1 1 1 The Next Generation Challenge for Software Defined Radio Mark Woh 1 , Sangwon Seo 1 , Hyunseok Lee 1 , Yuan Lin 1 , Scott Mahlke 1 , Trevor Mudge 1 , Chaitali Chakrabarti 2 , Krisztian Flautner 3 1 Advanced Computer Architecture Lab, University of Michigan 2 Department of Electrical Engineering, Arizona State University 3 ARM, Ltd.
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11 1 The Next Generation Challenge for Software Defined Radio Mark Woh 1, Sangwon Seo 1, Hyunseok Lee 1, Yuan Lin 1, Scott Mahlke 1, Trevor Mudge 1, Chaitali.
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11
1
The Next Generation Challenge for Software Defined Radio
Mark Woh1, Sangwon Seo1, Hyunseok Lee1, Yuan Lin1, Scott Mahlke1, Trevor Mudge1, Chaitali Chakrabarti2, Krisztian Flautner3
1Advanced Computer Architecture Lab, University of Michigan2Department of Electrical Engineering, Arizona State University
3ARM, Ltd.
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University of Michigan -SAMOS 2007
3G Wireless
Large Coverage
Outdoor - High Mobility
Up to 14Mbps
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Expected Wireless Growth
The growth of wireless will require more bandwidth
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4G Wireless
What we need Adaptive high performance transmission system
Great candidate for SDR
Large Coverage – 100Mbps Coverage
Outdoor - High Mobility
Macro CellsPico Cells
Isolated HotSpots – 1Gbps Coverage
Indoor – Very Low Mobility
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Next Generation Wireless – 4G
MIMOdecoder
DEMOD(OFDM)
ChannelDecoder
MIMOencoder
MOD(OFDM)
ChannelEncoder
...
...
· IFFT
· FFT · STBC· VBLAST
...
· Turbo code· LDPC code
TX
RX
Antenna
...
3 Major Components to 4G Modulation/Demodulation
Multiple-Input Multiple-Out (MIMO)
Channel Decoder/Encoders
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Modulation - OFDM
0 fsc Nfsc
….….
-Nfsc -fsc
Properties of OFDM-High Spectral Efficiency-Low Intersymbol Intereference-Flat Fading Subcarriers
Can sustain high data rates withmultiple users
Can be implemented with IFFT/FFT
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Major Component of Modulation – FFT/IFFT
Very wide data level parallelism
Requires complex operations
complex mult
x[1]
eiw
complexadd
complexsub
x[0]
X[1]
X[0]
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MIMO (Multiple Input – Multiple Out)
Previously we used single antenna systems
Now we use multiple antennas to increase the channel capacity
Diversity - High Reliability
Space Time Block Codes (STBC)
Multiplexing – High Throughput
Vertical-BLAST (V-BLAST)
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Space Time Block Codes (STBC)
CombinerChannel
EstimationChannel
Estimation
Tx1 Tx2Transmit Antennas
x[1]
-x[2]*
x[2]
x[1]*
h11 h22
h21 h12
Channel
Rx1 Rx2
Time
Receive Antennas
n11
n12
n21
n22
~x[1]~x[2]
h11
h12 h22
h21
Noise
y11 = h11x[1] + h12x[2] + n11
y12 = -h11x[2]* + h12x[1]* + n12
y21 = h21x[1] + h22x[2] + n21
y22 = -h21x[2]* + h22x[1]* + n22
Received Signal
~x[1] = h11*y11 + h12y12* + h21*y21 + h22y22*
~x[2] = h12*y11 - h11y12* + h22*y21 - h21y22*
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STBC
Requires complex operations
Low Data Movement
Highly parallelizable
ComplexMultiply
Accumulate
Channel Estimation
h22 h21 h12 h11
y21 y11
y22* y12*
Receiver Antenna 1 and 2
~x[1] ~x[2]
Conjugate+Negation
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University of Michigan -SAMOS 2007
Vertical-BLAST (V-BLAST)
S/P
Mod
Mod
V-Blast Detector
Demod
Demod
M Transmitters R Receivers
1 2 3 4 1 2 3 4 1 2 3 4
5 6 7 8 5 6 7 8 5 6 7 8
9 10 11 12 9 10 11 12 9 10 11 12
13 14 15 16 13 14 15 16 13 14 15 16
Data Stream of 4 TxLinear Combination
of Data
Channel Estimation
Nulling Vector
1 2 3 4
Subtract Strong Signal
Repeat
Strongest Signal
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V-BLAST
Implementation Based on Square Root Method for V-BLAST Original requires repeated pseudo-inverse calculation for finding the
strongest signal
This algorithm has reduces complexity
Complexity Requires matrix operations on complex numbers
Many Matrix Transformations
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Channel Decoding
3G Technologies in 4G Viterbi
Turbo Decoder
New to 4G LDPC
Better performance characteristics compared to Turbo and Viterbi
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LDPC
0 1 0 1 1 0 0 1
1 1 1 0 0 1 0 0
0 0 1 0 0 1 1 1
1 0 0 1 1 0 1 0
H =
E0
L0 L1 L2 L3
E1 E2 E3
L4 L5 L6 L7
L Node Original Value Message from Check Nodes Decision