2014 International Conference on Electronics Technology, Computer Science and Information processing

1. 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)

2. Content
• Introduction
– Contribution
• System Model
– Coordinated Small Cells
• Inter-User Interference Cancellation
• Channel Estimation Error
• Power Allocation
• Simulation Result
• Conclusion

3. 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

4. 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

5. 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

6. 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 C
i 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
𝑦 𝑢 𝑗
= 𝐻 𝑢 𝑗
𝑖 𝑤 𝑢 𝑗
𝑖 𝑢 𝑢 𝑗
𝑖
𝐶
𝑖=1
+ 𝑛 𝑢 𝑗
Coordinated Small Cells
SC : Small Cells
Coordinated Small Cells

7. Inter-User Interference Calculation
The pictures are taken from slide “Multi-user MIMO –Linear Precoding”, Ochi Laboratory
𝑦 𝑢 𝑗
= 𝐻 𝑢 𝑗
𝑖 𝑤 𝑢 𝑗
𝑖 𝑢 𝑢 𝑗
𝑖
𝐶
𝑖=1
+ 𝑛 𝑢 𝑗
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

8. Channel Estimation Error
Error Problem
𝐻 𝑢 𝑗
𝑒
= 𝐻 𝑢 𝑗
𝑖
+ 𝜎𝑒𝑟𝑟_𝑢 𝑗
2
Consider : Error Problem 𝜎𝑒𝑟𝑟_𝑢 𝑗
2
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 P
Loss 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).

9. Simulation Result (1)
• BD is better compare to RCI
• inter-user interference can
not be removed completely
in RCI
inter-user interference

10. 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

11. 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

12. Thank You, Q&A