slide paper : effect of channel estimation error in coordinated small cells
DESCRIPTION
2014 International Conference on Electronics Technology, Computer Science and Information processingTRANSCRIPT
Effect of Channel Estimation Error
on Coordinated Small-Cells with Block Diagonalization
Toha Ardi Nugraha
IT Convergence Engineering
Kumoh National Institute of Technology
2014 International Conference on Electronics Technology,
Computer Science and Information processing
(ETCSIP 2014)
Content
• Introduction
– Contribution
• System Model
– Coordinated Small Cells
• Inter-User Interference Cancellation
• Channel Estimation Error
• Power Allocation
• Simulation Result
• Conclusion
Introduction
Small cells
• On of the effective solution for increasing the capacity of wireless systems
especially in the indoor public areas.
• Connected via a high-speed optical fiber backbone to the gateway.
• Easily to implement a cooperative communication scheme.
Contributions
• Propose cooperative communication scheme in smalls cells (coordinated
small cells)
• Employing BD Preceding in MIMO for multi user
• Consider channel estimation error
Introduction
• Multi-User MIMO
There are two Precoding method “Linear Precoding”,”Non Linear Precoding”
• “Linear Precording ” is not complex but low performance.
• “Non Linear Precoding” is complex but high performance.
This paper investigate two methods
• RCI (Regular Channel Inversion) form from MMSE
• Block Diagonalization (BD)
The pictures are taken from slide “Multi-user MIMO –Linear Precoding”, Ochi Laboratory
System Model
• Universal frequency reuse
• Power Small Cell 20 dBm
• Indoor Propagation Model for Small
Cell: Cost 231 Multi Wall Model
• Cooperative cells with the number of Coordinated Small Cell = 3
N-transmitter (Nt) = 2
N-receiver (Nr) = 2
• Assume user allocated in the cell edge zone.
• No backhaul problems
System Model
,1
1
(1)C
t t
i
N n
,1
1
(2)j
N
r r
u
N n
1 ... (3)j j j
C
u u uH H H
Received Signal ,1 1
j j j j j n n j
n u j
C Ci i i i i i
u u u u u u u u
i i
N
u
y H w u H w u n
Serving Small Cells Neighbor Small Cells
𝑦𝑢𝑗 = 𝐻𝑢𝑗𝑖 𝑤𝑢𝑗𝑖 𝑢𝑢𝑗𝑖
𝐶
𝑖=1
+ 𝑛𝑢𝑗 Coordinated Small Cells
SC : Small Cells Coordinated Small Cells
Inter-User Interference Calculation
The pictures are taken from slide “Multi-user MIMO –Linear Precoding”, Ochi Laboratory
𝑦𝑢𝑗 = 𝐻𝑢𝑗𝑖 𝑤𝑢𝑗𝑖 𝑢𝑢𝑗𝑖
𝐶
𝑖=1
+ 𝑛𝑢𝑗
Coordinated Small Cells
Block Diagonalization
Channel Matrix
BD forms HW
Channel State Information (CSI) is required
Example : Uj = k Un = k’ 𝑓𝑜𝑟 𝑎𝑙𝑙 𝑗 ≠ 𝑛
Channel Estimation Error
Error Problem
𝐻𝑢𝑗𝑒 = 𝐻𝑢𝑗
𝑖 + 𝜎𝑒𝑟𝑟_𝑢𝑗2
Consider : Error Problem 𝜎𝑒𝑟𝑟_𝑢𝑗2
The pictures are taken from slide “Multi-user MIMO –Linear Precoding”, Ochi Laboratory
CSI = V
Power Allocation (Water Filling) [6]
2 2 2
1
1(8)
j
jj j j
N
u c
uu u u
P PLoss N Loss Loss
[6] S. Y. Shin and T. Nugraha, “Cooperative water filling (coopwf) algorithm for small cell networks,”
in ICT Convergence (ICTC), 2013 International Conference on, (2013).
Simulation Result (1)
• BD is better compare to RCI
• inter-user interference can
not be removed completely
in RCI
inter-user interference
Simulation Result (2)
BD can manage the impact channel estimation problem in coordianated
small cells with zero mean and variance of = 0.5 and 1
Conclusion
• This paper investigated coordinated small cell with channel estimation
problem
• Block Diagonalization precoding was adopted to mitigate inter-user
interference
• Coordinated small cells with BD showed good performance compare to the
previous algorithm.
• Coordinated small cells that have error channel estimation in BD precoding
can manage the performance the impact channel estimation problem
compare to previous algorithm
Thank You, Q&A