© 2004 qualcomm flarion technologies 1 + lessons unlearned in wireless data rajiv laroia qualcomm...

© 2004 Qualcomm Flarion Technologies 1

+

Lessons Unlearned in Lessons Unlearned in Wireless DataWireless Data

Rajiv Laroia

Qualcomm Flarion Technologies


Lessons UnlearnedLessons Unlearned

All orthogonal bases are equivalent

– CDM, TDM and OFDM

Cellular channel model is y=hx+n

OFDM is a physical layer technology

TDM is optimal for downlink data

Reuse 1 is the most efficient for data


OFDM ModulationOFDM Modulation

0 50 100 150 200 250 300 350 400 4501

2

3

4

5

6

7

8

9

symT

cpTOFDM symbol

Cyclic prefixT

f=1/T

f=2/T

f=N/T

Data bits


Tone OrthogonalityTone Orthogonality


OrthogonalityOrthogonality

Aren’t all orthogonal basis equivalent? What about Eigenbasis? Sinusoids are

Eigenfunctions of all linear time invariant systems.– Sinusoidal orthogonality is preserved under

multipath delay spread.– Other basis, e.g., Walsh functions, are not.

Sinusoids are nature’s ‘chosen’ functions– Many advantages above physical layer


High-speed downlink and uplink based on OFDM– no in-cell interference– no equalization for multipath delay-spread

Ton

es

symT1/T

Time

OFDM OFDM Physical Layer DesignPhysical Layer Design

Resource Orthogonality

(>35 dB)


Lessons Unlearned - Channel ModelLessons Unlearned - Channel Model

0 dB80 dB

SNR = 13 dB SNR = 0 dB

Large dynamic range!


Channel ModelChannel Model

Fading (multipath) plus noise is the traditional wireless model

Good enough for point-to-point links Not good enough in multi-user mobile

environment

WHY NOT?



Channel (h) uncertainty introduces additional noise

The power of this noise is proportional to signal power. Hence called ‘Self Noise’

Noise power N=NT+ αP

Self noise is a fundamental property of mobile wireless systems


Channel EstimationChannel Estimation

F

T

In a mobile environment, channel knowledge is intrinsically imperfect because there is only a finite energy available to estimate it.



•Still fading channel - Gaussian noise N=NT+ αP

•No difference for point-to-point.•No difference once power is set.•No difference to receiver.•Big difference for multi-user power allocation.•Big difference when self noise is not cross-user:

increases dynamic range.


Multi User Power AllocationMulti User Power Allocation

Transmit to two users A & B simultaneously

(at different powers) xA+xB

Receiver for user A:

•CDMA (Walsh basis) N=NT+ α(PA+PB)•Self noise is fixed if total transmit power is fixed

•OFDM (Eigenbasis) N=NT+ αPA

•Self noise depends on user signal power

© 2004 Qualcomm Flarion Technologies 13© 2004 Qualcomm Flarion Technologies 13

SNR and Self noiseSNR and Self noise

Received pilot power

Rec

eive

d si

gnal

pow

er

Tota

l noi

se p

ower

Noise power

Sig

nal-d

epen

dent

nois

e

Sig

nal-i

ndep

ende

ntno

ise

Null pilot noise

Slope = SNR

SN

R

Transmit power

Without signal-dependent noise

With signal-dependent noise


Channel EstimationChannel Estimation

F

T

Average channel requires 2 parameters;1. pilot snr2. null-pilot snr

Null pilots

Pilots


Self Noise Implications for OFDMSelf Noise Implications for OFDM

•Large dynamic range of multiuser power allocation•Better snr – higher capacity

•Many more•Superposition coding


Superposition CodingSuperposition Coding

C2

C2 C1 R1

R2Timesharing

Superposition

C2 C1 R1

C2

R2

Timesharing Superposition


Classical Superposition CodingClassical Superposition Coding

Regular information for stronger receiver is superposed on protected information

Protected infoRegular info


Receiver AlgorithmReceiver Algorithm

Joint decoder is too complex Successive decoding involves

cancellation of protected signal

Protected code Regular code (assuming perfect cancellation)

N

PSNR

wxxyy

rr

rpr

)( NP

PSNR

wxxy

r

pp

pr


Impact of Imperfect CancellationImpact of Imperfect Cancellation

Cancellation is often imperfect, e.g., due to imperfect channel estimation

Residual self-noise affects all degrees of freedom

Protected code Regular code

)( NP

PSNR

wxxy

r

pp

pr

)][(

ˆ

2 NEP

PSNR

wxxxyy

p

rr

prpr



Traditional superposition by cancellation (subtraction) is vulnerable to channel estimate errors.



QPSK is the right constellation for relatively low rate wireless communication.

QPSK Constellation


What is optimal ?What is optimal ?


What is practical ?What is practical ?

•Capacity calculations support the idea.


Better than QPSK?Better than QPSK?

5 Point Constellation


Practical version for OFDMPractical version for OFDM

… …

QPSK is 2 bits per symbol.

One out of 4 symbols (2bits) is QPSK (2 bits) = 1 bit per symbol.



Soft (LDPC)Decoder

Conditional distribution of position and phase.

Performs as well as QPSK/LDPC for low (1/4) rate codes.



Soft (LDPC)Decoder

Conditional distribution of position and phase.

Performs as well as QPSK/LDPC for low (1/6) rate codes.

So What ?


Zero symbol has no self noise!Zero symbol has no self noise!

•No cancellation of protected code•Full superposition gain available for users with very different snrs



OFDM is a physical layer technology

What are some other advantages of OFDM? Granularity of resource allocation

– Better MAC layer, QOS– Better link layer, low delay

Flash signals for cell identification


Flash SignalingFlash Signaling

High power concentrated on one or more tones for a short time.

Capacity achieving for fading channels at very low data rate, or very wide band.

Achieves minimal Eb/No requirement.


Beacon Tone Beacon Tone

Beacon is a special downlink symbol in which power of a single tone (beacon tone) is significantly (e.g., 26 dB) higher than average per-tone power– Beacon is so strong that it could never be mistaken to be

anything produced by Gaussian noise process

Beacon tone occurs once every ~100,000 symbols– Negligible overhead and interference impact


Beacon Tone Beacon Tone

Beacon can be easily detected prior to timing or frequency synchronization or channel estimation– Exploit unique property of

sinusoid tones (impossible for Walsh codes)

– Almost no additional computational complexity (no chip-level search required)

regular tone

beacon tone

time

Freq

uenc

y


Use of Beacon Tone Use of Beacon Tone

Information conveyed in beacon tone includes – Carrier location– Cell/sector ID– Symbol level timing

Some uses of Beacons– Detect a candidate base station long before

pilots are visible– Estimate path loss from cell– Make hand-off decisions


Beacon InterferenceBeacon Interference

Beacons provide impulsive noise Decode signal using saturation or

reversal metrics in decoder– Automatic cancellation

(erasure)– Protection against impulse

noise– Little impact on Gaussian noise

performance

Saturation metric

Reversal metric

Decoder metrics

-1 1

1-1


Conclusions Conclusions

The World welcomes technological improvement. If you join a wireless start-up you have a good chance

of getting rich.

Many interesting things unlearned

© 2004 qualcomm flarion technologies 1 + lessons unlearned in wireless data rajiv laroia qualcomm...

Documents

user signal power

channel gaussian noise

nt pself noise

nt paself noise

self noisenoise power

nt pa pbself noise

additional noisethe

big difference