a mixed signal mimo beamforming receiver richard tseng, ada s. y. poon, yun chiu

1
Illinois Center fo Wireless Systems A Mixed Signal MIMO Beamforming Receiver Richard Tseng, Ada S. Y. Poon, Yun Chiu C ore DLL Edge Combiners False Lock Detector R esistive Interpolation 12 phases at2G H z 4 phases at6G H z 8 phases at6G H z Reference at2G H z Large number of analog components Strong interferers easily saturate the ADCs, rendering any MIMO algorithm useless. Most research activities focus on the VLSI implementation of various MIMO algorithms and do not solve the critical problem. DSP LPF LPF LPF LPF 90 ° 90 ° LNA LNA Com plex Multiplier Com plex Multiplier Com plex Adder A/D A/D A/D A/D Simplify analog circuits, move complexity to the digital domain Solve dynamic range problem by performing beamforming and signal combining in the analog domain Many MIMO algorithms still applicable in analog domain, greatly relaxes circuit requirements. DSP Com plex M ultiplier Quantization Algorithm LPF LNA LNA Com plex M ultiplier LPF I Q I Q I Q A/D A/D Direct Conversion Implementation Matching Network LPF LN A 45˚ 90˚ 135˚ b 0 =±1 b 1 =±1 b 2 =±1 b 3 =±1 b 0 ,b 1 ,b 2 ,b 3 LPF b 2 =±1 b 3 =±1 -b 0 =±1 -b 1 =±1 SD A lgorithm v i y i Re{ v i *y i } Im{ v i *y i } D igital Dom ain A nalog Dom ain D LL LO ref 0˚ 45˚90˚135˚ Nonlinear Expansion Linear Reconstruction Decisions 10 1 10 2 10 -5 10 -4 10 -3 10 -2 10 -1 10 0 10 1 MSE M M SE vs Num ber of Bases Accuracy: •MSE α 1/M 2 Cost: •M LO Phases •M Mixers/Ant. -1.5 -1 -0.5 0 0.5 1 1.5 -1.5 -1 -0.5 0 0.5 1 1.5 Phase ShiftConstellation forM=8 Three Pronged Approach Proposed Implementation S-D in the phase domain 1 0 ] [ 2 ˆ ]) 1 [ ] [ ( ] [ ˆ ]) 1 [ ] [ ( ] 1 [ ] [ ] [ 0 ] 0 [ , all for ] [ M m M m j e m y M v m e m y Q m y m e m y Q m e m y m e e m v m y SD (N onlinear) Expansion v Linear Reconstruction v hat Analog Domain Digital Domain Scalable Architecture Novel circuits Vbp Vbn V i + V i - V o - V bleed LO + LO + LO - V o + B B B Signal Combiner Mixer Core Transconductance Stage x x x x I BB Q BB x x x x Digital algorithm Current MIMO Implementations •Quantization algorithm based on frame theory and stochastic approximation. •Complex multiplier architecture scales up to multiple LO signals and high frequencies •Core DLL runs at a lower frequency •Edges combined to produce high frequency LO signals •Copying of signals allows circuit component reuse •Algorithm MSE can be reduced to arbitrarily small values •Accurate complex multiplication •Insensitive to phase and gain mismatch This work is supported by C2S2/DARPA

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Accuracy: MSE α 1/M 2 Cost: M LO Phases M Mixers/Ant. Linear Reconstruction. Nonlinear Expansion. Decisions. Direct Conversion Implementation. - in the phase domain. Digital Domain. Analog Domain. Transconductance Stage. Mixer Core. Signal Combiner. - PowerPoint PPT Presentation

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Page 1: A Mixed Signal MIMO Beamforming Receiver Richard Tseng, Ada S. Y. Poon, Yun Chiu

Illinois Center forWireless Systems

A Mixed Signal MIMO Beamforming ReceiverRichard Tseng, Ada S. Y. Poon, Yun Chiu

Core DLL

Edge Combiners

False Lock Detector

Resistive Interpolation

12 phasesat 2GHz

4 phases at 6GHz

8 phases at 6GHz

Referenceat 2GHz

• Large number of analog components

• Strong interferers easily saturate the ADCs, rendering any MIMO algorithm useless.

• Most research activities focus on the VLSI implementation of various MIMO algorithms and do not solve the critical problem.

DSPLPF

LPF

LPF

LPF

90°

90°LNA

LNA

Complex Multiplier

Complex Multiplier

Complex Adder

A/D

A/D

A/D

A/D

• Simplify analog circuits, move complexity to the digital domain

• Solve dynamic range problem by performing beamforming and signal combining in the analog domain

• Many MIMO algorithms still applicable in analog domain, greatly relaxes circuit requirements.

DSP

ComplexMultiplier

QuantizationAlgorithm

LPF

LNA

LNA ComplexMultiplier

LPF

I

Q

I

Q

I

QA/D

A/D

Direct Conversion Implementation

Matching Network

LPF

LNA

45˚

90˚

135˚

b0=±1

b1=±1

b2=±1

b3=±1

b0, b1, b2, b3

LPF

b2=±1

b3=±1

-b0=±1

-b1=±1

SD Algorithm vi

yi

Re{vi*yi}

Im{vi*yi}

DigitalDomain

AnalogDomain

DLLLOref

0˚ 45˚ 90˚135˚

Nonlinear

Expansion

Linear

Reconstruction

Decisions

101

102

10-5

10-4

10-3

10-2

10-1

100

101

MS

E

M

MSE vs Number of Bases

Accuracy:•MSE α 1/M2

Cost:•M LO Phases•M Mixers/Ant.

-1.5 -1 -0.5 0 0.5 1 1.5-1.5

-1

-0.5

0

0.5

1

1.5Phase Shift Constellation for M=8

Three Pronged Approach

Proposed Implementation

S-D in the phase domain

1

0

][2

ˆ

])1[][(][ˆ

])1[][(]1[][][

0]0[ , allfor ][

M

m

M

mj

emyM

v

memyQmy

memyQmemyme

emvmy

SD(Nonlinear)Expansion

v Linear Reconstruction

vhat

Analog DomainDigital Domain

Scalable Architecture Novel circuits

Vbp

Vbn

Vi+ Vi

-

Vo-

Vbleed

LO+LO+LO-

Vo+

BBB

Signal CombinerMixer CoreTransconductance Stage

x

x

x

x IBB

QBBx

x

x

x

Digital algorithm

Current MIMO Implementations

•Quantization algorithm based on frame theory and stochastic approximation.

•Complex multiplier architecture scales up to multiple LO signals and high frequencies

•Core DLL runs at a lower frequency•Edges combined to produce highfrequency LO signals

•Copying of signals allows circuit component reuse

•Algorithm MSE can be reduced toarbitrarily small values

•Accurate complex multiplication•Insensitive to phase and gain mismatch

This work is supported by C2S2/DARPA