Digital Communication Fundamentals

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Chapter 1

Digital CommunicationsFundamentals

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1. Digital Communication Fundamentals

1.1 Communication Systems (Fig 1.1)

Mobile any terminal that moves rapidly.

Portable hand held terminal that moves slowly.

Base Station (BS)

a station that is fixed andcommunicates with the mobile.

Classes of transmission systems (Fig 1.2)

Simplex one way communication, Eg. Paging,

Broadcast etc. Half duplex two way communication, either

transmit or receive at any instant, Eg. Walkie

Talkie

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Channel is time shared (uses time slots).

Single channel, simultaneoustransmission and reception not possible.

A channel transmitting at higher data rates

appears to be transmitting and receiving

data simultaneously. Used in digital communication systems

and is prone to timing error and jitter.

TDD

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1.2 Digital Mobile Systems

Figure 1.2 A typical

Communication System


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Example: ARQ (Automatic Repeat Request).

1.3 Problems associated with MCS

Fading Occurs due to motion.

Losses could be as high as tens of dBs.

Fading rate proportional to the Carrier

Frequency and speed of the mobile.

Imbedding error correction protocols in data terminals

insures data fidelity.

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At high data rates, frequency selective fading

causes higher BER and Inter SymbolInterference (ISI).

Noise a general problem encountered in

communication channels resulting in higher BER.

can be reduced by error correction schemes. Additive White Gaussian Noise (AWGN) is

assumed.

Noise, fading, path loss complicate analysis.

Requires separate circuits handle each.

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1.4. Modulation and Coding requirements

a. Maximize transmission bit rates

b. Minimize error probability, .

c. Minimize power - minimize bit energy to noise

power spectral density, .

d. Minimize system BW.

e. Maximize system utilization.

f. Minimize system complexity, cost and load.

B eP P

0/NEb

R

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Maximizing rate requires larger BW.

Minimizing BER requires maximizing

power.

Trade offs required.

Theoretical considerations that necessitate

trade offs are: Nyquist theoretical BW.

Shannon capacity theorem.

Goals (a) contradicts (d) and (b) contradicts (c).

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BW efficiency represents the measure of data

throughput per hertz of BW.

Units are bits/s/Hz.

Shows how efficiently modulation (signaling)

technique utilizes BW.

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Theoretical max BW efficiency with out ISI2 (without ISI)

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k

M PAM

symbols / s / Hz

BWE bps / s / Hz

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Example

16ary PSK with a data rate of 9600 bps.

2

16 2 4 /

/

4 /9600

2400 /4

k

k

s

M

k bits symbol

Rbits sR

bits symbol

symbols s

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1.5.3 Shannons capacity theorem

The capacity of a channel in the presence

of AWGN is a function of average received

signal power.

2 lo 1g 1 .3S

C WN

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Unattainable

Physical Systems

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1.5.5 Entropy (H)

Defined as the average amount of information

per source output.

piis the probability of the ithoutput and

H in the case of two sources having

probabilities p and q = (1-p)is

2

1

log 71.n

i i

i

H p p

1ip

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2 2log log 1.8 H p p q q

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1.5.6 Bandwidth

BW-Range of positive frequencies over

which signal exists

Null to Null BW Range of positive

frequencies within the main lobe

3-db BW range of positive frequencies

from the maximum to the frequency where

the magnitude drops to 1/2 its peak value.

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Digital Communication Fundamentals