EE359

1
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.
• 2nd Exam next Monday, 12/6, 930-130, Gates B01
• Review of Last LectureRAKE Receivers
• Course Summary
• EE359 Megathemes
• Wireless Networks
• Hot Research Topics

2
2nd Exam Announcements

• 2nd Exam next Monday, 12/6, 930-1130, 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.

3
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

Interference Rejection
ISI Rejection
1
1
-1 N
Tc
NTc
-Tc
4
RAKE Receiver

• Multibranch receiver
• Assume h(t)?a1d(t)a2d(t-Tc)aNd(t-MTc)
• Branches synchronized to different MP components
• ISI with delay jTc on ith branch reduced by
  rsc((j-i)Tc)
• Diversity combiner can use SC, MRC, or EGC

a1dkISI1n1
Demod
sc(t)
y(t)

dk
aidkISIini
Diversity Combiner
Demod
sc(t-iTc)
aMdkISINnM
Demod
sc(t-MTc)
5
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

6
Future Wireless Networks
Ubiquitous Communication Among People and Devices
Wireless Internet access Nth generation
Cellular Wireless Ad Hoc Networks Sensor Networks
Wireless Entertainment Smart Homes/Spaces Automat
ed Highways All this and more

• Hard Delay/Energy Constraints

• Hard Rate Requirements

7
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

8
Signal Propagation

• Path Loss
• Shadowing
• Multipath

9
Statistical Multipath Model

• Random of multipath components, each with
  varying amplitude, phase, doppler, and delay
• Narrowband channel
• Signal amplitude varies randomly (complex
  Gaussian).
• 2nd order statistics (Bessel function), Fade
  duration, etc.
• Wideband channel
• Characterized by channel scattering function
  (Bc,Bd)

10
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

11
Linear Modulation in AWGN

• ML detection induces decision regions
• Example 8PSK
• Ps depends on
• of nearest neighbors
• Minimum distance dmin (depends on gs)
• Approximate expression

12
Linear Modulation in Fading

• In fading gs and therefore Ps random
• Metrics outage, average Ps , combined outage and
  average.

Ts
Ps
Outage
Ps(target)
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Moment Generating Function Approach

• Simplifies average Ps calculation
• Uses alternate Q function representation
• Ps reduces to MGF of gs distribution
• Closed form or simple numerical calculation for
  general fading distributions
• Fading greatly increases average Ps .

14
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 BdTs

15
ISI Effects

• 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 TsgtgtTm (RsltltBc)

Tm
0
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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

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Variable-Rate Variable-Power MQAM
Goal Optimize S(g) and M(g) to maximize EM(g)
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Optimal Adaptive Scheme

• Power Water-Filling
• Spectral Efficiency

g
Equals Shannon capacity with an effective power
loss of K.
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Practical Constraints

• Constellation restriction
• Constant power restriction
• Constellation updates.
• Estimation error.
• Estimation delay.

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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)

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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.

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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

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Digital Equalizers

• Equalizer mitigates ISI
• Typically implemented as FIR filter.
• Criterion for coefficient choice
• Minimize Pb (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.

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Multicarrier Modulation

• Divides bit stream into N substreams
• Modulates substream with bandwidth B/N
• Separate subcarriers
• B/NltBc 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

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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

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Direct Sequence Spread Spectrum

• Bit sequence modulated by chip sequence
• Spreads bandwidth by large factor (K)
• Despread by multiplying by sc(t) again (sc(t)1)
• Mitigates ISI and narrowband interference
• ISI mitigation a function of code autocorrelation
• Must synchronize to incoming signal

S(f)
s(t)
sc(t)
Sc(f)
S(f)Sc(f)
1/Tb
1/Tc
TbKTc
2
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RAKE Receiver

• Multibranch receiver
• Branches synchronized to different MP components
• These components can be coherently combined
• Use SC, MRC, or EGC

Demod
sc(t)
y(t)

dk
Diversity Combiner
Demod
sc(t-iTc)
Demod
sc(t-NTc)
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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.

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Wireless Network Design

• Broadcast and Multiple Access Channels
• Spectral Reuse
• Cellular System Design
• Ad-Hoc Network Design
• Networking Issues

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Broadcast and Multiple Access Channels
R3
R2
R1
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Bandwidth Sharing

• Dedicated channel assignment
• Frequency Division
• Time Division
• Code Division
• Hybrid Schemes

7C29822.033-Cimini-9/97
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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)

a
a
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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

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Random Access
RANDOM ACCESS TECHNIQUES

• 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

7C29822.038-Cimini-9/97
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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.

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Design Issues

• Reuse distance
• Cell size
• Channel assignment strategy
• Interference management
• Power adaptation
• Smart antennas
• Multiuser detection
• Dynamic resource allocation

8C32810.44-Cimini-7/98
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Dynamic Resource AllocationAllocate 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

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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

39
Power Control

• Assume each node has an SIR constraint
• Write the set of constraints in matrix form
• If rFlt1 ? a unique solution
• Power control algorithms
• Centralized or distributed

Power control for random channels more complicated
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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.

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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.

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Higher LayerNetworking Issues
NETWORK ISSUES

• Architecture
• Mobility Management
• Identification/authentication
• Routing
• Handoff
• Control
• Reliability and Quality-of-Service

8C32810.53-Cimini-7/98
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Wireless Applications and QoS
Wireless Internet access Nth generation
Cellular Wireless Ad Hoc Networks Sensor Networks
Wireless Entertainment Smart Homes/Spaces Automat
ed 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
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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 arent necessarily good metrics.

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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
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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

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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

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The End

• Thanks!!!
• Have a great winter break