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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.

Dec 21, 2015

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Page 1: 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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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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University of Michigan -SAMOS 2007

Expected Wireless Growth

The growth of wireless will require more bandwidth

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University of Michigan -SAMOS 2007

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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University of Michigan -SAMOS 2007

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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University of Michigan -SAMOS 2007

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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University of Michigan -SAMOS 2007

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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University of Michigan -SAMOS 2007

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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University of Michigan -SAMOS 2007

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

L0

L1

L2

L3

L4

L5

L6

L7

1

1

0

1

0

1

0

1

E1 → 0 E3 → 1 1

0

0

1

0

1

0

1

E0 → 0 E1 → 0E1 → 1 E2 → 0E0 → 0 E3 → 1E0 → 1 E3 → 0E1 → 0 E2 → 1E2 → 0 E3 → 0E0 → 1 E2 → 1

E0

L0 L1 L2 L3

E1 E2 E3

L4 L5 L6 L7

1 1 0 01 1 0 1

E0

L0 L1 L2 L3

E1 E2 E3

0

L4 L5 L6 L7

1 1 0 01 1 0 1

Message Sent = [ 1 0 0 1 0 1 0 1 ]

Message Recieved = [ 1 1 0 1 0 1 0 1 ]

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LDPC

Min-Sum Decoding Used

Regular LDPC code

Can get benefit from Wide SIMD Can do the Bit Node and Check Node

Alignment of Check and Bit nodes is a problem

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SODA PE Architecture

SIMDReg.File

EX

SIMDALU+Mult

SIMDShuffle

Net-work(SSN)

WB

ScalarALU

WB

EX

ScalarRF

LocalSIMD

Memory

LocalScalar

Memory

STV

AGURF

EX

WB

AGUALU

1. SIMD pipeline

2. Scalar pipeline

4. AGU pipeline

VTS

Pred.Regs

WB

SIMDto

Scalar(VtoS)ALU

RF

DMA

GlobalMemory

SODADSP

5. DMA

3. Localmemory

System

Interco

nn

ect

SIMD – 32 Wide, 16-bit datapath, Predicate Execution

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Key 4G algorithms

100 Mbps 1 Gbps

MCycle/s MCycle/s

FFT 2x360 4x360

IFFT 2x360 4x360

STBC 240 -

V-BLAST - 1900

LDPC 7700 4x18500

4G Workload on SODA

100 Mbps 4G requires 8Ghz SODA PE

1 Gbps 4G requires 20Ghz SODA PE

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SODA With Technology Scaling

0

500

1000

1500

2000

2500

3000

3500

4000

180nm 130nm 90nm 65nm 45nm 32nm 22nm

Fre

qu

en

cy

(M

hz)

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

Po

we

r (W

)

ITRS Scaled Frequency Fixed Scaled Frequency Scaled Power

180nm 130nm 90nm 65nm 45nm 32nm 22nm

Vdd (V) 1.8 1.3 1.1 1.1 1 0.9 0.8

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We can’t do any of 4G with technology scaling on one core Would 8GHz cores even be an energy efficient solution?

What about 1Gbps? Are we ever going to get a 20GHz core?

Cannot rely on technology scaling to give us 4G for free 4G SDR will require algorithmic and architectural innovations

SDR Challenges In 4G

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University of Michigan -SAMOS 2007

4G Algorithm-Architectural Co-design

Architectural improvements (SODA II) Specialized functional units

CISC-like complex arithmetic operations

Specialized data movement hardware Less strain on the memory system

Wider SIMD

How wide can we go?

More PEs

What does the interconnect look like?

Algorithmic optimization through parallelization Reduce intra-kernel communication

Reduce memory accesses

Arithmetic is much cheaper than data movement

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Thanks

Questions?

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University of Michigan -SAMOS 2007

Successive Cancelling for V-BLAST

V-BLAST successive interference cancelling (SIC)

The ith ZF-nulling vector wi is defined as the unique minimum-norm vector satisfying

Orthogonal to the subspace spanned by the contributions to yi due to the symbols not yet estimated and cancelled and is given by the ith row of H

~

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Alamouti Scheme

Assumption: the channel remains unchanged over two consecutive symbols Rate = 1 Diversity order = 2

Simple decoding

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Advantages of Software Defined Radio

Multi-mode operations

Lower costs Faster time to market

Prototyping and bug fixes

Chip volumes

Longevity of platforms

Enables future wireless communication innovations

Cognitive radio

UWB EDGE 802.16a

802.16a Bluetooth

802.11b WCDMA 802.11n

SDR