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Christian Doppler Laboratory forDependable Wireless Connectivity for the Society in Motion
Three-Dimensional Beamforming
Fjolla Ademaj15.11.2016
Dependable Wireless Connectivity for the Society in Motion
Studying 3D channel models
I Channel models on system-level tools commonly 2-dimensional (2D)
I 3GPP Spatial Channel Model (SCM)I A geometric stochastic modelI Only linear antenna arrays can be inspected with 2D channel models
I Three-Dimensional (3D) channel model enable investigations onI Full-dimension MIMOI 3D Beamforming
Slide 2 / 19
Dependable Wireless Connectivity for the Society in Motion
Studying 3D channel models
I Channel models on system-level tools commonly 2-dimensional (2D)
I 3GPP Spatial Channel Model (SCM)I A geometric stochastic modelI Only linear antenna arrays can be inspected with 2D channel models
I Three-Dimensional (3D) channel model enable investigations onI Full-dimension MIMOI 3D Beamforming
Slide 2 / 19
Dependable Wireless Connectivity for the Society in Motion
Studying 3D channel models
I Channel models on system-level tools commonly 2-dimensional (2D)
I 3GPP Spatial Channel Model (SCM)I A geometric stochastic modelI Only linear antenna arrays can be inspected with 2D channel models
I Three-Dimensional (3D) channel model enable investigations onI Full-dimension MIMOI 3D Beamforming
Slide 2 / 19
Dependable Wireless Connectivity for the Society in Motion
Studying 3D channel models
I Channel models on system-level tools commonly 2-dimensional (2D)
I 3GPP Spatial Channel Model (SCM)I A geometric stochastic modelI Only linear antenna arrays can be inspected with 2D channel models
I Three-Dimensional (3D) channel model enable investigations onI Full-dimension MIMOI 3D Beamforming
Slide 2 / 19
Dependable Wireless Connectivity for the Society in Motion
Studying 3D channel models
I Channel models on system-level tools commonly 2-dimensional (2D)
I 3GPP Spatial Channel Model (SCM)I A geometric stochastic modelI Only linear antenna arrays can be inspected with 2D channel models
I Three-Dimensional (3D) channel model enable investigations onI Full-dimension MIMOI 3D Beamforming
Slide 2 / 19
Dependable Wireless Connectivity for the Society in Motion
Studying 3D channel models
I Channel models on system-level tools commonly 2-dimensional (2D)
I 3GPP Spatial Channel Model (SCM)I A geometric stochastic modelI Only linear antenna arrays can be inspected with 2D channel models
I Three-Dimensional (3D) channel model enable investigations onI Full-dimension MIMOI 3D Beamforming Antenna array
Slide 2 / 19
Dependable Wireless Connectivity for the Society in Motion
Contents
Modeling the wireless channel in 3-dimensions
Complexity- Simulation run times
Massive MIMO: Spatial resolution of planar antenna arrays
Conclusion and Outlook
Slide 3 / 19
Dependable Wireless Connectivity for the Society in Motion
Overview
Modeling the wireless channel in 3-dimensions
Complexity- Simulation run times
Massive MIMO: Spatial resolution of planar antenna arrays
Conclusion and Outlook
Dependable Wireless Connectivity for the Society in Motion
Modeling the wireless channel in 3-dimensions
The 3GPP 3D channel model in Vienna LTE-A system-level simulator
I Considers elevation and azimuth
I Incorporates planar antenna arrays
z
x
y
x
y
z
θTX,m
ϕTX,m
θRX,m
ϕRX,m
Cluster
BS
UEPaths
Azimuth
Elevation
Slide 4 / 19
Dependable Wireless Connectivity for the Society in Motion
Reduction in complexity
I The 3GPP 3D model imposes high complexity
I Complexity reduction by:I Partition the scenario into equally sized cubesI Within a cube UE experiences the same propagation conditions
I Spatial resolution 1 mI Temporal resolution 1 msI UE speed v = [7.5, 0, 0] km/h
I Change the cube each 36 sub-frames
Temporal resolution refers to the length of one LTE sub-frame
Slide 5 / 19
Dependable Wireless Connectivity for the Society in Motion
Reduction in complexity
I The 3GPP 3D model imposes high complexity
I Complexity reduction by:I Partition the scenario into equally sized cubesI Within a cube UE experiences the same propagation conditions
I Spatial resolution 1 mI Temporal resolution 1 msI UE speed v = [7.5, 0, 0] km/h
I Change the cube each 36 sub-frames
Temporal resolution refers to the length of one LTE sub-frame
Slide 5 / 19
Dependable Wireless Connectivity for the Society in Motion
Reduction in complexity
I The 3GPP 3D model imposes high complexity
I Complexity reduction by:I Partition the scenario into equally sized cubesI Within a cube UE experiences the same propagation conditions
I Spatial resolution 1 mI Temporal resolution 1 msI UE speed v = [7.5, 0, 0] km/h
I Change the cube each 36 sub-frames
Temporal resolution refers to the length of one LTE sub-frame
Slide 5 / 19
Dependable Wireless Connectivity for the Society in Motion
Reduction in complexity
I The 3GPP 3D model imposes high complexity
I Complexity reduction by:I Partition the scenario into equally sized cubesI Within a cube UE experiences the same propagation conditions
I Spatial resolution 1 mI Temporal resolution 1 msI UE speed v = [7.5, 0, 0] km/h
I Change the cube each 36 sub-frames
Temporal resolution refers to the length of one LTE sub-frame
Slide 5 / 19
Dependable Wireless Connectivity for the Society in Motion
Reduction in complexity
I The 3GPP 3D model imposes high complexity
I Complexity reduction by:I Partition the scenario into equally sized cubesI Within a cube UE experiences the same propagation conditions
1 m
UE
1 m1
m
z
x
y
v
I Spatial resolution 1 mI Temporal resolution 1 msI UE speed v = [7.5, 0, 0] km/h
I Change the cube each 36 sub-frames
Temporal resolution refers to the length of one LTE sub-frame
Slide 5 / 19
Dependable Wireless Connectivity for the Society in Motion
Reduction in complexity
I The 3GPP 3D model imposes high complexity
I Complexity reduction by:I Partition the scenario into equally sized cubesI Within a cube UE experiences the same propagation conditions
1 m
UE
1 m1
m
z
x
y
v
I Spatial resolution 1 mI Temporal resolution 1 msI UE speed v = [7.5, 0, 0] km/h
I Change the cube each 36 sub-frames
Temporal resolution refers to the length of one LTE sub-frame
Slide 5 / 19
Dependable Wireless Connectivity for the Society in Motion
Reduction in complexity
I The 3GPP 3D model imposes high complexity
I Complexity reduction by:I Partition the scenario into equally sized cubesI Within a cube UE experiences the same propagation conditions
1 m
UE
1 m1
m
z
x
y
v
I Spatial resolution 1 mI Temporal resolution 1 msI UE speed v = [7.5, 0, 0] km/h
I Change the cube each 36 sub-frames
Temporal resolution refers to the length of one LTE sub-frame
Slide 5 / 19
Dependable Wireless Connectivity for the Society in Motion
Calibration: Zenith spread
I Comparing system-level simulations and 3GPP TR 36.873 results
0 10 20 30 40 50 600
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
Zenith spread of departure [°]
ECD
F
3GPP - data from 21 sources
3GPP - median from 21 sources
Vienna LTE-A System-Level simulator
0 10 20 30 40 50 600
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
Zenith spread of arrival [°]
ECD
F
3GPP - data from 21 sources
3GPP - median from 21 sources
Vienna LTE-A System-Level simulator
Slide 6 / 19
Dependable Wireless Connectivity for the Society in Motion
Overview
Modeling the wireless channel in 3-dimensions
Complexity- Simulation run times
Massive MIMO: Spatial resolution of planar antenna arrays
Conclusion and Outlook
Dependable Wireless Connectivity for the Society in Motion
Simulation run times
I A network of seven hexagonally arranged macro-sites, each employing threeeNodeB sectors
I Evaluate the simulation complexity [Ademaj et al., a]:I Number of interfering links Nsector = {2, 8, 14, 20}I Number of UEs per sector K = {2, 20, 50}I Number of antenna elements M = {8, 24, 40, 80}I Simulation length NTTI = {10, 50, 100}
Slide 7 / 19
Dependable Wireless Connectivity for the Society in Motion
Simulation run times
I A network of seven hexagonally arranged macro-sites, each employing threeeNodeB sectors
I Evaluate the simulation complexity [Ademaj et al., a]:I Number of interfering links Nsector = {2, 8, 14, 20}I Number of UEs per sector K = {2, 20, 50}I Number of antenna elements M = {8, 24, 40, 80}I Simulation length NTTI = {10, 50, 100}
Slide 7 / 19
Dependable Wireless Connectivity for the Society in Motion
Simulation run times
I A network of seven hexagonally arranged macro-sites, each employing threeeNodeB sectors
I Evaluate the simulation complexity [Ademaj et al., a]:I Number of interfering links Nsector = {2, 8, 14, 20}I Number of UEs per sector K = {2, 20, 50}I Number of antenna elements M = {8, 24, 40, 80}I Simulation length NTTI = {10, 50, 100}
Slide 7 / 19
Dependable Wireless Connectivity for the Society in Motion
Simulation run times
I A network of seven hexagonally arranged macro-sites, each employing threeeNodeB sectors
I Evaluate the simulation complexity [Ademaj et al., a]:I Number of interfering links Nsector = {2, 8, 14, 20}I Number of UEs per sector K = {2, 20, 50}I Number of antenna elements M = {8, 24, 40, 80}I Simulation length NTTI = {10, 50, 100}
Slide 7 / 19
Dependable Wireless Connectivity for the Society in Motion
Simulation run times
I A network of seven hexagonally arranged macro-sites, each employing threeeNodeB sectors
I Evaluate the simulation complexity [Ademaj et al., a]:I Number of interfering links Nsector = {2, 8, 14, 20}I Number of UEs per sector K = {2, 20, 50}I Number of antenna elements M = {8, 24, 40, 80}I Simulation length NTTI = {10, 50, 100}
... ... ...
Co-pol
Q={
2, 6
, 10,
20}
p0 p2 p1 p3
λ/2
λ/2
ω1(θtilt)
ωQ(θtilt)
Slide 7 / 19
Dependable Wireless Connectivity for the Society in Motion
Simulation run times
I A network of seven hexagonally arranged macro-sites, each employing threeeNodeB sectors
I Evaluate the simulation complexity [Ademaj et al., a]:I Number of interfering links Nsector = {2, 8, 14, 20}I Number of UEs per sector K = {2, 20, 50}I Number of antenna elements M = {8, 24, 40, 80}I Simulation length NTTI = {10, 50, 100}
... ... ...
Co-pol
Q={
2, 6
, 10,
20}
p0 p2 p1 p3
λ/2
λ/2
ω1(θtilt)
ωQ(θtilt)
Slide 7 / 19
Dependable Wireless Connectivity for the Society in Motion
Simulation run times: Varying the size of antenna array
K Number of UEsNsector Number of interferers
NTTI Simulation length in TTIsM Number of antenna elements in array
M = 80M = 8M = 24M = 40
100
Simulation length N75
5025
05040
30Number K of UEs
2010
0
1
0
2
3
4
5
6× 10 5
Sim
ulat
ion
runt
ime
[s]
TTI
20
Interfering eNodeBs N15
105
05040
3020
1000
0.5
1
1.5
2× 10 4
Sim
ulat
ion
runt
ime
[s]
Number K of UEs
sector
Slide 8 / 19
Dependable Wireless Connectivity for the Society in Motion
Simulation run times: Varying the size of antenna array
K Number of UEsNsector Number of interferers
NTTI Simulation length in TTIsM Number of antenna elements in array
M = 80M = 8M = 24M = 40
100
Simulation length N75
5025
05040
30Number K of UEs
2010
0
1
0
2
3
4
5
6× 10 5
Sim
ulat
ion
runt
ime
[s]
TTI
20
Interfering eNodeBs N15
105
05040
3020
1000
0.5
1
1.5
2× 10 4
Sim
ulat
ion
runt
ime
[s]
Number K of UEs
sector
Slide 8 / 19
Dependable Wireless Connectivity for the Society in Motion
Simulation run times: Varying the size of antenna array
K Number of UEsNsector Number of interferers
NTTI Simulation length in TTIsM Number of antenna elements in array
M = 80M = 8M = 24M = 40
100
Simulation length N75
5025
05040
30Number K of UEs
2010
0
1
0
2
3
4
5
6× 10 5
Sim
ulat
ion
runt
ime
[s]
TTI
20
Interfering eNodeBs N15
105
05040
3020
1000
0.5
1
1.5
2× 10 4
Sim
ulat
ion
runt
ime
[s]
Number K of UEs
sector
Slide 8 / 19
Dependable Wireless Connectivity for the Society in Motion
Simulation run times: Varying the size of antenna array
K Number of UEsNsector Number of interferers
NTTI Simulation length in TTIsM Number of antenna elements in array
M = 80M = 8M = 24M = 40
100
Simulation length N75
5025
05040
30Number K of UEs
2010
0
1
0
2
3
4
5
6× 10 5
Sim
ulat
ion
runt
ime
[s]
TTI
20
Interfering eNodeBs N15
105
05040
3020
1000
0.5
1
1.5
2× 10 4
Sim
ulat
ion
runt
ime
[s]
Number K of UEs
sector
Slide 8 / 19
Dependable Wireless Connectivity for the Society in Motion
Simulation run times: Varying the size of antenna array
K Number of UEsNsector Number of interferers
NTTI Simulation length in TTIsM Number of antenna elements in array
M = 80M = 8M = 24M = 40
100
Simulation length N75
5025
05040
30Number K of UEs
2010
0
1
0
2
3
4
5
6× 10 5
Sim
ulat
ion
runt
ime
[s]
TTI
20
Interfering eNodeBs N15
105
05040
3020
1000
0.5
1
1.5
2× 10 4
Sim
ulat
ion
runt
ime
[s]
Number K of UEs
sector
Slide 8 / 19
Dependable Wireless Connectivity for the Society in Motion
Simulation run times: Varying the size of antenna array
K Number of UEsNsector Number of interferers
NTTI Simulation length in TTIsM Number of antenna elements in array
M = 80M = 8M = 24M = 40
100
Simulation length N75
5025
05040
30Number K of UEs
2010
0
1
0
2
3
4
5
6× 10 5
Sim
ulat
ion
runt
ime
[s]
TTI
20
Interfering eNodeBs N15
105
05040
3020
1000
0.5
1
1.5
2× 10 4
Sim
ulat
ion
runt
ime
[s]
Number K of UEs
sector
Slide 8 / 19
Dependable Wireless Connectivity for the Society in Motion
Simulation run times: Varying the size of antenna array
K Number of UEsNsector Number of interferers
NTTI Simulation length in TTIsM Number of antenna elements in array
M = 80M = 8M = 24M = 40
100
Simulation length N75
5025
05040
30Number K of UEs
2010
0
1
0
2
3
4
5
6× 10 5
Sim
ulat
ion
runt
ime
[s]
TTI
20
Interfering eNodeBs N15
105
05040
3020
1000
0.5
1
1.5
2× 10 4
Sim
ulat
ion
runt
ime
[s]
Number K of UEs
sector
Slide 8 / 19
Dependable Wireless Connectivity for the Society in Motion
Simulation run times: Varying the size of antenna array
K Number of UEsNsector Number of interferers
NTTI Simulation length in TTIsM Number of antenna elements in array
M = 80M = 8M = 24M = 40
100
Simulation length N75
5025
05040
30Number K of UEs
2010
0
1
0
2
3
4
5
6× 10 5
Sim
ulat
ion
runt
ime
[s]
TTI
20
Interfering eNodeBs N15
105
05040
3020
1000
0.5
1
1.5
2× 10 4
Sim
ulat
ion
runt
ime
[s]
Number K of UEs
sector
Slide 8 / 19
Dependable Wireless Connectivity for the Society in Motion
Throughput performance: Rayleigh versus 3GPP 3D model
I Desired channel modeled by 3GPP 3D modelI Interfering channels modeled as
I A noise-limited networkI Rayleigh fadingI The 3GPP 3D model
Slide 9 / 19
Dependable Wireless Connectivity for the Society in Motion
Throughput performance: Rayleigh versus 3GPP 3D model
I Desired channel modeled by 3GPP 3D modelI Interfering channels modeled as
I A noise-limited networkI Rayleigh fadingI The 3GPP 3D model
Slide 9 / 19
Dependable Wireless Connectivity for the Society in Motion
Throughput performance: Rayleigh versus 3GPP 3D model
I Desired channel modeled by 3GPP 3D modelI Interfering channels modeled as
I A noise-limited networkI Rayleigh fadingI The 3GPP 3D model
0 0.5 1 1.5 2 2.5 3 3.50
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
Average UE throughput [Mbit/s]
ECD
F Noise only
Slide 9 / 19
Dependable Wireless Connectivity for the Society in Motion
Throughput performance: Rayleigh versus 3GPP 3D model
I Desired channel modeled by 3GPP 3D modelI Interfering channels modeled as
I A noise-limited networkI Rayleigh fadingI The 3GPP 3D model
0 0.5 1 1.5 2 2.5 3 3.50
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
Average UE throughput [Mbit/s]
ECD
F
Rayleigh fading
Noise only
Slide 9 / 19
Dependable Wireless Connectivity for the Society in Motion
Throughput performance: Rayleigh versus 3GPP 3D model
I Desired channel modeled by 3GPP 3D modelI Interfering channels modeled as
I A noise-limited networkI Rayleigh fadingI The 3GPP 3D model
0 0.5 1 1.5 2 2.5 3 3.50
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
Average UE throughput [Mbit/s]
ECD
F
Rayleigh fading
3GPP 3D model
Noise only
Slide 9 / 19
Dependable Wireless Connectivity for the Society in Motion
Overview
Modeling the wireless channel in 3-dimensions
Complexity- Simulation run times
Massive MIMO: Spatial resolution of planar antenna arrays
Conclusion and Outlook
Dependable Wireless Connectivity for the Society in Motion
Spatial resolution of planar antenna arrays
I How does the channel impacts the spatial resolution of an antenna array?I What is the spatial separation of narrow beams in LOS and NLOS, outdoors and
indoors [Ademaj et al., b]?
90°
0°
h BSh UE
d =250 m
UE
UE d =150 mUE
d =50 mUE
θ s
Slide 10 / 19
Dependable Wireless Connectivity for the Society in Motion
Resolution of a uniform vertical linear array
Antenna array radiation pattern in elevation
w (q )1 s
w (q )2 s
w (q )3 s
w (q )M s
M
q =90°s
Slide 11 / 19
Dependable Wireless Connectivity for the Society in Motion
Resolution of a uniform vertical linear array
Antenna array radiation pattern in elevation
w (q )1 s
w (q )2 s
w (q )3 s
w (q )M s
M
q =90°s
5
10
15
20
25
60
210
30
240
0
180
120
150
150
120
90
M=1M=10M=100
Slide 11 / 19
Dependable Wireless Connectivity for the Society in Motion
Resolution of a uniform vertical linear array
Antenna array radiation pattern in elevation
w (q )1 s
w (q )2 s
w (q )3 s
w (q )M s
M
q =90°s
5
10
15
20
25
60
210
30
240
0
180
120
150
150
120
90
M=1M=10M=100
5
Slide 11 / 19
Dependable Wireless Connectivity for the Society in Motion
2D Antenna array structure
I Antenna port configuration: NTx × NRx = 4× 2I Antenna array geometry at eNodeB: NTx ×M
... ... ...
M={
1, 1
0, 1
00}
λ/2
ωM(θs)
ω2(θs)
ω1(θs)
...
p={1, 2, ..., ΝTx} r={1, ..., ΝRx}
eNodeB UE
Slide 12 / 19
Dependable Wireless Connectivity for the Society in Motion
Indoor UE: Channel energy and UE throughput
I UE height hUE = 1.5 mI UE distance dUE = 150 mI M = {1, 10, 100}I Steering angle θs = {0◦, 10◦, 20◦, · · · , 180◦}I Target angle θs = 98.9◦
Slide 13 / 19
Dependable Wireless Connectivity for the Society in Motion
Indoor UE: Channel energy and UE throughput
I UE height hUE = 1.5 mI UE distance dUE = 150 mI M = {1, 10, 100}I Steering angle θs = {0◦, 10◦, 20◦, · · · , 180◦}I Target angle θs = 98.9◦
Steering angle [°]100 120 140 160 180
Chan
nel e
nerg
y [d
B]
-150
-140
-130
-120
-110
-100
-90
-80
806040200
Steering angle [°]100 120 140 160 180
Ave
rage
UE
thro
ughp
ut [M
bit/
s]
0
10
20
30
40
50
60
70
80
806040200
Slide 13 / 19
Dependable Wireless Connectivity for the Society in Motion
Indoor UE: Channel energy and UE throughput
I UE height hUE = 1.5 mI UE distance dUE = 150 mI M = {1, 10, 100}I Steering angle θs = {0◦, 10◦, 20◦, · · · , 180◦}I Target angle θs = 98.9◦
M=1 M=10 M=100LOS NLOS
Steering angle [°]100 120 140 160 180
Chan
nel e
nerg
y [d
B]
-150
-140
-130
-120
-110
-100
-90
-80
806040200
Steering angle [°]100 120 140 160 180
Ave
rage
UE
thro
ughp
ut [M
bit/
s]
0
10
20
30
40
50
60
70
80
806040200
Slide 13 / 19
Dependable Wireless Connectivity for the Society in Motion
Indoor UE: Channel energy and UE throughput
I UE height hUE = 1.5 mI UE distance dUE = 150 mI M = {1, 10, 100}I Steering angle θs = {0◦, 10◦, 20◦, · · · , 180◦}I Target angle θs = 98.9◦
M=1 M=10 M=100LOS NLOS
Steering angle [°]100 120 140 160 180
Chan
nel e
nerg
y [d
B]
-150
-140
-130
-120
-110
-100
-90
-80
806040200
Steering angle [°]100 120 140 160 180
Ave
rage
UE
thro
ughp
ut [M
bit/
s]
0
10
20
30
40
50
60
70
80
806040200
Slide 13 / 19
Dependable Wireless Connectivity for the Society in Motion
Overview
Modeling the wireless channel in 3-dimensions
Complexity- Simulation run times
Massive MIMO: Spatial resolution of planar antenna arrays
Conclusion and Outlook
Dependable Wireless Connectivity for the Society in Motion
Conclusion
I Incorporation of the elevation dimension increases the computational complexityby more than three times
I The complexity grows roughly linearly with the number of antenna elements perantenna array
I A more optimistic view on performance observed by 3D model: simple channelmodels may underestimate the achievable performance
I In terms of spatial resolution, doubling the number of antenna elements inelevation does not double the received channel energy
I The optimal number of antenna elements - ?
Slide 14 / 19
Dependable Wireless Connectivity for the Society in Motion
Outlook: 5G System LevelThe 3GPP 3D channel model
I Reduce the model complexity by pruning the multipath componentsI Adapt the model for moving scenarios: spatial correlation and channel transitions
z
x
y
BS
Clusters
Clusters
x
y
z UE
Slide 15 / 19
Dependable Wireless Connectivity for the Society in Motion
Outlook: 5G System Level3D Channel models > 6 GHz
I 3GPP TR 38.900: Channel models for carrier frequencies 6 GHz− 100 GHz
I Covering many scenarios (rural, urban, street canyons, open area, indoorscenarios, D2D and V2V)
I Three-dimensional beamforming
Slide 16 / 19
Dependable Wireless Connectivity for the Society in Motion
Outlook: Full-dimension MIMO
I Antenna configurations for 2-dimensional antenna arraysI New transmitter architectures: TXRU modeling and two-layer mappingI New precoding strategies to support the element-level antenna structure
TXRU Transceiver Unit
Slide 17 / 19
Dependable Wireless Connectivity for the Society in Motion
Outlook: Full-dimension MIMO
I Antenna configurations for 2-dimensional antenna arraysI New transmitter architectures: TXRU modeling and two-layer mapping
I New precoding strategies to support the element-level antenna structure
TXRU Transceiver Unit
Slide 17 / 19
Dependable Wireless Connectivity for the Society in Motion
Outlook: Full-dimension MIMO
I Antenna configurations for 2-dimensional antenna arraysI New transmitter architectures: TXRU modeling and two-layer mapping
I New precoding strategies to support the element-level antenna structure
TXRU Transceiver Unit
Slide 17 / 19
Dependable Wireless Connectivity for the Society in Motion
Outlook: Full-dimension MIMO
I Antenna configurations for 2-dimensional antenna arraysI New transmitter architectures: TXRU modeling and two-layer mapping
I New precoding strategies to support the element-level antenna structure
TXRU Transceiver Unit
Slide 17 / 19
Dependable Wireless Connectivity for the Society in Motion
Outlook: Full-dimension MIMO in moving scenarios
I Beam alignment schemes for efficient UE trackingI Cars and high speed trains
http://www.profheath.org/research/millimeter-wave-cellular-systems/mmwave-for-vehicular-communications-2/
Slide 18 / 19
Christian Doppler Laboratory forDependable Wireless Connectivity for the Society in Motion
Three-Dimensional Beamforming
Fjolla Ademaj15.11.2016
Dependable Wireless Connectivity for the Society in Motion
References I
Ademaj, F., Taranetz, M., and Rupp, M.3GPP 3D MIMO Channel Model: A Holistic Implementation Guideline for Open Source SImulation Tools.EURASIP Journal on Wireless Communication Networks 2016. doi:10.1186/s13638-016-0549-9.
Ademaj, F., Taranetz, M., and Rupp, M.Evaluating the spatial resolution of 2d antenna arrays for massive mimo transmissions.The 24th European Signal Processing Conference, EUSIPCO 2016.
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