r2 r3 r4 r5 ap the throughput does not grow in the same way as wireless demands limited wireless...
TRANSCRIPT
A Brief Study on Distributed MIMO Systems
Hongzi Mao
ELEC5360 Principle of Digital Communication
R2
R3
R4
R5APThe throughput does not grow in the same way as wireless
demands
Limited wireless spectrum & unlimited user demands
AP R1
R6
Vision: APs grow in a distributed fashion
AP1 R1
AP2 R2
AP3 R3
Sep
ara
ted
Acc
ess
poin
tsM
ultip
le w
irele
ss device
s
The whole system works as if it were a single big MIMO system
Same frequency band
Overview
Intuition & Challenges
Mathematical concepts
Implementation & experiments
Limitation
Conclusion
Intuition & Challenges
AP2 R2
AP1 R1AP R
Traditional MIMO Distributed MIMO
Different devices sitting on different boards, with different oscillators. The phase can not be tightly synchronized. To fall back equivalent classical MIMO, frequency offset is the main challenge.
Mathematical concepts
Some theoretical works
S. Aeron and V. Saligrama. Wireless ad hoc networks: Strategies and scaling laws for the fixed SNR regime. IEEE Transactions on Inf. Theor., 53(6), 2007.
O. Simeone, O. Somekh, H. Poor, and S. Shamai. Distributed MIMO in multi-cell wireless systems via finite-capacity links. ISCCSP, 2008.
A. Ozgur, O. Leveque, and D. Tse. Hierarchical cooperation achieves optimal capacity scaling in ad hoc networks. IEEE Trans. on Info. Theor., 2007.
K. Tan, H. Liu, J. Fang, W. Wang, J. Zhang, M. Chen, and G. M. Voelker. SAM: enabling practical spatial multiple access in wireless LAN. ACM MobiCom, 2009.
Mathematical concepts
AP1 R1
AP2 R2
x1
x2
h11
h21
h12
h22
y1
y2
ωT1
ωT2
ωR1
ωR2
Mathematical concepts
AP1 R1
AP2 R2
x1
x2
h11
h21
h12
h22
y1
y2
ωT1
ωT2
ωR1
ωR2
Mathematical concepts
AP1 R1
AP2 R2
x2
h11
h21
h12
h22
y2
ωT1
ωT2
ωR1
ωR2
x1 y1
Physical meaning & Implementation
AP1 R1
AP2 R2
x2
h11
h21
h12
h22
y2
ωT1
ωT2
ωR1
ωR2
x1 y1
Transmitter 2 measures the frequency offset w. r. t. transmitter 1Need channel measurement to perform beamforming
Transmitters 1,2 then transmit signal
Physical meaning & Implementation
AP1 R1
AP2 R2
x2
h11
h21
h12
h22
y2
ωT1
ωT2
ωR1
ωR2
x1 y1
Receivers 1, 2 need to measure the frequency offset w. r. t. transmitter 1, then compensate the effect in decoding stage
Notice that the matrix left now is diagonal, meaning there is no interference
Actual implementation and protocol
H. Rahul, S. Kumar, D. Katabi. MegaMIMO: Scaling Wireless Capacity with User Demands. ACM SIGCOMM, 2012.
AP1 R1
AP2 R2
x2
h11
h21
h12
h22
y2
ωT1
ωT2
ωR1
ωR2
x1 y1
AP1Syn
AP2Syn
R1CFO
R2CFO
hj1
esthj2
esthj1
esthj2
est…
Multiple data transmission
Evaluation & Limitation
From theoretical work derivation, the throughput gain increase as N log SNR, where N is total number of antennas on independent APs.
Empirically, it is demonstrated that 10 mobile devices using 10 APs can obtain 8~9x throughput gain.
The limitation is mainly due to the synchronization error. One core measurement is interference noise ratio, where transmitters send null signals. The signal above noise flow is due to interference. It is shown that 10 APs have roughly 1.5dB interference noise.
Related work
S. Aeron and V. Saligrama. Wireless ad hoc networks: Strategies and scaling laws for the fixed SNR regime. IEEE Transactions on Inf. Theor., 53(6), 2007.
O. Simeone, O. Somekh, H. Poor, and S. Shamai. Distributed MIMO in multi-cell wireless systems via finite-capacity links. ISCCSP, 2008.
A. Ozgur, O. Leveque, and D. Tse. Hierarchical cooperation achieves optimal capacity scaling in ad hoc networks. IEEE Trans. on Info. Theor., 2007.
K. Tan, H. Liu, J. Fang, W. Wang, J. Zhang, M. Chen, and G. M. Voelker. SAM: enabling practical spatial multiple access in wireless LAN. ACM MobiCom, 2009.
K. Tan, J. Zhang, J. Fang, H. Liu, Y. Ye, S. Wang, Y. Zhang, H. Wu, W. Wang, and G. M. Voelker. Sora. High performance software radio using general purpose multi-core processors. NSDI, 2009.
H. Rahul, S. Kumar, D. Katabi. MegaMIMO: Scaling Wireless Capacity with User Demands. ACM SIGCOMM, 2012.