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
Review of Last Lecture+RAKE Receivers
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
Introduction to Spread Spectrum
Direct Sequence Spread Spectrum
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
Receiver Input
Despread Signal
I(f)
*
S
c
(f)
S(f)
a
p⡦)
p⡦)
*
S
c
(f)[
ad
⡴(
+
b
⡴

t
⥝
䥮漮op楧i慬
剥ce楶敲䥮pu
䑥獰re慤⁓楧i慬
br
p
’
(f)
Interference
Rejection
ISI
Rejection

1
N
1
T
c

T
c
1
NT
c
RAKE Receiver
Multibranch receiver
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
Flat Fading Mitigation
Diversity
Adaptive Modulation
ISI Mitigation
Equalization
Multicarrier Modulation
Spread Spectrum
Future Wireless Networks
Wireless Internet access
Nth generation Cellular
Wireless Ad Hoc Networks
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

limited broadcast communications medium
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
Shadowing
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
Easier to adapt.
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
Linear Modulation in Fading
In fading
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
for general fading distributions
Fading greatly increases average
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
Capacity of Flat Fading Channels
Three cases
Fading statistics known
Fade value known at receiver
Fade value known at receiver and transmitter
Optimal Adaptation
Vary rate and power relative to channel
Optimal power adaptation is water

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
佮O瑨
䴨
g
⤠P潩湴o
BSPK
4

QAM
16

QAM
Goal: Optimize S(
g
) and M(
g
) to maximize EM(
g
)
Optimal Adaptive Scheme
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
Constellation updates.
Estimation error.
Estimation delay.
Diversity
Send bits over independent fading paths
Combine paths to mitigate fading effects.
Independent fading paths
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
receiver antennas
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)
Diversity versus capacity tradeoff
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
flat fading (no ISI)
FDM has substreams completely separated
OFDM overlaps substreams
More spectrally efficient
Substreams separated in receiver
Efficient FFT Implementation
One modulator and demodulator
FFT performs frequency translation
Cyclic prefix eliminates ISI between blocks
Fading Across Subcarriers
Compensation techniques
Frequency equalization (noise enhancement)
Precoding (channel inversion)
Coding across subcarriers
Adaptive loading (power and rate)
Practical Issues for OFDM
Peak

to

average power ration
System imperfections
Direct Sequence
Spread Spectrum
Bit sequence modulated by
chip
sequence
Spreads bandwidth by large factor (K)
Despread by multiplying by s
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
RAKE Receiver
Multibranch receiver
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).
We can compensate for flat fading using diversity or adapting.
MIMO channels promise a great capacity increase.
A plethora of ISI compensation techniques exist
Various tradeoffs in performance, complexity, and implementation.
Wireless Network Design
Broadcast and Multiple Access Channels
Spectral Reuse
Cellular System Design
Ad

Hoc Network Design
Networking Issues
Broadcast and Multiple
Access Channels
Broadcast (BC):
One Transmitter
to Many Receivers.
Multiple Access (MAC):
Many Transmitters
to One Receiver.
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
same received power
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
heavy loading
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
Power adaptation
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
Ad

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
愠a湩n略潬畴楯n
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
about the network design:
Bit allocation must be optimized across
all
protocols.
Delay vs. throughput vs. node/network lifetime tradeoffs.
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
Wireless Ad Hoc Networks
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

limited broadcast communications medium
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
Link
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
Link Layer
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
Ad Hoc Networks
How to use multiple antennas
Cross

layer design
Sensor networks
Energy

constrained communication
Cooperative techniques
Information Theory
Capacity of ad hoc networks
Imperfect CSI
Incorporating delay: Rate distortion theory for networks
The End
Thanks!!!
Have a great winter break
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