1. Achieving High Data Rates in a Distributed MIMO System
Horia Vlad Balan Ryan Rogalin
Antonios Michaloliakos Konstantinos Psounis
Giuseppe Caire
USC

2. Structure of this talk Motivation Multiuser MIMO and precoding schemes
Distributed MIMO and synchronization
Experimental results

3. [Webb - The Future of Wireless Communication]
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]

4. Enterprise WiFi

5. Multiuser MIMO

6. Shannon’s Theory

7. Increasing the Rate Prelog Factor Increase your bandwidth!
Inlog Factor
Increase your power
exponentially!!!

8. MIMO Communication
interference

9. Dirty Paper Coding provides the achievable rate region
Separate the Channels
limited interference
Dirty Paper Coding provides the achievable rate region

10. Zero-Forcing -1

11. Tomlinson-Harashima PrecodingU -1 L U L

12. Tomlinson-Harashima 3 3 -1 1 2 +2 -2 1 +2 +3 +4 -9 (mod 5) = 1 4
Modulo Compensation -3 1 2 3 4 5 6 7 8 9 -2 -1 -4 -5

13. Tomlinson-Harashima PrecodingU -1
) mod (
mod L U -1

14. Blind Interference Alignment+
3 slots, 4 symbols => 4/3 DoFs + 72 + + -1 + +

15. Distributed MIMO

16. Challenges Maintaining phase synchronization between the different APs
Gathering channel state information and transmitting before the channel coherence time ends

17. OFDM Modulation
Subcarriers
Carrier
Cyclic Prefix
OFDM Symbol

18. OFDM Demodulation
IFFT
FFT

19. Distributed OFDM
Symbol
Alignment
TX 1
Phase
Alignment
TX 2 RX
FFT

20. Distributed OFDM TX 1 TX 2 Carrier Frequency Random Timing Offset
Phase
TX 1
TX 2

21. Phase Alignment

22. Phase Alignment What should be the effective channel matrix? option 1
option 2: coherence time depends on the electronics
What should be the effective channel matrix?

23. What should be the effective channel matrix?
Phase Alignment
option 1
What should be the effective channel matrix?

24. Achieving Phase Synchronization
Pilot Signal
Data
User
Master
Secondaries

25. Distributed MIMO Testbed
Pilot Signal
Master
TDMA point-to-point
Secondaries
Data
Clients
(4x4 MIMO)

26. Channel Orthogonalization
Results
Phase Accuracy
Channel Orthogonalization
ZFBF
(2x2 MIMO)

27. (85% of the theoretical gain)
Results
Tomlinson Harashima
85% rate increase
(85% of the theoretical gain)
(2x2 MIMO)

28. (55% of the theoretical gain)
Results
Tomlinson Harashima
165% rate increase
(55% of the theoretical gain)
(4x4 MIMO)

29. Results Blind Interference Alignment 22% rate increase
(66% of the theoretical gain)

30. 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 .

31. 4x4 achievable rates (simulation)
Results
4x4 achievable rates (simulation)

32. 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

33. Questions?

34. Thank you!