeling?

o  Human ears have a perceptual phenomenon known as auditory masking.

o  Specifically, the human ear does not perceive quantization noise in a given frequency band if the average noise power lies below the masking threshold

o  The masking threshold varies with frequency across the band.

o  Hence, a perceptual weighting filter is applied to waveforms before quantization.

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o OSI

OSI (Open System Interconnection) model; the acronym DLC in the middle of the figure stands for data link control.


Communication Networks

o OSI reference model was developed by ISO (International Organization for Standardization) in 1977.

o  Figure 1 only concerns PHY layer. o Now we take a quick look of its relation with

higher layers, such as Network layers.

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Network Layer : Routers



o  Routing mechanisms n  Circuit Switching

o  Uninterrupted, exclusively use of links o  E.g., Telephone.

n  Packet Switching o  Shared-on-demand links

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o Why OSI reference model? n  Each layer can perform its related subset of

primitive functions without knowing the implementation details of the next lower layer.

n  The adjacent layers communicate through well-defined interfaces, which defines the services offered by the lower layer to the upper layer.


Communication Networks o  The entities that comprise the corresponding

layers on different systems are referred to as peer processes.

o  Two peer entities then communicate through a well-defined set of rules of procedures, named Protocol.

o  Again, this text/course primarily considers PHY layer.

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Internet

o  Internet – A special communication network, as contrary to an Intranet.

o  Features of Internet n  Applications are carried out independently of the

technology employed to construct the network. n  The network technology is capable of evolving

without affecting the applications.


Internet

o Architecture of Internet

Direct Data Exchange

Cross-Router Data Exchange

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Internet Protocol (IP)


Internet Service

o  Internet Service is “Best Effort” in nature. o As a consequence, no guarantees of timely

transmission, and even delivery.

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Communication Channels

o  Channels, where the noise/interference resides, can be roughly divided into two groups: n  Guided propagation channels

o  E.g., telephone channels, coaxial cables, and optical fibers

n  Free propagation channels o  E.g., broadcast channels, mobile radio channels, and

satellite channels


Communication Channels: (i) Telephone Channel

o  Features of telephone channel n  A channel performs “voice → electrical signal →

sound” n  Band-limited channel

o  A speech signal (male or female) is essentially limited to a band from 300 to 3100 Hz.

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o Measures used in characterizing channel n  Insertion loss = 10 log10 (P0/PL) dB

o  PL = power delivered to a load from a source via the channel o  P0 = power delivered to the same source not via the channel

PL

P0

Channel



n  Envelope delay o  The negative of the derivative of the phase response with

respect to the angular frequency ω = 2πf. o  Example. Envelope delay = a for the next channel.

fajefH π2)( −=)(tg )( atg −

)].(exp[|)(|)( fjfHfH β=The phase response of a channel filter H(f) is β(f), where

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Insertion Loss Envelope Delay


Communication Channels: (ii) Coaxial Cable

o A coaxial cable offers a greater degree of immunity to electromagnetic interference (EMI), and a much higher bandwidth than twisted pair telephone lines.

o  Example of its applications n  Local area network in an office environment n  Cable television

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Communication Channels: (iii) Optical Fiber

o  Features n  Enormous potential bandwidth

o  The bandwidth is roughly equal to 10% of the carrier frequency (2 × 1014 Hz).

o  Notably, the transmission attainable limit (for additive white Gaussian noise with SNR=10dB) is around

secondper Gigabit 86.6918secondper bit 1091886.6

)101(log)102()1(log

13

10/102

13

2

=

×=

+×=

+=dB

SNRBC


Communication Channels: (iii) Optical Fiber

n  Low transmission loss o  0.1dB/km

n  Immunity to EMI n  Small size and weight (thinner than human hair) n  Ruggedness and flexibility

o  Possibility of being bent or twisted without damage

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Communication Channels: (iv) Wireless Broadcast Channels

o  Transmission n  Up-convert the modulated baseband information-

bearing signal to Radio Frequency (RF) passband signal

n  Transmit the RF passband signal via antenna o  Reception

n  Pick up the radiated waves by an antenna. n  Down-convert the received passband signal to

baseband signal (perhaps through an intermediate step called the intermediate frequency (IF) band).


Communication Channels: (v) Mobile Radio Channels

o  The main difference between this channel and the previous channel is the consideration of mobility. n  Due to mobility, there is no “line-of-sight” path for

communication; n  rather, radio propagation takes place mainly by way

of scattering from the surfaces of the surrounding buildings and by diffraction over and around them.

n  This results in a multipath fading transmission.

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Communication Channels: (v) Mobile Radio Channels

Transmitter Receiver

),( 11 τα

),( 22 τα

),( 33 τα

)()()()(

33

22

11

tntststs

+

−+

−+

−

τα

τα

τα)(ts

Notably, αj and τj can also be functions of time.


Communication Channels: (vi) Satellite Channels

o  Satellite communications n  The satellite is placed in geostationary orbit.

o  Geostationary orbit 1. The satellite orbits the Earth in exactly 24 hours

(geosynchronous). 2. The satellite is placed in orbit directly above the equator on

an eastward heading.

n  It acts as a powerful repeater in the sky. n  It often uses 6 GHz for the uplink and 4 GHz for

the downlink.

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n  The 6/4-GHz band offers the following attributes: 1. Relatively inexpensive microwave equipment 2. Low attenuation due to rainfall

n  Rainfall is a primary atmospheric cause of signal loss. 3. Insignificant sky background noise

n  The sky background noise due to random noise emissions from galactic, solar and terrestrial sources reaches its lowest level between 1 and 10 GHz.



n  A typical satellite in the 6/4-GHz band is assigned a 500 MHz bandwidth, which is divided among 12 transponders. o  Each transponder can carry at least one color television

signal, 1200 voice circuits, or digital data at a rate of 50 Mb/s.

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Classifications of Communication Channels (according to the natures or resources)

o  Linear or non-linear n  A wireless radio channel is linear whereas a satellite

channel is usually non-linear. o  Time invariant or time varying

n  An optical fiber is time invariant, whereas a mobile radio channel is typically time varying.

o  Band limited or power limited n  A telephone channel is band limited, whereas an

optical fiber link and a satellite channel are both power limited.


Classification of Modulation Process

o  Continuous-wave modulation n  A sinusoidal wave is used as the carrier. n  It can be further classified as:

o  Amplitude modulation (AM) : Amplitude of the carrier is varied in accordance with the message.

o  Frequency modulation (FM) : Frequency of the carrier is varied in accordance with the message.

o  Phase modulation (PM) : Phase of the carrier is varied in accordance with the message.

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Classification of Modulation Process

o  Pulse modulation n  The carrier consists of a sequence of rectangular

pulses. n  It can be sub-divided to:

o  Analog pulse modulation o  Digital pulse modulation


Classification of Modulation Process n  Analog pulse modulation

o  Pulse-amplitude modulation (PAM), pulse-duration modulation (PDM), pulse-position modulation (PPM)

o  The amplitude, duration, position of the pulses varies in accordance with the message signals.

n  Digital pulse modulation o  Pulse-code modulation (PCM)

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Example of PAM (Telephone System)

Sampling the voice according to some clocks.


Example of PCM

o Originate from PAM, but with the following modifications. n  Convert the (sampled) pulse into bits, e.g., 8 bits. n  All 8 bits of the input PCM signal are gated to the

output port in parallel. n  The gate can now be designed using “truth table”

which facilitates system integration or multiplexing.

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What is multiplexing?

o  To combine (several modulated) signals for their simultaneous (or concurrent) transmission. n  Frequency-division multiplexing (FDM) n  Time-division multiplexing (TDM) n  Code-division multiplexing (CDM) n  Wavelength-division multiplexing (WDM),

specifically for use of optical fibers. o  Some treats WDM as a special case of FDM, since c =

f λ.


Shannon’s Information Capacity Theorem

o  The underlying limit for digital communications

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Transmission Rate = Source code bit per second (Information bit per second)



o Reliable transmission rate (for pre-specified modulator, channel and demodulator). n  The rate for which a proper design of channel

encoder-decode pair can fulfill arbitrarily small error requirement.

o  Shannon finds the general formula for the largest reliable transmission rate, which he baptized as “(coding) channel capacity.”

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o  For additive white Gaussian noise as demodulator output = modulator input + Gaussian

the channel capacity is equal to C = B log2(1+SNR) bits/second, where B is the bandwidth.

o  It took 45 years (1948~1993) of research to reach this “capacity!”


An Exemplified Ideal Digital Communication Problem – Phase Shift Keying

Channel Encoder

…0110 Modulator

…,-m(t), m(t), m(t), -m(t)

m(t)

T

⊗

Carrier wave Accos(2πfct)

s(t) ⊕

w(t)

x(t) ⊗

Local carrier cos(2πfct)

∫Tdt

0

correlator

yT > < 0 0110…

No IF here because this is an ideal system.

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o Assume that the local carrier (at the receiver end) is exactly the same as the transmitter carrier.

o Assume that the correlator is completely synchronized with the transmitter. n  So the integration inside correlator covers a

complete message signal m(t). In other words, it will not happen that the integration inside correlator covers 80% of the current m(t) but 20% of the previous m(t).

yT = x(t)cos(2π fct)dt0

T∫

= [s(t)+w(t)]cos(2π fct)dt0

T∫

= [±Ac cos(2π fct)+w(t)]cos(2π fct)dt0

T∫

= ±Ac cos2(2π fct)dt0

T∫ + w(t)cos(2π fct)dt0

T∫

= ±Ac1+ cos(4π fct)

2dt

0


T∫

= ±12AcT ±

12Ac cos(4π fct)dt0


T∫

= ±12AcT + w(t)cos(2π fct)dt0

T∫


(By assuming that fc is a multiple of 1/T.)

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o  Some interesting issues to consider: n  What if the local carrier does not equal the

transmitter carrier.

n  What if fc is not a multiple of 1/T. n  What if the receiver does not synchronize with the

transmitter? n  What is the BER of this system?

yT = [±Ac cos(2π ftct)+w(t)]cos(2π frct)dt0

T∫



n  Is the correlator receiver optimal in the sense of BER?

n  Is the “sign-decision” optimal in the sense of BER? n  Is the above combination optimal in the sense of

BER? n  Is the BER robust for imperfect system, such as

timing and carrier mismatch? n  Is the rectangular m(t) a fine choice? Moreover, is

PSK a fine choice? If affirmative, in what sense? n  ….

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o All these problems will be hopefully answered in this course (and subsequent courses).

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