Achieving High Data Rates in a Distributed

MIMO System

Horia Vlad Balan Ryan RogalinAntonios Michaloliakos Konstantinos Psounis

Giuseppe Caire

USC

Structure of this talk

•Motivation

•Multiuser MIMO and precoding schemes

•Distributed MIMO and synchronization

•Experimental results

Motivation•Cellular companies spend

billions for more bandwidth

•Spectrum reuse is the most promising way to increase wireless transfer rates and distributed MIMO is its ideal implementation

•In WiFi networks, with a high number of users, spectrum reuse becomes equally important

[Webb - The Future of Wireless Communication]

Enterprise WiFi

Multiuser MIMO

Shannon’s Theory

Increasing the Rate

Inlog FactorIncrease your

powerexponentially!!!

Prelog FactorIncrease your

bandwidth!

MIMO Communication

interference

Separate the Channels

limited interference

Dirty Paper Coding provides the

achievable rate region

Zero-Forcing-1

Tomlinson-Harashima Precoding

L UL U U

-1

-1L

Tomlinson-Harashima

Modulo Compensation

+2

+3

+4

-13 3

12 2

1 1

+2

-2

-9 (mod 5) = 1

414 (mod 5)

= 4

-3 1 2 3 4 5 6 7 8 9-2 -1 0-4-5

Tomlinson-Harashima Precoding

L U U

-1

-1L U U

-1

-1

) mod

) mod

) mod

(

(

(

mod

mod

mod

Blind Interference Alignment

3 slots, 4 symbols => 4/3 DoFs

+ +

77 22+ + + + + +

--11

+

++

+

+ +

Distributed MIMO

Challenges

• Maintaining phase synchronization between the different APs

• Gathering channel state information and transmitting before the channel coherence time ends

OFDM Modulation

OFDM Symbol

Cyclic Prefix

Carrier

Subcarriers

OFDM Demodulation

IFFT

FFT

Distributed OFDM

FFT

TX 1

TX 2

RX

Symbol Alignment

Phase Alignment

Distributed OFDM

TX 1

TX 2

Random

Phase

Timing Offset

Carrier Frequency

Offset

Phase Alignment

Phase Alignment

What should be the effective channel matrix?

option 1option 2: coherence time depends on the

electronics

Phase Alignment

What should be the effective channel matrix?

option 1

Achieving Phase Synchronization

Master

Secondaries

Pilot Signal

Data

User

Distributed MIMO Testbed

(4x4 MIMO)

MasterSecondaries

Pilot

Signal

Data

Clients

TDMA point-to-point

Results

Phase Accuracy

ZFBF

Channel Orthogonalization

(2x2 MIMO)

Results

Tomlinson Harashima85% rate increase(85% of the theoretical

gain)(2x2 MIMO)

Results

Tomlinson Harashima165% rate increase(55% of the theoretical

gain)(4x4 MIMO)

Results

Blind Interference Alignment22% rate increase(66% of the theoretical

gain)

MAC Layer Results• Comparing scheduling strategies

through simulation in a 4 AP, 8 users scenario

• Greedy Zero-Forcing, Tomlinson-Harashima precoding, Blind Interference Alignment

• Using TDMA as a reference point

Results

4x4 achievable rates (simulation)

Future Work

• improving the accuracy of our estimators

• combining distributed MIMO with incremental redundancy schemes

• characterize the channel quality variations of BIA in large deployments

Questions?

Thank you!