vtc-location based channel estimation for massive full-dimensional mimo systems
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Location-based Channel Estimation for Massive Full-Dimensional MIMO
Systems
Authors: Wendong Liu, Chen Qian and Zhaocheng Wang
Presenter: Qian Han
3
Abstract
Propose a two-dimensional location-based channel estimation for massive FD-MIMO systems
Intra-cell pilot reuse scheme is adopted Users with same pilots could be distinguished
by their non-overlapping A-AOAs and E-AOAs Interference is reduced and the sum capacity
could be improved
5
Introduction
Massive MIMO is a promising technology for next generation wireless communication systems
Space limitation for large antenna arrays FD-MIMO (full-dimensional MIMO, 3D-MIMO)
is proposed and rectangular antenna array Massive FD-MIMO systems reach high
capacity
6
Introduction With the same number of antennas, ULA perfomrs
better than URA More work will focus on optimizing FD-MIMO including
better precoding strategies or elevation beamforming A two-dimensional location-based channel estimation
algorithm is proposed with 2D-FFT-based post-processing is inserted after the conventional pilot-aided channel estimation
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System model A single-cell multi-user FD-MIMO system Pilot reuse: 2K users assigned with K orthogonal pilots Channel matrix between the l-th user and BS:
Pilot-aided estimated channel matrix: Antenna array size: Simplified 3D SCM
Fig. 1 K=12, single-cell pilot reuse pattern
,{ }l l xyhH
lH
y xM M
, , ,1
1 ( , )P
l l p l p l ppP
H B
P: number of paths, : large-scale fading parameter : A-AOA of the p-th path : E-AOA of the p-th path
,l p,l p,l p
1 p P
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System model Steering matrix :
Assumption: angular spread of A-AOA is small. E-AOAs are determined by locations of users.
Inner part user: Outer part user:
( , ) { }xyb B
cos cos sin, ( , )
jkD x yx yb e
0, 1, 0, 1x yx M y M
D: antenna spacing, , is the wavelength 2 /k
, min max[ , ]l ll p
min max m
arctan ,arctan , arctan ,arctanin outmid id
L L L Lr r r r
min m[ , ]in idd r r
m max[ , ]out idd r r
11
Proposal: 2D-DFT Analysis Horizontal domain:
can be seen as a single-frequency signal with Vertical domain: : single-frequency signal with 2D-DFT of tends to a 2D- function with infinity
number of antennas. Different users have different impulse position and could be distinguished in angle domain.
1 2[ , , , ]y
h h hM B b b b
cos cossin
cos cos
1
y
jkDh jkDyy
jkDM
ee
e
b
hyb cos cosh
Df
sincos cos sin1 yjkDMv jkDx jkDx e e e b
vxb sinv
Df
B
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Proposal: 2D-DFT Analysis
Perform 2D-DFT of : 11
2 ( ) 2 ( )
0 0
112 ( ) 2 ( )
0 0
| ( , ) | | || |
| | | |
yxh h v v
yxh h v v
MMj q k j q k
h vx y
MMj q k j q k
x y
x y
X k k e e
e e
M M M
Let and( ) cos coshx
D kq kN
( ) sinvy
D kq kN
( , ) B
| ( , ) |h vX k k reaches maximum value when and both are integers( )hq k( )vq k
( , , )
( , )h h x
v v y
k g N
k g N
cos cos , [0, )2( , , )
cos cos , [ , ]2
x x
h x
x
DN Ng N
DN
min max( , ) sin , [ , ]v y y yDg N N N
Means rounding operation
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Proposal: Procedure Calculate the 2D window function in angle domain
: band-pass rectangle window
: pilot-aided estimated channel : 2D-FFT of : final estimated channel
1, ( , )( , )
0, ( , )h v
I h vh v
k k Ik k
k k I
W
max max min min min max
min min max max
0, ( , , ) ( , , ) , ,02
( , , ) , ( , , ) ,
l l l l l lh x h x x
hl l l l
h x h x
g N g N NI
g N g N otherwise
max min( , ) , ( , )l lv v y v yI g N g N
IW ( , )
h vl l I I I h vk k F F W
lH
lF lH
2 ( )(1: ,1: )l l x yIFFT M MH F
lH
16
Simulation results
1. Proposed two-dimensional location-based channel estimation is better than conventional pilot-aided scheme
2. 3D MIMO improves sum capacity and can serve more users
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