Networking with massive MU-MIMO

Lin Zhonghttp://recg.org

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Guiding Principles

• Spectrum is scarce

• Hardware is cheap, and getting cheaper

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Antennas

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Data 1

Omni-directional base station

Poor spatial reuse; poor power efficiency; high inter-cell interference

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Data 1Data 2

Data 3

Sectored base station

Better spatial reuse; better power efficiency; high inter-cell interference

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Data 2

Data 1Data 3

Data 5

Single-user beamforming base station

Better spatial reuse; best power efficiency; reduced inter-cell interference

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Data 2

Data 1

Data 6

Data 3

Data 4Data 5

Multi-user MIMO base station

M: # of BS antennasK: # of clients (K ≤ M)

Best spatial reuse; best power efficiency; reduced inter-cell interference

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Key benefits of MU-MIMO• High spectral efficiency

• High energy efficiency

• Low inter-cell interference

• Orthogonal to Small Cell solutions– Centralized vs. distributed antennas

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Why massive?

• More antennas Higher spectral efficiency

• More antennas Higher energy efficiency

• Simple baseband technique becomes effective

T.L. Marzetta. Noncooperative cellular wireless with unlimited numbers of base station antennas. IEEE Trans. on Wireless Comm., 2010.

Background: Beamforming

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Background: Beamforming

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=

Constructive Interference

Background: Beamforming

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=

Constructive Interference

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Destructive Interference

Background: Beamforming

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=

Destructive Interference

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Constructive Interference

Background: Beamforming

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?

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Due to environment and terminal mobility estimation has to occur quickly and periodically

BS

The CSI is then calculated at the terminal and sent back to the BSA pilot is sent from each BS antenna

Background: Channel Estimation

+

+

Align the phases at the receiver to ensure constructive interferenceFor uplink, send a pilot from theterminal then calculate CSI at BS

Path Effects (Walls)Uplink?

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Background: Multi-user MIMO

BS

M: # of BS antennas K: # of clients

K ≤ M

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Multi-user MIMO: Precoding

BS

(M x 1 matrix)(Kx1 matrix)

M: # of BS antennas K: # of clients

K ≤ M

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Linear Precoding

BS

(M x 1 matrix)(Kx1 matrix)

M: # of BS antennas K: # of clients

K ≤ M

sWs

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Background: Zeroforcing Beamforming

Data 1

Null

Null

NullNullNull

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Background: Zeroforcing Beamforming

Data 2

Null

NullNull

Null

Null

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Background: Zeroforcing Beamforming

Data 2

Data 1

Data 6

Data 3

Data 4Data 5

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Background: Conjugate Beamforming

Data 1

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With more antennas

Data 1

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With even more antennas

Data 1

Data 3

Data 5

Conjugate Multi-user Beamforming

Data 1

Data 6

Data 2

Data 4

Conjugate approaches Zeroforcing as M/K∞

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Conjugate vs. Zeroforcing

• Trivial computation

• Suboptimal capacity

• Scalable

• Nontrivial computation

• Close to capacity achieving

• Not scalable

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Recap

1) Estimate channels

2) Calculate weights

3) Apply linear precoding

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Scalability Challenges

1) Estimate channels– M+K pilots, then M•K feedback

2) Calculate weights– O(M•K2), non-parallelizable, centralized

data

3) Apply linear precoding– O(M•K), then O(M) data transport

Argos’ Solutions

1) Estimate channels– New reciprocal calibration method

2) Calculate weights– Novel distributed beamforming method

3) Apply linear precoding– Carefully designed scalable architecture

O(M•K) → O(K)

O(M•K2) → O(K)

O(M•K) → O(K)

C. Shepard et al. Argos: Practical many-antenna base stations. ACM MobiCom, 2012.

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Solution: Argos ArchitectureCentral

Controller

Argos Hub

Argos Hub

Argos Hub

Module

Module

Module

Module

Module

…

…

…

Data Backhaul

ModuleRadio Radio Radio…

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Argos ImplementationCentral

Controller

Argos Hub

Module

Module

Module

…Central

Controller(PC with MATLAB)

Sync Pulse

Ethernet

Clock Distribution

Argos Hub Argos

Interconnect

WARP ModuleFPGA

Power PC

FPGA FabricHardware

ModelPeripherals and Other

I/O

Clock Board

Daughter

Cards

Radio 4

Radio 3

Radio 2

Radio 1

WARP ModuleFPGA

Power PC

FPGA FabricHardware

ModelPeripherals and Other

I/O

Clock Board

Daughter

Cards

Radio 4

Radio 3

Radio 2

Radio 1

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………

Ethe

rne

t

WARP ModuleFPGA

Power PC

FPGA FabricHardware

ModelPeripherals and Other

I/O

Clock Board

Daughter

Cards

Radio 4

Radio 3

Radio 2

Radio 1

ArgosInterconne

ct

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WARP Module

s

Central Controll

er

Argos Hub

Clock Distributio

nEtherne

t Switch

SyncDistributio

n

Argos Interconnects

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Experimental Setup• Time Division Duplex (TDD)

– Uplink and Downlink use the same band

• DownlinkListen to pilot

Calculate BF weights

Send data

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Conjugate vs. Zeroforcing

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Without considering computation

Listen to pilot

Calculate BF weights

Send data

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Linear gains as # of BS antennas increases

Capacity vs. M, with K = 15

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Linear gains as # of users increasesCapacity vs. K, with M = 64

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Considering computation

Listen to pilot

Calculate BF weights

Send data

40Zeroforcing with various hardware configurations

M = 64 K = 15

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Conclusion• First many-antenna beamforming platform– Demonstration of manyfold capacity increase

• Devised novel techniques and architecture– Unlimited Scalability

• Simplistic conjugate beamforming works

• Need adaptive solutions

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Ongoing work

A network of massive MU-MIMO base stations

• Inter-cell interference management

• Pilot contamination• Client grouping & scheduling

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~$2,000 per antenna

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Acknowledgments

http://argos.rice.edu

More BS antennas + MU-MIMO Higher efficiency & lower interference

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More BS antennas + MU-MIMO Higher efficiency & lower interference