EE359 – Lecture 20 Outline

AnnouncementsProject due Friday at 5 pm (extend to Sunday 5pm).HW due Friday at 5.τβπ evals at end of class (10 bonus poits), then pizza

Must be turned in no later than at exam.2nd Exam next Wednesday, 12/14, 9:30-11:30, McCoull115

Review of Last Lecture+Synch+RAKECourse Summary

EE359 Megathemes

Wireless Networks Hot Research Topics

2nd Exam Announcements

2nd Exam next Wed., 12/14, 9:30-11:30, MCCULL115, Local SCPD student take in class, others contact Joice.

Open book/notes

Covers Chapters 9,10,12,13 (and related prior stuff)

Similar format to first exam

Practice finals posted (10 bonus points)

Exam review session Sunday 6-7 room TBD

Extra OHsMy OHs: today 12:30-1:30, Th 12-1, next M 6-7 & by appt.Ritesh: Sun 7-8, T 2-4.

Review of Last LectureDirect Sequence Spread Spectrum

ISI rejection by code autocorrelationMaximal linear codes

Good propertiesLong versus short codes

S(f)S(f)

I(f)S(f)*Sc(f)

Info. Signal Receiver Input Despread Signal

I(f)*Sc(f)

S(f)αS(f)

S(f)*Sc(f)[αδ(t)+β(t-τ)]

Info. Signal Receiver Input Despread Signal

βρS’(f)

InterferenceRejection

ISIRejection

-1N

1

Tc-Tc

1

NTc

Synchronization

Adjusts delay of sc(t-τ) to hit peak value of

autocorrelation.Typically synchronize to LOS component

Complicated by noise, interference, and MP

Synchronization offset of ∆t leads to signal

attenuation by ρc(∆t)

RAKE Receiver

Multibranch receiverBranches synchronized to different MP components

These components can be coherently combinedUse SC, MRC, or EGC

x

x

sc(t)

sc(t-iTc)

xsc(t-NTc)

Demod

Demod

Demod

y(t)

DiversityCombiner

dk̂

Main Points

Synchronization also depends on autocorrelation properties of spreading code.

RAKE receivers combine energy of all MPUse same diversity combining techniques as before

Wireless Vision

Wireless Internet accessNth generation CellularWireless Ad Hoc NetworksSensor Networks Wireless EntertainmentSmart Homes/SpacesAutomated HighwaysAll this and more…

Ubiquitous Communication Among People and Devices

•Hard Delay Constraints•Hard Energy Constraints

Course Summary

Signal Propagation and Channel Models

Modulation and Performance Metrics

Impact of Channel on Performance

Fundamental Capacity Limits

Flat Fading MitigationDiversityCoding and InterleavingAdaptive Modulation

ISI MitigationEqualizationMulticarrier ModulationSpread Spectrum

Signal Propagation

Path Loss

Shadowing

Multipathd

Pr/Pt

d=vt

Statistical Multipath Model

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

Narrowband channelSignal amplitude varies randomly (complex Gaussian).2nd order statistics (Bessel function), Fade duration, etc.

Wideband channelCharacterized by channel scattering function (Bc,Bd)

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 nonlinearEasier to adapt.Issues: differential encoding, pulse shaping, bit mapping.

Nonlinear modulation (FSK)Information encoded in frequencyMore robust to channel and amplifier nonlinearities

Linear Modulation in AWGN

ML detection induces decision regionsExample: 8PSK

Ps depends on# of nearest neighborsMinimum distance dmin (depends on γs)Approximate expression

( )sMMs QP γβα≈

dmin

Linear Modulation in Fading

In fading γs and therefore Ps randomMetrics: outage, average Ps , combined outage and average.

Ps

Ps(target)

Outage

Ps

Ts

Ts

sssss dpPP γγγ )()(∫=

Moment Generating Function Approach

Simplifies average Ps calculation

Uses alternate Q function representation

Ps reduces to MGF of γs distribution

Closed form or simple numerical calculation for general fading distributions

Fading greatly increases average Ps .

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

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

ISI leads to irreducible error floorIncreasing signal power increases ISI power

ISI requires that Ts>>Tm (Rs<<Bc)

ISI Effects

Tm0

Capacity of Flat Fading Channels

Four casesNothing knownFading statistics knownFade value known at receiverFade value known at receiver and transmitter

Optimal AdaptationVary rate and power relative to channelOptimal power adaptation is water-fillingExceeds AWGN channel capacity at low SNRsSuboptimal techniques come close to capacity

Variable-Rate Variable-Power MQAM

UncodedData Bits Delay

PointSelector

M(γ)-QAMModulator

Power: S(γ)

To Channel

γ(t) γ(t)

log2 M(γ) Bits One of theM(γ) Points

BSPK 4-QAM 16-QAM

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

Optimal Adaptive Scheme

Power Water-Filling

Spectral Efficiency

SS

K K K( )γ γ γγ γγ

=− ≥ =⎧

⎨⎩

1 10

0

0 else

γ

10γ

1γK

γk γ

RB

p dK K

=⎛⎝⎜

⎞⎠⎟

∞

∫ log ( ) .2

γ

γγ

γ γ

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 pathsCombine paths to mitigate fading effects.

Independent fading pathsSpace, time, frequency, polarization diversity.

Combining techniquesSelection 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 systemDemodulation complexity reduction

Multicarrier Modulation

Divides bit stream into N substreams

Modulates substream with bandwidth B/NSeparate subcarriersB/N<Bc flat fading (no ISI)

FDM has substreams completely separated

OFDM overlaps substreamsMore spectrally efficientSubstreams separated in receiver

Efficient FFT Implementation

Fading Across Subcarriers

Compensation techniquesFrequency equalization (noise enhancement)PrecodingCoding across subcarriersAdaptive loading (power and rate)

Practical Issues for OFDMPeak-to-average power rationSystem imperfections

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 interferenceISI mitigation a function of code autocorrelation

Must synchronize to incoming signal

s(t) sc(t)

Tb=KTcTc

S(f)Sc(f)

1/Tb1/Tc

S(f)*Sc(f)

2

RAKE Receiver

Multiple branches synchronize to each multipath component:

N receiver spreading codes, the ith one synchronized to delay τi.

These components can be coherently combined.

Same diversity combining techniques as discussed earlier.

)()(1

i

N

ii tth τδα −= ∑

=

Megathemes of EE359

The wireless vision poses great technical challenges

The wireless channel greatly impedes performanceLow 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 existVarious tradeoffs in performance, complexity, and implementation.

What we didn’t cover

Multiple Access

Spectral Reuse

Cellular System Design

Ad-Hoc Network Design

Networking Issues

7C29822.033-Cimini-9/97

Multiple Access (BW Sharing)

Dedicated channel assignment

Frequency Division

Time Division

Code Division

Hybrid Schemes

Code Space

Time

FrequencyCode Space

Time

FrequencyCode Space

Time

Frequency

MAC Issues

Fundamental capacity limits

Practical design

Performance for voice, data, & multimedia

Flexibility to adapt rate, power, code, etc.

RANDOM ACCESS TECHNIQUES

7C29822.038-Cimini-9/97

Random Access

Dedicated channels wasteful for datause statistical multiplexing

TechniquesAlohaCarrier sensing

Collision detection or avoidanceReservation protocolsPRMA

Retransmissions used for corrupted data

Poor throughput and delay characteristics

802.11 Wireless LANs

802.11bStandard for 2.4GHz ISM band (80 MHz)DSSS, 1.6 Mbps, 500 ft rangeStar or peer-to-peer architecture

802.11aStandard for 5GHz NII band (300 MHz)OFDM with time division20-70 Mbps (adapt. modulation/coding), variable rangeAloha access, Peer-to-peer architecture

802.11g Same as 802.11a but in the 2.4 GHz ISM band

802.11n, 802.11eStandards being developed to include MIMO or QoS

WiMax

Emerging standard for long-range wireless LANS.

Utilizes multiple antennas to get high data rates40 Mbps fixed, 15 Mbps mobile

Projected range of several kilometers

Fixed standard finalized and being certified

Could be a competitor to cellular

Intel heavily invested.

Ad-Hoc Networks

Peer-to-peer communications.No backbone infrastructure.Routing can be multihop.

Topology is dynamic.

Fully connected with different link SINRs

Design Issues

Ad-hoc networks provide a flexible network infrastructure for many emerging applications.

The capacity of such networks is generally unknown.

Transmission, access, and routing strategies for ad-hoc networks are generally ad-hoc.

Crosslayer design critical and very challenging.

Energy constraints impose interesting design tradeoffs for communication and networking.

BASE STATION

Cellular System Design

Frequencies, timeslots, or codes reused at spatially-separate locationsEfficient system design is interference-limitedBase 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 managementPower adaptationSmart antennasMultiuser detectionDynamic resource allocation

3G Cellular Design: Voice and Data

3G cellular uses CDMA (cdma2000 or WCDMA) 1.25-5 MHz bandwidthSmall differences between cdma2000 and WCDMA, but they are incompatible.Data rates on order of 2.4 Mbps (projected up to 8).Variable modulation and coding (convolutional and turbo)Starting to get traction in US/Europe/Asia

Evolution of GSM (time-division):GPRS: timeslot aggregation (140.8 Kbps)EDGE: GPRS with adaptive modulation and coding (384 Kbps)

Evolution of IS-95 (CDMA)IS-95b (CDMA): Aggregate Walsh functions (115 Kbps)

Emerging Systems

Ultrawideband

4G in wireless LANs and cellular

Sensor networks

Distributed control networks

Ultrawideband Radio (UWB)

UWB is an impulse radio: sends pulses of tens of picoseconds(10-12) to nanoseconds (10-9)

Duty cycle of only a fraction of a percent

A carrier is not necessarily needed

Uses a lot of bandwidth (GHz)

Low probability of detection

Excellent ranging capability

Multipath highly resolvable: good and badCan use OFDM to get around multipath problem.

Why is UWB Interesting?

Unique Location and Positioning properties1 cm accuracy possible

Low Power CMOS transmitters100 times lower than Bluetooth for same range/data rate

Very high data rates possible500 Mbps at ~10 feet under current regulations

7.5 Ghz of “free spectrum” in the U.S.FCC recently legalized UWB for commercial useSpectrum allocation overlays existing users, but its allowed power level is very low to minimize interference

“Moore’s Law Radio”Data rate scales with the shorter pulse widths made possible with ever faster CMOS circuits

4G Cellular/WLANs

Nobody knows what this will be

Major questionsMerging of cellular and WiFi?OFDM or CDMA?Single hop or multihop (mesh network)?QoS?What are the killer apps?

Sensor NetworksEnergy is the driving constraint

Nodes powered by nonrechargeable batteriesData flows to centralized location.Low per-node rates but up to 100,000 nodes.Data highly correlated in time and space.Nodes can cooperate in transmission, reception, compression, and signal processing.

Energy-Constrained Nodes

Each node can only send a finite number of bits.Transmit energy minimized by maximizing bit timeCircuit energy consumption increases with bit timeIntroduces a delay versus energy tradeoff for each bit

Short-range networks must consider transmit, circuit, 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.

IEEE 802.15.4 / ZigBee Radios

Low-Rate WPAN

Data rates of 20, 40, 250 kbps

Star clusters or peer-to-peer operation

Support for low latency devices

CSMA-CA channel access

Very low power consumption

Frequency of operation in ISM bands

Focus is primarily on radio and access techniques

Distributed Control over Wireless Links

Packet loss and/or delays impacts controller performance.

Controller design should be robust to network faults.

Joint application and communication network design.

Automated Vehicles- Cars- UAVs- Insect flyers

Joint Design Challenges

There is no methodology to incorporate random delays or packet losses into control system designs.

The best rate/delay tradeoff for a communication system in distributed control cannot be determined.

Current autonomous vehicle platoon controllers are not string stable with any communication delay

Can we make distributed control robust to the network?Yes, by a radical redesign of the controller and the network.

The End

Thanks!!!

Have a great winter break