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