# EE359 Lecture 20 Outline

Mobile - Wireless

Nov 21, 2013 (4 years and 5 months ago)

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EE359

Lecture 20 Outline

Announcements

Project due Friday at 5 pm (extension request due today).

HW 8 due Friday at 5 (no late HWs: solns posted at 5).

tbp
evals at end of class (10 bonus poits)

Must be turned in no later than Monday, Dec. 6, at exam.

2
nd

Exam next Monday, 12/6, 9:30
-
1:30, Gates B01

Course Summary

EE359 Megathemes

Wireless Networks

Hot Research Topics

2
nd

Exam Announcements

2nd Exam next Monday, 12/6, 9:30
-
11:30, Gates B01

Local SCPD student take in class, others contact Joice.

Open book/notes

Covers Chapters 9
-
13 (and related prior material)

Similar format to first exam

Practice finals posted (10 bonus points)

Exam review session Thursday 5
-
6 pm TCSEQ 102

Extra OHs

My OHs: Th 7
-
8, F 4
-
5 and by appt (none today).

Rajiv: T 6
-
7, W 5
-
7, F 11
-
12, Sa 3
-
4, Email: TWTh 10
-
11pm.

Review of Last Lecture

ISI rejection by code autocorrelation

Maximal linear codes

Good properties

Long versus short codes

S(f)

S(f)

I(f)

S(f)
*
S
c
(f)

Info. Signal

I(f)
*
S
c
(f)

S(f)

a
p⡦)

p⡦)
*
S
c
(f)[
⡴(
+
b

-
t

䥮漮op楧i慬

䑥獰re慤⁓楧i慬

br
p

(f)

Interference

Rejection

ISI

Rejection

-
1

N

1

T
c

-
T
c

1

NT
c

Assume h(t)

a
1
d
(t)+
a
2
d
(t
-
T
c
)+…+
a
N
d
(t
-
MT
c
)

Branches synchronized to different MP components

ISI with delay jT
c

on i
th

branch reduced by
r
s
c
((j
-
i)T
c
)

Diversity combiner can use SC, MRC, or EGC

x

x

s
c
(t)

s
c
(t
-
iT
c
)

x

s
c
(t
-
MT
c
)

Demod

Demod

Demod

y(t)

Diversity

Combiner

d
k

^

a
1
d
k
+ISI
1
+n
1

a
i
d
k
+ISI
i
+n
i

a
M
d
k
+ISI
N
+n
M

Course Summary

Signal Propagation and Channel Models

Modulation and Performance Metrics

Impact of Channel on Performance

Fundamental Capacity Limits

Diversity

ISI Mitigation

Equalization

Multicarrier Modulation

Future Wireless Networks

Wireless Internet access

Nth generation Cellular

Sensor Networks

Wireless Entertainment

Smart Homes/Spaces

Automated Highways

All this and more…

Ubiquitous Communication Among People and Devices

Hard Delay/Energy Constraints

Hard Rate Requirements

Design Challenges

Wireless channels are a difficult and capacity
-

Traffic patterns, user locations, and network
conditions are constantly changing

Applications are heterogeneous with hard
constraints that must be met by the network

Energy, delay, and rate constraints change design
principles across all layers of the protocol stack

Signal Propagation

Path Loss

Multipath

d

P
r
/P
t

d=vt

Statistical Multipath Model

Random # of multipath components, each with
varying amplitude, phase, doppler, and delay

Narrowband channel

Signal amplitude varies randomly (complex Gaussian).

2
nd

order statistics (Bessel function), Fade duration, etc.

Wideband channel

Characterized by channel scattering function (
B
c
,B
d
)

Modulation Considerations

Want high rates, high spectral efficiency, high power
efficiency, robust to channel, cheap.

Linear Modulation (MPAM,MPSK,MQAM)

Information encoded in amplitude/phase

More spectrally efficient than nonlinear

Issues: differential encoding, pulse shaping, bit mapping.

Nonlinear modulation (FSK)

Information encoded in frequency

More robust to channel and amplifier nonlinearities

Linear Modulation in AWGN

ML detection induces decision regions

Example: 8PSK

P
s

depends on

# of nearest neighbors

Minimum distance
d
min
(depends on
g
s
)

Approximate expression

s
M
M
s
Q
P
g
b
a

d
min

g
s

and therefore
P
s

random

Metrics:
outage
,
average
P
s

, combined
outage and average.

P
s

P
s(target)

Outage

P
s

T
s

T
s

s
s
s
s
s
d
p
P
P
g
g
g
)
(
)
(

Moment Generating

Function Approach

Simplifies average
P
s

calculation

Uses alternate Q function representation

P
s

reduces to MGF of
g
s

distribution

Closed form or simple numerical calculation

P
s

.

Doppler Effects

High doppler causes channel phase to
decorrelate between symbols

Leads to an irreducible error floor for
differential modulation

Increasing power does not reduce error

Error floor depends on B
d
T
s

Delay spread exceeding a symbol time
causes ISI (self interference).

ISI leads to irreducible error floor

Increasing signal power increases ISI power

ISI requires that T
s
>>T
m

(R
s
<<B
c
)

ISI Effects

Tm

0

Three cases

Vary rate and power relative to channel

-
filling

Exceeds AWGN channel capacity at low SNRs

Suboptimal techniques come close to capacity

Variable
-
Rate Variable
-
Power MQAM

Uncoded

Data Bits

Delay

Point

Selector

M(
g
)
-
Q䅍

Modulator

Power: S(
g
)

T漠䍨慮C敬

g
(t)

g
⡴(

log
2

M(
g
⤠䉩瑳

g
⤠P潩湴o

BSPK

4
-
QAM

16
-
QAM

Goal: Optimize S(
g
) and M(
g
) to maximize EM(
g
)

Power Water
-
Filling

Spectral Efficiency

S
S
K
K
K
(
)
g
g
g
g
g
g

1
1
0
0
0
else
g

1
0
g
1
g
K
g
k

g

R
B
p
d
K
K

log
(
)
.
2
g
g
g
g
g
Equals Shannon capacity with an effective power loss of
K
.

Practical Constraints

Constellation restriction

Constant power restriction

Estimation error.

Estimation delay.

Diversity

Send bits over independent fading paths

Combine paths to mitigate fading effects.

Space, time, frequency, polarization diversity.

Combining techniques

Selection combining (SC)

Equal gain combining (EGC)

Maximal ratio combining (MRC)

Diversity Performance

Maximal Ratio Combining (MRC)

Optimal technique (maximizes output SNR)

Combiner SNR is the sum of the branch SNRs.

Distribution of SNR hard to obtain.

Can use MGF approach for simplified analysis.

Exhibits 10
-
40 dB gains in Rayleigh fading.

Selection Combining (SC)

Combiner SNR is the maximum of the branch SNRs.

Diminishing returns with # of antennas.

CDF easy to obtain, pdf found by differentiating.

Can get up to about 20 dB of gain.

Multiple Input Multiple

Output (MIMO)Systems

MIMO systems have multiple (
M
) transmit and

With perfect channel estimates at TX and RX,
decomposes to
M

indep. channels

M
-
fold capacity increase over SISO system

Demodulation complexity reduction

Beamforming alternative:

Send same symbol on each antenna (diversity gain)

Digital Equalizers

Equalizer mitigates ISI

Typically implemented as FIR filter.

Criterion for coefficient choice

Minimize P
b

(Hard to solve for)

Eliminate ISI (Zero forcing, enhances noise)

Minimize MSE (balances noise increase with ISI removal)

Channel must be learned through training and
tracked during data transmission.

n(t)

c(t)

+

d(t)=
S
d
n
p(t
-
nT)

g*(
-
t)

H
eq
(z)

d
n

^

y
n

Multicarrier Modulation

Divides bit stream into N substreams

Modulates substream with bandwidth B/N

Separate subcarriers

B/N<B
c

FDM has substreams completely separated

OFDM overlaps substreams

More spectrally efficient

Efficient FFT Implementation

One modulator and demodulator

FFT performs frequency translation

Cyclic prefix eliminates ISI between blocks

Compensation techniques

Frequency equalization (noise enhancement)

Precoding (channel inversion)

Coding across subcarriers

Practical Issues for OFDM

Peak
-
to
-
average power ration

System imperfections

Direct Sequence

Bit sequence modulated by
chip

sequence

Spreads bandwidth by large factor (K)

c
(t) again (s
c
(t)=1)

Mitigates ISI and narrowband interference

ISI mitigation a function of code autocorrelation

Must synchronize to incoming signal

s(t)

s
c
(t)

T
b
=KT
c

T
c

S(f)

S
c
(f)

1/
T
b

1/
T
c

S(f)
*
S
c
(f)

2

Branches synchronized to different MP components

These components can be coherently combined

Use SC, MRC, or EGC

x

x

s
c
(t)

s
c
(t
-
iT
c
)

x

s
c
(t
-
NT
c
)

Demod

Demod

Demod

y(t)

Diversity

Combiner

d
k

^

Megathemes of EE359

The wireless vision poses great technical challenges

The wireless channel greatly impedes performance

Low fundamental capacity.

Channel is randomly time
-
varying.

ISI must be compensated for.

Hard to provide performance guarantees (needed for multimedia).

MIMO channels promise a great capacity increase.

A plethora of ISI compensation techniques exist

Various tradeoffs in performance, complexity, and implementation.

Wireless Network Design

Spectral Reuse

Cellular System Design

-
Hoc Network Design

Networking Issues

Access Channels

One Transmitter

Multiple Access (MAC):

Many Transmitters

R
1

R
2

R
3

x

h
1
(t)

x

h
21
(t)

x

h
3
(t)

x

h
22
(t)

7C29822.033
-
Cimini
-
9/97

Bandwidth Sharing

Dedicated channel assignment

Frequency Division

Time Division

Code Division

Hybrid Schemes

Code Space

Time

Frequency

Code Space

Time

Frequency

Code Space

Time

Frequency

Multiple Access SS

Interference between users mitigated by code
cross correlation

In downlink, signal and interference have

In uplink, “close” users drown out “far” users
(near
-
far problem)

)
(
)
2
cos(
5
.
5
.
)
(
)
(
5
.
5
.
))
(
2
cos(
)
2
cos(
)
(
)
(
)
(
)
2
(
cos
)
(
)
(
)
(
ˆ
12
2
1
0
2
1
2
2
1
1
1
2
2
0
2
2
2
1
1
1
t
r
t
p
a
a
t
p
p
t
t
a
p
a
c
T
c
c
c
c
c
c
T
c
c
f
d
d
dt
t
s
t
s
d
d
dt
t
f
t
f
t
s
t
s
t
s
t
f
t
s
t
s
t
x
b
b

a

a

Multiuser Detection

In all CDMA systems and in TD/FD/CD
cellular systems, users interfere with each other.

In most of these systems the interference is
treated as noise.

Systems become interference
-
limited

Often uses complex mechanisms to minimize impact
of interference (power control, smart antennas, etc.)

Multiuser detection exploits the fact that the
structure of the interference is known

Interference can be detected and subtracted out

Better have a darn good estimate of the interference

RANDOM ACCESS TECHNIQUES

7C29822.038
-
Cimini
-
9/97

Random Access

Dedicated channels wasteful for data

use statistical multiplexing

Techniques

Aloha

Carrier sensing

Collision detection or avoidance

Reservation protocols

PRMA

Retransmissions used for corrupted data

Poor throughput and delay characteristics under

Hybrid methods

BASE

STATION

Cellular System Design

Frequencies, timeslots, or codes reused at
spatially
-
separate locations

Efficient system design is interference
-
limited

Base stations perform centralized control functions

Call setup, handoff, routing, adaptive schemes, etc.

8C32810.44
-
Cimini
-
7/98

Design Issues

Reuse distance

Cell size

Channel assignment strategy

Interference management

Smart antennas

Multiuser detection

Dynamic resource allocation

Dynamic Resource Allocation

Allocate resources as user and network conditions change

Resources:

Channels

Bandwidth

Power

Rate

Base stations

Access

Optimization criteria

Minimize blocking (voice only systems)

Maximize number of users (multiple classes)

Maximize “revenue”

Subject to some minimum performance for each user

BASE

STATION

-
Hoc Networks

Peer
-
to
-
peer communications

No backbone infrastructure or centralized control

Routing can be multihop.

Topology is dynamic.

Fully connected with different link SINRs

Open questions

Fundamental capacity

Optimal routing

Resource allocation (power, rate, spectrum, etc.) to meet QoS

Power Control

Assume each node has an SIR constraint

Write the set of constraints in matrix form

If
r
F
<1

Power control algorithms

Centralized or distributed

i
j
i
j
ij
i
i
ii
i
P
G
P
G
SIR
g

0
P
0,
u
P
F
I

u
F
I
P
-1
*

P
1

P
2

P
*

Feasible Region

Iterative Algorithm

Power control for random channels more complicated

Wireless Networks with
Energy
-
Constrained Nodes

Limited node processing/communication capabilities

Nodes can cooperate in transmission and reception.

Intelligence must be “in the network”

Data flows to centralized location.

Low per
-
node rates but 10s to 1000s of nodes

Data highly correlated in time and space.

Energy
-
Constrained Nodes

Each node can only send a
finite

number of bits.

Energy minimized by sending each bit very slowly.

Introduces a delay versus energy tradeoff for each bit.

Short
-
range networks must consider both transmit
and processing energy.

Sophisticated techniques not necessarily energy
-
efficient.

Sleep modes save energy but complicate networking.

Changes
everything

Bit allocation must be optimized across
all
protocols.

Optimization of node cooperation.

NETWORK ISSUES

8C32810.53
-
Cimini
-
7/98

Higher Layer

Networking Issues

Architecture

Mobility Management

Identification/authentication

Routing

Handoff

Control

Reliability and Quality
-
of
-
Service

Wireless Applications and QoS

Wireless Internet access

Nth generation Cellular

Sensor Networks

Wireless Entertainment

Smart Homes/Spaces

Automated Highways

All this and more…

Applications have hard delay constraints, rate requirements,

and energy constraints that must be met

These requirements are collectively called QoS

Challenges to meeting QoS

Wireless channels are a difficult and capacity
-

Traffic patterns, user locations, and network
conditions are constantly changing

No single layer in the protocol stack can
guarantee QoS: cross
-
layer design needed

It is impossible to guarantee that hard constraints
are always met, and average constraints aren’t
necessarily good metrics.

Crosslayer Design

Application

Network

Access

Hardware

Delay Constraints

Rate Requirements

Energy Constraints

Mobility

Optimize and adapt across design layers

Provide robustness to uncertainty

Schedule dedicated resources

4G

Is 4G an evolution, an alternative, or a supplement
to 3G, or something more?

What services should 4G support?

Research challenges associated with 4G:

Air interface

Flexible QoS

Support for heterogeneous services

Cross
-
layer design

Promising Research Areas

Wideband air interfaces and dynamic spectrum management

Practical MIMO techniques (modulation, coding, imperfect CSI)

Cellular Systems

How to use multiple antennas

Multihop routing

Variable QoS

How to use multiple antennas

Cross
-
layer design

Sensor networks

Energy
-
constrained communication

Cooperative techniques

Information Theory

Imperfect CSI

Incorporating delay: Rate distortion theory for networks

The End

Thanks!!!

Have a great winter break