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

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Presentation on theme: "Achieving High Data Rates in a Distributed MIMO System Horia Vlad Balan Ryan Rogalin Antonios Michaloliakos Konstantinos Psounis Giuseppe Caire USC."— Presentation transcript:

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 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 Shannons Theory

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

8 MIMO Communication interferenc e

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

10 Zero-Forcing

11 Tomlinson-Harashima Precoding LU LUU L

12 Tomlinson-Harashima Modulo Compensation (mod 5) = (mod 5) =

13 Tomlinson-Harashima Precoding LUU LUU ) mod ( ( ( mod

14 Blind Interference Alignment 3 slots, 4 symbols => 4/3 DoFs

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 OFDM Symbol Cyclic Prefix Carrier Subcarrier s

18 OFDM Demodulation IFFTIFFT FFT

19 Distributed OFDM FFT TX 1 TX 2 RX Symbol Alignmen t Phase Alignmen t

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

21 Phase Alignment

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

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

24 Achieving Phase Synchronization Maste r Secondari es Pilot Signal Data User

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

26 Results Phase Accuracy ZFB F Channel Orthogonalization (2x2 MIMO)

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

28 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 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!


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