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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. Structure of this talk. Motivation Multiuser MIMO and precoding schemes Distributed MIMO and synchronization
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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
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]
Increasing the Rate Prelog Factor Increase your bandwidth! Inlog Factor Increase your power exponentially!!!
MIMO Communication interference
Separate the Channels limited interference Dirty Paper Coding provides the achievable rate region
-1 Zero-Forcing
-1 L L U -1 L U U Tomlinson-Harashima Precoding
4 +2 +2 -5 -4 -3 +3 -2 -2 -1 +4 0 1 2 3 4 14 (mod 5) = 4 5 6 1 2 7 8 9 2 1 1 -9 (mod 5) = 1 Tomlinson-Harashima 3 3 -1 Modulo Compensation
-1 -1 ) mod ( mod ( ) mod mod ( ) mod mod -1 -1 L L U U U U Tomlinson-Harashima Precoding
+ + + 72 -1 + + + + + + + + + + + Blind Interference Alignment 3 slots, 4 symbols => 4/3 DoFs
Challenges • Maintaining phase synchronization between the different APs • Gathering channel state information and transmitting before the channel coherence time ends
Subcarriers OFDM Symbol Carrier Cyclic Prefix OFDM Modulation
FFT IFFT OFDM Demodulation
Symbol Alignment FFT Phase Alignment Distributed OFDM TX 1 TX 2 RX
Random Phase Carrier Frequency Offset Timing Offset Distributed OFDM TX 1 TX 2
option 1 option 2: coherence time depends on the electronics Phase Alignment What should be the effective channel matrix?
option 1 Phase Alignment What should be the effective channel matrix?
Data User Achieving Phase Synchronization Pilot Signal Master Secondaries
TDMA point-to-point Distributed MIMO Testbed Pilot Signal Master Secondaries Data Clients (4x4 MIMO)
Phase Accuracy Channel Orthogonalization Results ZFBF (2x2 MIMO)
Results Tomlinson Harashima 85% rate increase (85% of the theoretical gain) (2x2 MIMO)
Results Tomlinson Harashima 165% rate increase (55% of the theoretical gain) (4x4 MIMO)
Results Blind Interference Alignment 22% 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