Achieving High Data Rates in a Distributed MIMO System Horia Vlad Balan Ryan Rogalin Antonios Michaloliakos Konstantinos Psounis Giuseppe Caire USC
Mar 27, 2015
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!