advanced wireless communications lecture notes: section 1...advanced wireless communications is the...

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Advanced Wireless Communications lecture notes: section 1 Andrea M. Tonello Double Master Degree in Electrical Engineering - University of Udine, Italy and Information and Communication Engineering - University of Klagenfurt, Austria Note: these lecture notes have been prepared as part of the material for the joint class “Advanced wireless communications” and “Comunicazioni Wireless” by A. Tonello. The class has been offered in the Spring 2015 term, by means of video conferencing in time sharing between two locations.

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Page 1: Advanced Wireless Communications lecture notes: section 1...Advanced wireless communications is the second part of the class “Comunicazioni wireless” offered in Udine Students

Advanced Wireless Communications

lecture notes: section 1Andrea M. Tonello

Double Master Degree inElectrical Engineering - University of Udine, Italy

andInformation and Communication Engineering - University of Klagenfurt, Austria

Note: these lecture notes have been prepared as part of the material for the joint class “Advanced wirelesscommunications” and “Comunicazioni Wireless” by A. Tonello. The class has been offered in the Spring 2015 term, by

means of video conferencing in time sharing between two locations.

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A. Tonello 2

Class Content Description

o The class advanced wireless communications offers a description of relevant techniques fordata transmission in wireless channels. It starts with a review of basic topics in mobilecommunications (as the cellular concept, fading channel models, digital modulationtechniques). Then, it discusses the performance in fading channels of digital modulation,antenna diversity techniques, state-of-the-art multicarrier modulation techniques, spreadspectrum and code division multiple access, ultra wide band modulation.

Topics

o Review of the cellular communication concepto Baseband representation of a digital modulation systemo Mobile wireless channel: fading and its statisticso Performance analysis of digital modulation in fading channelso Antenna diversity techniques and performanceo Multicarrier modulation: OFDM and FMTo Spread spectrum systems: DS-CDMA, multiple access interference, rake receivero Ultra wide band modulationo Some elements of wireless standards

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Material

Text books

o J. G. Proakis, Digital Communications, McGraw-Hill, NewYork, 2001o G. T. Stüber, Principles of mobile communications, KAP, 2001o T. Rappaport, Wireless communications: Principles and practice, 2001

Class materialo Slides and class material

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History of Communications: 1937-1970

Antonio Meucci, 1871

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History of Communications: 1971-1999

D. Ring, R. Young, 1947

R. Frenkiel, J. Engel, P. Porter, 1967

M. Cooper, 1973

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Communication Services

There has been a tremendous growth of communication services

High speed core networks have been realized using optical fiber

Last mile communications and internet access enabled by DSL

Wireless communications are now massively deployed and support mobility

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A. Tonello 7

Evolution of Cellular Technology: from GSM to LTE

Bits

per

seco

nd

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A. Tonello 8

Mobile Communication Standards

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Spectrum is Limited

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Evolution of Mobile Terminals

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Complexity

Increased data rates determine increased processing power

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Key points are:

o Increase spectral efficiency

o Reduce complexity, power consumption and size

o Devise fast analysis and prototyping methodologies

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Open System Interconnection (OSI) Model

In the OSI model, a communication network comprises nodes that implementthe procedures described by the seven layers

This class is about L1: the physical layer

L7: Application

L6: Presentation

L5: Session

L4: Transport

L3: Network

L2: Data link

L1: Physical

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Block Diagram of a Communication System

This class offers the tools to design and analyze a wireless physical layer:o Channel modelo Digital modulation and performanceo Diversity techniqueso Advanced modulation techniques

Source coder Channel coder Digital modulator

Digital Demodulator Channel decoder Source decoder

Channel

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Background Knowledge

Advanced wireless communications is the second part of the class“Comunicazioni wireless” offered in Udine Students of “Comunicazioni wireless” have already learnt about:

o Cellular concepto Network aspects and element of system capacityo Multiplexing and media access techniqueso Mobile radio channel model: path loss and fast fading models

This second part is related to physical layer aspects. Required background:

o Signal theory: convolution (filtering) and Fourier transformo Statistics: random variables and random processeso Principles of communications

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Review of the Cellular Concept

Key aspects Exploit signal attenuation with

distance Exploit frequency reuse Offer wide coverage Offer high capacity with limited

spectrum Support mobility Mobility affects the channel

x x

x

x

x

xx

x x

x

x

x

xx

x x

x

x

x

xx

x x

x

x

x

xx

x x

x

x

x

xx

x x

x

x

x

xx

x x

x

x

x

xx

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Review of Multiplexing

Contention based protocols are also used, e.g., Aloha, Slotetd Aloha, CSMA

User 1 User 2 User 3

time

frequency

User 1 User 2 User 3

Code 1

Code 2

TDMA : Time Division Multiple Access

FDMA : Frequency Division Multiple Access

CDMA : Code Division Multiple Access

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Review of Digital Modulation

We consider band pass digital quadrature modulation (only)

A. Transmission of a stream of bits

B. The communication medium (radio channel) is band pass

C. The bit stream has to be mapped into a suitable band pass analog waveform

1 1 0 0 1 0 0 0 … t f-f0 f0

V(f)v(t)

bit stream analog real waveform band pass spectrum

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Linear Modulator

a(t), tℝ: real base band signal

A(f)

f-B B

A(f)=Fa(t), f [-B, B]

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Linear Modulator

a(t), tℝ: real base band signal

Va(f)

f

12A(f−fo)

a(t)X

cos(2πfot)

va(t)

12A(f+fo)

A(f)

f-B B

fo-fo

A(f)=Fa(t), f [-B, B]Va f = 12A(f−fo)+12A(f+fo)

Correct modulation condition: f0 > B

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Quadrature Modulator

a(t), b(t), tℝ: base band real signals

A(f), B(f)

f-B B

A(f), B(f), f [-B, B]a(t)

X

cos(2πfot)

va(t)

b(t)X

-sin(2πfot)

vb(t)+

v(t)

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Quadrature Modulator

a(t), b(t) tℝ: real base band signals

V(f)

f

12A(f+fo)+12j B(f+fo)

fo-fo

f-B B

-+

V(f) = Va(f)+Vb(f)

=12 A(f−fo)+A(f+fo) +

12j B(f+fo)−B(f−fo)

A(f), B(f), f [-B, B]a(t)

X

cos(2πfot)

va(t)

b(t)X

-sin(2πfot)

vb(t)+

v(t)

12A(f−fo) − 12j B(f−fo)

A(f), B(f)

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M-QAM Modulation

an

bn

Map

Map

S/Pbits

The streams of bits are mapped into two real symbol sequencesan = a nT bn = b nT ∈ ℤ T is the symbol period,M is the modulation order Alphabet of an, bn has L values, e.g., L= M, = − L + 1,… , − 1,1, … , L − 1

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M-QAM Modulation

an

bn

Map

Map

S/Pbits

Alphabet elements are labeled with N=log2L bits

31-1-3

10110100

M=16 modulation orderL = 4 levels for an and bnN = 2 bits

The streams of bits are mapped into two real symbol sequencesan = a nT bn = b nT ∈ ℤ T is the symbol period,M is the modulation order Alphabet of an, bn has L values, e.g., L= , = − L + 1,… , − 1,1, … , L − 1

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M-QAM Modulation

The continuous time signals a t , b(t) are obtained by the interpolation of thesequences of data symbols an, bn with the base band pulse shaping filter gTX(t)

a(t)X

cos(2πfot)

va(t)

b(t)X

-sin(2πfot)

vb(t)

+v(t)

↑ gTX(t)an

↑ gTX(t)bn

Map

Map

S/Pbits

a t = angTX(t − nT) b t = bngTX(t − nT)Pulse amplitude modulation (PAM) on each channel

G(f)

f12 =− 12

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Complex Representation

v t = angTX t − nT cos(2πfot) − bngTX t − nT sin(2πfot)

a(t)X

cos(2πfot)

va(t)

b(t)X

-sin(2πfot)

vb(t)

+v(t)

an

bn

↑ gTX(t)

↑ gTX(t)

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Complex Representation

v t = angTX t − nT cos(2πfot) − bngTX t − nT sin(2πfot)v t = Re an + jbn gTX t − nT e

cn=an+jbn complex data symbols

c(t)X

v(t)↑ gTX(t)cn Re ·

e

a(t)X

cos(2πfot)

va(t)

b(t)X

-sin(2πfot)

vb(t)

+v(t)

an

bn

↑ gTX(t)

↑ gTX(t)

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Constellation The alphabet of the data symbol cn can be represented in the complex plane with

points of a regular lattice forming a constellation

Since = , both the phase and the amplitude of the signal are modulated

Bit rate: R = bit/s

By increasing the modulation order M, we transmit more bits per second !

Im cn

Re cnM=16 (constellation size)

0000 0001

0010 0011

0100 0101

0110 0111

1010

10001001

1011

1101 1100

11101111

bit label

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Constellation for M=32

Im cn

Re cn

M=32

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Demodulator

V(f)= Va(f)+Vb(f)

f+ -

gRX(t) za tX

cos(2πfot)

xa(t)

X

-sin(2πfot)

xb(t)

v(t)

gRX(t) zb t

fo-fo 12A(f−fo)−12j B(f−fo)

12A(f+fo)+12j B(f+fo)

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Demodulation: contribution of signal a(t)

f

f

12A(f − f0)12A(f + f0)12 12A(f)/2

gRX(t) za tX

cos(2πfot)

xa(t)

X

-sin(2πfot)

xb(t)

v(t)

gRX(t) zb t Contribution of signal a(t)

fo-fo

-2fo 2fo

Va(f)

Xa(f)

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A. Tonello 32

Demodulation: contribution of signal a(t)

f

f

f

Za(f)=12A(f)

12A(f − f0)12A(f + f0)12 12

za(t)= a(t)+ signal bgRX(t) za tX

cos(2πfot)

xa(t)

X

-sin(2πfot)

xb(t)

v(t)

gRX(t) zb t Contribution of signal a(t)

A(f)/2-2fo 2foGRX(f)= rect 2

B-B

fo-fo

Va(f)

Xa(f)

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A. Tonello 33

Demodulation: contribution of signal b(t)

za(t)=12 a(t)+ signal b

Contribution of signal b(t)

gRX(t) za tX

cos(2πfot)

xa(t)

X

-sin(2πfot)

xb(t)

v(t)

gRX(t) zb t-

f+

f-+

f

Za(f)=0

− 12j B(f − f0)12j B(f + f0)12 12

GRX(f)= rect 20

-2fo 2fo

B-B0

fo-fo

Vb(f)

Xa(f)

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A. Tonello 34

Output Signals

zo t = za(t)+jzb(t) = 12 cng t − nT

za(t)=12 a(t)

zb(t)=12 b(t)

zo nT = (an+jbn) = cn Complex data symbol weighted by V0 /2

If gEQ nT = V0 for n = 00 for n ≠ 0 Nyquist criterion for no ISI

zo(t)=12 a(t)+ jb(t)

gRX(t) za tX

cos(2πfot)

xa(t)

X

-sin(2πfot)

xb(t)

v(t)

gRX(t) zb t

Let us sample the signal z(t) with period T:

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Additive Noise

z (nT) = za(nT)+jzb(nT) = cn + w(nT)

gRX(t)X

cos(2πfot)

xa(t)

X

-sin(2πfot)

xb(t)

v(t)

gRX(t)+( )

za t = a(t) + wa(t)

zb t = b(t) + wb(t)

↓ za nT↓ zb nT

Output sample at time nT:

complex data symbol noise sample wa,n+jwb,n

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Detection with Additive Noise Additive noise shifts the position of the transmitted data symbol

Detection (intuition): decide for the data symbol that is at minimum Euclideandistance from the received signal sample

Decision regions are determined

Im cn

Re cn

cn = argmin |z(nT) − a|2

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Final Remarks

We have learnt:

o QAM exploits two digital amplitude modulators in quadrature

o QAM transmits a high number of bits in the available band

But what happens in wireless channel ?

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Transmission Chain in a Mobile Radio Channel

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Time Variant Radio Mobile Channel

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Base Band System Rapresentation

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Relevant Cases

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Output BB Signal

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Focus on Case A

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Nyquist Criterion

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Root Nyquist Pulse

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Matched Filter

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Focus on Case C

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Slowly Time Variant Channel

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Noise

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Noise at the RX Output

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Noise at the RX Output

Sampled at time kT

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Inpt/Output Signal Model

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Clarke‘s Channel Model

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Statistical Radio Channel Model

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Rayleigh Fading

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Effect of Fading on Digital Modulation

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Coherent Detection in Fading Optimal coherent detection: decide for the data symbol corrected by the channel

amplitude and phase (fading coefficient) that is at minimum Euclidean distancefrom the received signal sample

Im cnRe cn

ck = argmin |z(kT) − Ak |2

Im cnRe cn

Im cnRe cn

Original 4-PSK constellation Modified constellation Erroneous decision

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Coherent Detection

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Channel Estimation

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Differential Modulation

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Differential Demodulation

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Penalty