© 2004 Qualcomm Flarion Technologies 1 + Lessons Unlearned in Wireless Data Rajiv Laroia Qualcomm...

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Transcript of © 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
© 2004 Qualcomm Flarion Technologies 2
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
© 2004 Qualcomm Flarion Technologies 3
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
© 2004 Qualcomm Flarion Technologies 4
Tone OrthogonalityTone Orthogonality
© 2004 Qualcomm Flarion Technologies 5
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
© 2004 Qualcomm Flarion Technologies 6
Highspeed downlink and uplink based on OFDM– no incell interference– no equalization for multipath delayspread
Ton
es
symT1/T
Time
OFDM OFDM Physical Layer DesignPhysical Layer Design
Resource Orthogonality
(>35 dB)
© 2004 Qualcomm Flarion Technologies 7
Lessons Unlearned  Channel ModelLessons Unlearned  Channel Model
0 dB80 dB
SNR = 13 dB SNR = 0 dB
Large dynamic range!
© 2004 Qualcomm Flarion Technologies 8
Channel ModelChannel Model
Fading (multipath) plus noise is the traditional wireless model
Good enough for pointtopoint links Not good enough in multiuser mobile
environment
WHY NOT?
© 2004 Qualcomm Flarion Technologies 9
Channel ModelChannel Model
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
© 2004 Qualcomm Flarion Technologies 10
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.
© 2004 Qualcomm Flarion Technologies 11
Channel ModelChannel Model
•Still fading channel  Gaussian noise N=NT+ αP
•No difference for pointtopoint.•No difference once power is set.•No difference to receiver.•Big difference for multiuser power allocation.•Big difference when self noise is not crossuser:
increases dynamic range.
© 2004 Qualcomm Flarion Technologies 12
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
nald
epen
dent
nois
e
Sig
nali
ndep
ende
ntno
ise
Null pilot noise
Slope = SNR
SN
R
Transmit power
Without signaldependent noise
With signaldependent noise
© 2004 Qualcomm Flarion Technologies 14
Channel EstimationChannel Estimation
F
T
Average channel requires 2 parameters;1. pilot snr2. nullpilot snr
Null pilots
Pilots
© 2004 Qualcomm Flarion Technologies 15
Self Noise Implications for OFDMSelf Noise Implications for OFDM
•Large dynamic range of multiuser power allocation•Better snr – higher capacity
•Many more•Superposition coding
© 2004 Qualcomm Flarion Technologies 16
Superposition CodingSuperposition Coding
C2
C2 C1 R1
R2Timesharing
Superposition
C2 C1 R1
C2
R2
Timesharing Superposition
© 2004 Qualcomm Flarion Technologies 17
Classical Superposition CodingClassical Superposition Coding
Regular information for stronger receiver is superposed on protected information
Protected infoRegular info
© 2004 Qualcomm Flarion Technologies 18
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
© 2004 Qualcomm Flarion Technologies 19
Impact of Imperfect CancellationImpact of Imperfect Cancellation
Cancellation is often imperfect, e.g., due to imperfect channel estimation
Residual selfnoise affects all degrees of freedom
Protected code Regular code
)( NP
PSNR
wxxy
r
pp
pr
)][(
ˆ
2 NEP
PSNR
wxxxyy
p
rr
prpr
© 2004 Qualcomm Flarion Technologies 20
Superposition CodingSuperposition Coding
Traditional superposition by cancellation (subtraction) is vulnerable to channel estimate errors.
© 2004 Qualcomm Flarion Technologies 21
Superposition CodingSuperposition Coding
Traditional superposition by cancellation (subtraction) is vulnerable to channel estimate errors.
© 2004 Qualcomm Flarion Technologies 22
Lessons UnlearnedLessons Unlearned
QPSK is the right constellation for relatively low rate wireless communication.
QPSK Constellation
© 2004 Qualcomm Flarion Technologies 23
What is optimal ?What is optimal ?
© 2004 Qualcomm Flarion Technologies 24
What is practical ?What is practical ?
•Capacity calculations support the idea.
© 2004 Qualcomm Flarion Technologies 25
Better than QPSK?Better than QPSK?
5 Point Constellation
© 2004 Qualcomm Flarion Technologies 26
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.
© 2004 Qualcomm Flarion Technologies 27
Practical version for OFDMPractical version for OFDM
Soft (LDPC)Decoder
Conditional distribution of position and phase.
Performs as well as QPSK/LDPC for low (1/4) rate codes.
© 2004 Qualcomm Flarion Technologies 28
Practical version for OFDMPractical version for OFDM
Soft (LDPC)Decoder
Conditional distribution of position and phase.
Performs as well as QPSK/LDPC for low (1/6) rate codes.
So What ?
© 2004 Qualcomm Flarion Technologies 29
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
© 2004 Qualcomm Flarion Technologies 30
Lessons UnlearnedLessons Unlearned
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
© 2004 Qualcomm Flarion Technologies 31
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.
© 2004 Qualcomm Flarion Technologies 32
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 pertone 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
© 2004 Qualcomm Flarion Technologies 33
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 chiplevel search required)
regular tone
beacon tone
time
Freq
uenc
y
© 2004 Qualcomm Flarion Technologies 34
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 handoff decisions
© 2004 Qualcomm Flarion Technologies 35
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
11
© 2004 Qualcomm Flarion Technologies 36
Conclusions Conclusions
The World welcomes technological improvement. If you join a wireless startup you have a good chance
of getting rich.
Many interesting things unlearned