Download - Communication System Design
Practical multitone architectures
Lecture 4
Vladimir Stojanović
6.973 Communication System Design – Spring 2006
Massachusetts Institute of Technology
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Loading with discrete information units
� Chow’s algorithm (rounding of waterfilling results) � Levin-Campello algorithm (greedy optimization)
� Each additional bit placed on subchannel that requires the least incremental energy for its transport
� Incremental energy ( ) � ε ( ) −ε (b − β )e b b
⎛ e b g ( ) ⎞ n 2 ⎜
n n n⎟b = log 1 +
⎝ Γ ⎠
n n n n n n
bit increment
� Efficiency of bit distribution� Can’t move a bit from one channel to another and reduce the
total energy
6.973 Communication System Design 2
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Levin-Campello (LC) algorithm- components
� Efficientizing (EF) – finding energy-efficient bit distribution � Always replace a bit distribution with a more efficient –
exhaustively search all single information unit changes at each step
Smallest energy to add a new bit
Largest energy to subtract the bit
Subtract bits from costly sub-channels and add to least costly sub-channels
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Efficientizing example
� 1+0.9D-1 channel (Pe=10-6, gap=8.8dB, PAM/QAM) � PAM and single-sideband � QAM
bn
b +1n
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6.973 Communication System Design 4
Rate adaptive solution
Need also to satisfy the energy constraint�
� E-tightness (ET) � Can’t add another bit without violating the E constraint
6.973 Communication System Design
If energy constraint violated subtract the most costly bit
If energy less than max add the bit that costs the least to add
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LC - Rate adaptive algorithm
� ET example (continue from EF example) � Start from efficient distribution that blows up the energy
constraint = 8 1 8Nε ⋅ = x
� Margin Nε 8x = =1.8dBε 5.32
� Levin-Campello Rate Adaptive algorithm � Choose any bit distribution � Make it efficient using (EF algorithm) � Make it energy tight using (ET algorithm)
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Dynamic rate adaptation
� Change the loading when channel changes � LC is a natural candidate � Keep the ET bit distribution and perturb based on
channel changes� Bit is moved from channel n to m
� Tightly coupled with channel and noise estimation � Will cover in later lectures
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6.973 Communication System Design 7
Channel partitioning� Divide the channel into a set of parallel,
independent channels
� Generalized Nyquist criterion � No interference between symbols � No interference between sub-channels
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Figure by MIT OpenCourseWare.
.
.
.
...
.
.
.
X1,k
X2,k
h(t) y(t)
n(t)x(t)
h*(T-t)
XN-1,k
XN,k
X1,k n2,k
nN,k
n1,ky1,k
y2,k
yN,k
X2,k
XN,k
Qk(MIMO)
x
ϕ1(t)
ϕ2(t)
ϕ∗1(T-t)
ϕ∗2(T-t)
ϕ∗N-1(T-t)t=T
t=T
t=T
t=T
yN-1,k
y1,k
y2,k
yN,kϕ∗N(-t)
ϕN-1(t)
ϕN(t)
++
+
+
+
(lower case yindicates normalizing||p|| factors included)
n=1
n=1k
x(t)
x(t)
=
=
h(t) * x(t) =
=
=
xn . ϕn(t)
xn,k . ϕn(t - kT)
xn,k . ϕn(t - kT) * h(t) =
xn,k . pn(t - kT)
N
N
n=1k
N
n=1k
N
pm(t) * pn(-t)||pm|| . ||pn||
*
Qk = Q(kT)
Qk = Iδk
qn,m (t)∆
Modal modulation
� Transmission with eigen-functions
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6.973 Communication System Design
06.
r(t) = h(t) * h*(-t) (-TH / 2, TH / 2)
ρn ϕn (t) =.
.
.
....
∫T / 2
-T / 2r(t - τ)ϕn(τ)dτ n = 1,..., , t [-(T - TH) / 2, (T + TH) / 2)]
X1,k
X2,k
h(t) y(t)
n(t)x(t)
h*(T-t)
XN-1,k
XN,k
n=1n=1
n=1
x
ϕ1(t)
ϕ2(t)
ϕ∗1(T-t)
ϕ∗2(T-t)
ϕ∗N-1(T-t)t=T
x(t)y(t)
==
=y(t)
t=T
t=T
t=T
yN-1,k
y1,k
y2,k
yN,kϕ∗N(-t)
xnϕn(t)
xn . [r(t) *
ϕN-1(t)
ϕN(t)
++
NN
N
. ϕn (t)
ϕn (t)] + n(t)~
(ρnxn)
Per-channel MAP is optimalProblem is vector AWGN
eigenfunctions (channel dependent)
ϕk (t ) Channel
Figure by MIT OpenCourseWare.
Convergence of multitone to modal modulation
� Modal modulation is optimal for finite symbol time � Eigenfunctions hard to compute and channel dependent
� Multitone converges to Modal modulation � As both N->inf and [-T/2, T/2]->(-inf,+inf)
� Set of eigenvalues of any autocorrelation function is unique � This set determines the performance of MM through SNR
is also a valid eigen-function for inf symbol period � Eigen-functions are not unique
�
� Corresponding eigenvalues are R(2πn/T) � No ISI on any tone since symbol period is infinite
� Each tone is AWGN channel � SBS detector is MAP optimal
� If channel is periodic (does not exist in practice) are then eigen-functions even on finite [-T/2,T/2]�
� Can use extra bandwidth in the design to make the channel “look” periodic
10
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6.973 Communication System Design
Finite symbol duration effects
� ISI corrupts the neighboring symbol � Need to leave the guardband
� Can try to create a more sinc-looking symbols in time by filtering the tones in frequency domain � Need excess bandwidth for filter roll-off
6.973 Communication System Design 11
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Discrete time channel partitioning
� Digital realization
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6.973 Communication System Design 12
X0
X1
XN-2
XN-1
m0
m1
mN-2
mN-1
+ +x
1/T 1/T
DAC
DA
C
x(t)
(t) (-t)(t)h
(t)n
*
(LPF) y(t) (LPF)
y = Px + n
f *N-1
f *N-2
f *1
f *0 Y0
Y1
YN-1
YN-2
yN-1
yN-2
y0
=
p0
p0
p0
p1
p1
py
py
pypy-1
0
0
00 0
0
0
0
xN-1
x0
x-y
x-1+
nN-1nN-1
n0
y
Figure by MIT OpenCourseWare.
Vector coding
� Creates a set of parallel channels by using SVD
singular-value decomposition of P
discrete transmitter waveforms discrete matched filters
since F is unitary N is also AWGN
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VC example
� 1+0.9D-1, N=8� Need one sample guardband
� Etot=(N+1)*E_dim=(8+1)*1=9
� SVD on
� Gives singular values � Sub-channel SNRs � Waterfilling shows only 7 dimensions can be used � Sub-channel energies � SNRs are then � Total SNR � VC capacity
� Would get 1.55bits/dim if N-> inf Cite as: Vladimir Stojanovic, course materials for 6.973 Communication System Design, Spring 2006.
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6.973 Communication System Design 14
DMT and OFDM
� Discrete multitone (DMT) and Orthogonal frequency Division Multiplexing (OFDM)
� DMT used on slowly time-varying channels � Optimize bn and En per sub-channel
� OFDM uses same channel partitioning as DMT � But uses same bn and En on all channels � Used on one-way broadcast channels
� Forms of vector coding with added restrictions � In vector coding, M,F channel dependent � Make the channel circular and make M,F channel
independent - simplify hardware implementation
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DMT/OFDM channel partitioning
� Make channel “look” circular � Repeat the tail of the symbol at its beginning
� Add cyclic prefix to each transmitted symbol CP
DMT 0 ...x 1...N Nx xν− −1...N Nx xν− − VC 0 ...x 1...N Nx xν− −0...0
2 2
� SVD can be replaced by eigen-decomposition (spectral factorization) � A discrete form of modal modulation � While SNRs are unique, many choices for M and F
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IDFT and DFT as orthogonal transformations
� DMT and OFDM use IDFT and DFT as eigen-vectors
DFT IDFT
� Proof channel gain at tone n
qn is eigen-vector of P #
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DMT/OFDM implementation
/(� Data rate penalty N N +ν )
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6.973 Communication System Design
XN-i = Xi if x(t)is real
XN-1
XN-2
X1
X0
.
.
.IDFT
.
.
.DFT
Y0
Y1
YN-2
YN-1
serial toparallel& cyclic
prefixremover
parallelto serial& cyclic
prefixinsert
Forces P to be cyclic matrix
DAC
ADC
(LPF)(LPF) y(t)
ϕ(t) h(t) ϕ (-t)
n(t)
+
1 N+v=
x(t)
1 N+v=Γ T TΓ
Figure by MIT OpenCourseWare.
One-tap frequency equalizer� Need to compensate for channel attenuation
� To recover the original constellation distance
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Figure by MIT OpenCourseWare.
Rx/Tx WindowingRectangular windowRaised cosine 5% Raised cosine 25%
Can overlap as long as sum is constant
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6.973 Communication System Design 20
1+0.9D-1 DMT example
� N=8
� Waterfilling with Etot=8 � Waste one unit on CP
lower than VC (8.1dB)
� For N=16 quickly reaches max of 8.8dB
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Complexity of DFE, VC, DMT
� Example 1+0.9D-1 channel
� MMSE-DFE, SNR=7.6 dB, 3ff, 1fb tap, 4 mac/sample
� VC, N=8, SNR=8.1 dB, 7*8/9=6.2MAC/sample
� DMT, N=8, SNR=7.6 dB, 8pt FFT/IFFT, 2.7MAC/sample
� N=16, 3.8MAC/sample, SNR=8.8 dB � DFE needs 10FF taps, 1FB tap, SNR=8.4 dB, 11MAC/sample
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Asymmetric digital subscriber line (ADSL)
� Symbol rate T=250us � Nd=256, 4.3125kHz wide
� 1/T’=2.208 MHz (CP = 40 samples) � Each time domain symbol 2*256+40=552 samples
� Hermitian symmetry creates real signal transmitted from 0-1.1MHz � First 2-3 tones near DC not used – avoid interference with voice � Tone 256 also not used, 64 reserved for pilot
� Nup=32, CP=5, each symbol 2*32+5=69 samples � Exactly 1/8 of downstream
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video switch
ADSL
ADSL
Split
Telco CO
POTS
UpDown
0 H
z
10 k
Hz
138
kHz
1.1
MH
z
frequency
12 Mbps
1.5 Mbps
psd
ADSL
ADSLAccessMux
(DSLAM)
SplitADSL
internet
POTS(or ISDN)
Switch
UPDown
Figure by MIT OpenCourseWare.
802.11a Wireless LAN example� Up to 54Mbps symmetrically (<100m) � 1-3 Tx power levels � Complex baseband
� unlike ADSL which is real baseband � N=64 (-31 … 31) (so 128 dimensions)
� Symbol length = 80 samples, CP=16 � Symbol rate 250kHz (T=4uS, T’=50ns), CPguard=0.8us
� FCC demands flat spectrum so no energy-allocation � The only knob is data rate selection
� Broadcast channel – can’t optimize bit allocation
not used
4 pilots 48 data tones
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R (Mbps) constellation code rate bn bbn
69
121824364854
BPSKBPSK
64QAM64QAM16QAM16QAM
4QAM4QAM
1/21/2
1/2 1/2
1/2
1/2
3/4
3/4
3/4
3/4
3/4
3/4
3/41/4
3/23/2
3/2
9/49/2
3/81
12
3
2436487296
144192216
40 mW
5.15 GHz 5.25 GHz20 MHz
5.35 GHz 5.725 GHz 5.825 GHz
200 mW 800 mW
52 carriers total, each ~ 300 kHz
20 MHz
Figure by MIT OpenCourseWare.
Figure by MIT OpenCourseWare.
High-level system view
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Data link control layer (DLC)
Physical radio layer (PHY)
Digital
Viterbidecoder +
descrambler
Demodulation+
deinterleaver
Guard interval
extraction +FFT
Scrambler +forward error
correction (FEC) coder
Interleaver+
modulation
IFFT +guard
intervalinsertion
Synchronization
Ana
log
front
-end
D/A
A/D
Analog
Figure by MIT OpenCourseWare.
Transceiver architecture
[2]
6.973 Communication System Design 26
FFT/IFFT
Cyclic prefix
Window
ing
DA
C
Upconvert
Synchronizer
Rem
ove prefix
AG
C&
AD
C
LNA
& D
ownconvert
Channel estim
atorP
ilot insertion
Mapper
Encoder
Interleaver
Descram
bler
Viterbi decoder
Deinterleaver
Dem
apper
Scram
bler
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Transmitter architecture detail
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MACData
ScramblerConvolutional
EncoderPuncturer
SignalMapper
Preamble
Interleaver
CyclicExtendIFFT
Modulation&
Upconvert
D/A
RF
Transmitter (Digital Components) Transmitter (Analog Components)
Figure by MIT OpenCourseWare.
Scrambling
� Need to randomize incoming data � Enables a number of tracking algorithms in
the receiver � Provides flat spectrum in the given band
pseudo-random bit sequence (prbs) generator
What is the period of this pseudo-random sequence?
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Interleaver� Protects the code from overload by burst errors � Block interleaver
� Block size is the #of coded bits in OFDM symbol (NCBPS) � Two-step permutation � Adjacent coded bits mapped
� Onto nonadjacent sub-carriers
� Alternate between less and more significant bits in the constellation – avoid long runs of low reliability LSBs
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Convolutional Encoder� Rate 1/2 convolutional encoder
� Punctured to obtain 2/3 and 3/4 rate � Omit some of the coded bits
Source Data
Encoded Data
Bit Stolen Data(sent/received data)
Bit Inserted Data
Decoded Data
Inserted Dummy Bit
Stolen Bit
Punctured Coding (r = 3/4)
Output Data B
Input Data
Output Data AX X X X X X X X X
A
A A A A A
B B B B B B1
A1 A4
6
A60
43
A3
7
A7
1 2 5 6 80 43 7
2
B2
5
B5
6
B6
8
B8
0
B0
3
B3
A A A A AA A A
B B B B B B B B B1 5 6 80
A0
43 7
1 2 5 6 80 43 7
y y y y y y y y y0 1 2 3 4 5 6 7 8
Tb Tb Tb Tb Tb Tb
B4
A5A2
B1
A8
B7
A2
g0=1338
g1=1718
� 64-state (constraint length K=7) code � Viterbi algorithm applied in the decoder
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Figure by MIT OpenCourseWare.
Signal mapper� BPSK, QPSK, 16-QAM, 64-QAM
� Data divided into groups of (1,2,4,6) bits and mapped to a constellation point (i.e. a complex number)
� Gray-coded constellation mapings
� Need the same average power for all mappings � Scale the output by KMOD
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Pilot insertion and FFT/IFFT
� Pilot insertion � Pilots BPSK, prbs modulated
� FFT and IFFT shared � Just flip the Re and Im inputs
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Spectral mask
� Cannot use last 5 tones on each side � Does not use extra windowing
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Power Spectral Density (dB)Transmit Spectrum Mask
(not to scale)
Typical Signal Spectrum(an example)
-20 dBr
-28 dBr
-40 dBr
-30 -20 -11 -9 30209 11fcFrequency (MHz)
Transmit spectrum mask
Figure by MIT OpenCourseWare.
Receiver architecture
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I and Q fromanalog
front-endADC FIR
RemoveDC
of fsetRotate FFT
Channel
FIR
Rx gainto analogfront-end Signal
detectand AGC
Auto-correlate
Frequencylock
Symboltiming
Pipelinecontrol
Channelestimate
andtracking
Deinterleave Viterbi
Rx datato MAC
correct
Figure by MIT OpenCourseWare.
Pilot tracking and channel correction
� OFDM packet structure
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8 + 8 = 16 µs
Signal Detect,AGC, DiversitySelection
Coarse Freq.Offset EstimationTiming Synchronize
Channel and Fine FrequencyOffset Estimation
RATELENGTH
SERVICE + DATA DATA
Data 1 Data 2
0.8 + 3.2 = 4.0 µs 0.8 + 3.2 = 4.0 µs 0.8 + 3.2 = 4.0 µs10 x 0.8 = 8 µs 2 x 0.8 + 2 x 3.2 = 8.0 µs
t1 T1 T2t2 t3 t4 t5 t6 t7 t8 t9t10 SIGNALGI GI GIGI2
angle adjust
to de-interleaver
compositechannel correctiondata
long2 training
long1 trainingfrom fft
fir complexinverse
pilotmagnitudemultiply
magnitudeadjust
training symbol pilots
to timing controlsymbol
timing adjust
pilots
+
channelcorrectionmultiply
pilottracking
core
rotate
Figure by MIT OpenCourseWare.
Figure by MIT OpenCourseWare.
Synchronizer
36
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6.973 Communication System Design
ProcessingData Path
NCO FFT
crosscorrelator
OutputSymbols
InputData
Tracking Data Path
MovingAverage
(16)Jc(k)
JF(k)
CombineIg.1(.)
IP
α
MovingAverage
βε
IJ*
Z-16 Z-49
PlateauDetector
Figure by MIT OpenCourseWare.
Channel estimator
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Estimation Buffer
(Circular Buffer)
Pilot SignCorrection
DelayBuffer
(D)
ReferenceSign
Correction
Sync. + FFTResidual
PhaseCorrection
SoftDemapper Deinterleaver Soft
Viterbi
Channel Estimator
MapperZero Forcing
Equalizer
HREF (k)
Y(i-D,k)Interleaver Conv. Encoder
X(i,k) =Y(i,k)
H(i-D,k)
H(i-D,k)
X(i-D,k)
Y(i-D,k)H(i-D,k) =
X(i-D,k)
X(i,k)
Figure by MIT OpenCourseWare.
First 802.11a chip
[1]
6.973 Communication System Design 38
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References� [1] T.H. Meng, B. McFarland, D. Su and J. Thomson "Design and implementation of an all-CMOS 802.11a
wireless LAN chipset," Communications Magazine, IEEE vol. 41, no. 8 SN - 0163-6804, pp. 160-168, 2003 � [2] M. Krstic, K. Maharatna, A. Troya, E. Grass and U. Jagdhold "Implementation of an IEEE 802.11a
compliant low-power baseband processor," Telecommunications in Modern Satellite, Cable and Broadcasting Service, 2003. TELSIKS 2003. 6th International Conference on vol. 1, no. SN -, pp. 97-100 vol.1, 2003.
� [3] J. Thomson, B. Baas, E.M. Cooper, J.M. Gilbert, G. Hsieh, P. Husted, A. Lokanathan, J.S. Kuskin, D. McCracken, B. McFarland, T.H. Meng, D. Nakahira, S. Ng, M. Rattehalli, J.L. Smith, R. Subramanian, L. Thon, Y.-H. Wang and R. Yu "An integrated 802.11a baseband and MAC processor," Solid-State Circuits Conference, 2002. Digest of Technical Papers. ISSCC. 2002 IEEE International vol. 1, no. SN -, pp. 126-451 vol.1, 2002.
� [4] E. Grass, K. Tittelbach-Helmrich, U. Jagdhold, A. Troya, G. Lippert, O. Kruger, J. Lehmann, K. Maharatna, K.F. Dombrowski, N. Fiebig, R. Kraemer and P. Mahonen "On the single-chip implementation of a Hiperlan/2 and IEEE 802.11a capable modem," Personal Communications, IEEE [see also IEEE Wireless Communications] vol. 8, no. 6 SN - 1070-9916, pp. 48-57, 2001.
6.973 Communication System Design 39
Cite as: Vladimir Stojanovic, course materials for 6.973 Communication System Design, Spring 200MIT OpenCourseWare (http://ocw.mit.edu/), Massachusetts Institute of Technology.
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