Submission
doc.: IEEE 11-15/0614r01May 2015
Alexander Maltsev, Intel
NG60 channel modeling plan
Slide 1
Authors:
Name Affiliation Address Phone Email
Alexander Maltsev Intel +7(962)5050236 [email protected]
Andrey Pudeyev Intel [email protected]
Ilya Bolotin Intel [email protected]
Carlos Cordeiro Intel [email protected]
Submission
doc.: IEEE 11-15/0614r01May 2015
Alexander Maltsev, Intel
Agenda
•Channel model requirements•NG60 use cases and modeling scenarios•Experimental measurements
– Overview– Plans
•Q-D channel model methodology– Brief introduction– Open area, Street canyon and Hotel lobby models– 802.11ad and Q-D model application to NG60: areas for further
development
•Summary / Next steps•References
Slide 2
Submission
doc.: IEEE 11-15/0614r01May 2015
Alexander Maltsev, Intel
NG60 Channel model requirements• Accurate space-time characterization of the propagation channel for
main use cases– mmWave propagation features– 3-dimensional model• Support of steerable directional antennas with no limitations on the
antenna technology– Phased antenna arrays, modular antenna arrays– Lens antennas / other prospective technologies• MIMO modes support
– Both for SLS and LLS analysis• Support of polarization characteristics of antennas and signals
– Antenna polarizations– Polarization changes during reflections• Support of non-stationary characteristics of the propagation channel.
– Mobility effects: Doppler effect from TX/RX motion, non-stationary environment – Path blockage (probability)• Channel model applicability to both system level simulation (SLS) and
PHY level (LLS) analysis Slide 3
Submission
doc.: IEEE 11-15/0614r01May 2015
Alexander Maltsev, Intel
System level and Link (PHY) level models
• System level models– Universal approach for any type/number of antennas– Channel characteristics depend on the given TX/RX positions– Should be used to produce PHY level model database (DB)• PHY level models
– Explicit DB of channel impulse responses (CIR) realizations for all required scenarios
– MIMO implementation– Option #1: SISO channel extension to MIMO case. Correlation parameters
determined from SLS model and verified by experiments (3GPP SCM and TGn -alike methodology)
– Option #2: Extend DB by inclusion additional CIR pairs for typical MIMO setups (2x2 arrays and other)
Slide 4
Submission
doc.: IEEE 11-15/0614r01May 2015
Alexander Maltsev, Intel
NG60 use cases summary [1]# Applications and Characteristics
Propagationconditions
Throughput Topology Priority (TBD)
1Ultra Short Range (USR) Communications-Static,D2D, -Streaming/Downloading
LOS only, Indoor<10cm
~10Gbps P2P Medium
28K UHD Wireless Transfer at Smart Home-Umcompressed 8K UHD Streaming
Indoor, LOS with small NLOS chance, <5m
>28Gbps P2P High
3Augmented Reality and Virtual Reality-Low Mobility, D2D -3D UHD streaming
Indoor, LOS with small NLOS chance<10m
~20Gbps P2P Low
4Data Center NG60 Inter-Rack Connectivity-Indoor Backhaul with multi-hop*
Indoor, LOS only <10m
~20GbpsP2P
P2MPLow
5
Video/Mass-Data Distribution/Video on Demand System- Multicast Streaming/Downloading- Dense Hotspots
Indoor, LOS/NLOS<100m
>20GbpsP2P
P2MPMedium
6Mobile Wi-Fi Offloading and Multi-Band Operation (low mobility )-Multi-band/-Multi-RAT Hotspot operation
Indoor/Outdoor, LOS/NLOS<100m
>20GbpsP2P
P2MPHigh
7 Mobile FronthaulingOutdoor, LOS
<200m~20Gbps
P2PP2MP
Low
8Wireless Backhauling with Single Hop-Small Cell Backhauling with single hop
Outdoor, LOS<1km
~20GbpsP2P
P2MPMedium
9Wireless Backhauling with Multi-hop-Small Cell Backhauling with multi-hop*
Outdoor, LOS<150m
~2GbpsP2P
P2MPLow
Slide 5
Submission
doc.: IEEE 11-15/0614r01May 2015
Alexander Maltsev, Intel
Use cases vs. channel scenarios• Use cases differs not only by environment, but also by throughput / latency /
topology parameters, from the other hand, the same use cases may be realized in the different environments
Slide 6
Channel modeling scenario Use cases Channel modeling approaches, commentsUltra-short range 1 Direct EM near-field calculation and measurements
Los and device to device reflections – new approach neededLiving room 2, 3 IEEE 802.11ad model [2] as a base
Enhancements: MIMO modes, Doppler and mobility effects, TX-Rx positions are changing
Data center 4 New static LOS scenario: Metallic constructions, ceiling reflections. No experimental data.
Enterprise/Mall/ExhibitionTransportation
5 LOS/NLOS, frequent human blockage, multiple reflectionsIEEE 802.11ad models for cubicle and conference room.Experimental measurements and ray tracing simulations required for models development (analysis of METIS, AIRBUS data, etc.)
Open area(Access/Fronthaul/Backhaul)
6,7,8,9 Open area channel model in MiWEBA Q-D methodology with extension to MIMO
Street canyon(Access/Fronthaul/Backhaul)
6,7,8,9 Street canyon channel model in MiWEBA Q-D methodology with extension to MIMO
Submission
doc.: IEEE 11-15/0614r01May 2015
Alexander Maltsev, Intel
Experimental measurements• Existing experimental measurements
– MiWEBA experimental campaigns (data available) [3,4]– HHI measurements (street canyon, omni, 250 MHz BW) [5]– IMC measurements (open area, directional, 800 MHz BW), [6]
– METIS experimental campaigns (raw data availability - TBD) ][7]– Ericsson (indoor/office, directional, 2 GHz BW)– Aalto (indoor: shopping mall, cafeteria; outdoor: dense urban omni/directional, 4
GHz BW),– HHI (outdoor, omni, 250 MHz BW)
– Other experimental data may be available: NIST, Huawei, universities [8]
• Desirable additional experimental measurements– Indoor/Outdoor data with high time domain resolution (2-4 GHz BW) for
Intra-cluster time parameters identification: High priority– Indoor/Outdoor data with high angular domain resolution (synthesized
aperture, very large antennas, etc.) for Intra-cluster angular parameters identification: Low priority
– Indoor/Outdoor data for closely placed antennas for SU-MIMO channel analysis: High priority
Slide 7
Submission
doc.: IEEE 11-15/0614r01May 2015
Alexander Maltsev, Intel
Q-D channel model basics• Joint map-based and statistical approach [9,10]• Parameters of the most strongest rays (D-rays) in
the given scenario explicitly obtained via ray-tracing, reflection coefficients and pathloss calculations (Fresnel formulas and Friis equation)• Random / weaker rays (R-rays) parameters taken
from the pre-defined statistical distributions (Poisson ToA, exponentially-decaying PDP, etc.)• Intra-cluster structure of the D- and R-rays built
on the base of statistical distributions• Currently three basic scenarios were
implemented in MiWEBA project: open-area, street canyon, hotel lobby, with access and backhaul links support (open-area model used for MU-MIMO performance evaluation in a small cells environment [11,12])
Slide 8
Random rays average power R-rays &
clusters
1/λ
D-rays
D-ray cluster
LOS ray
Reflected ray
timeT0 T0+τ1
power
K
Submission
doc.: IEEE 11-15/0614r01May 2015
Slide 9
Open-area access channel model: D-rays
• D-rays: Direct LOS ray and Ground-reflected ray• D-Rays calculated from geometry,
taking into account pathloss, reflection loss (Fresnel + scattering), and polarization
3 sector BS
H tx
H rx
f
Far reflector
Far wall ray, di
Random reflector
Component
Parameter Value
Direct
Delay
Direct ray delay is calculated from the model geometry:
22
D0 /
rxtxD
D
HHLd
cd
Power
Direct ray power calculated as free-space pathloss with oxygen absorption
000
D0 410log20 dAdP
, in dB
AoD 0˚ azimuth and elevation
AoA 0˚ azimuth and elevation
Ground
Delay Ground-reflected ray delay is calculated from the model geometry:
22
G0 /
rxtxG
G
HHLd
cd
Power Ground-reflected power calculated as free-space pathloss with oxygen absorption, with additional reflection loss
calculated on the base of Fresnel equations
B
BR
FRdAdP GG
ff
sin
sin10log20
410log20 0G0
f 2cos rB for horizontal polarization
22 /cos rrB f for vertical polarization
and f is a grazing angle
LHH rxtx /)tan( f
2sin
10log
80
f gF , in dB
AoD Azimuth: 0˚
Elevation: rxtxrxtxAoD HHLHHL /arctan/arctan
AoA Azimuth: 0˚
Elevation:
LHHLHH rxtxrxtxAoA /arctan/arctan
Submission
doc.: IEEE 11-15/0614r01May 2015
Slide 10
Open-area access channel model: R-rays
• R-rays– R-rays are generated as Poisson
processes with exponentially decaying profile
– AoA and AoD are uniformly distributed within limits
• Intra-cluster components– Applied to both D-rays and R-rays – Arrival also modeled as Poisson
process– AoA and AoD modeled as
independent normally distributed random variables around the central ray with RMS equal to 50
Parameter Value
Number of clusters, Ncluster 3
Cluster arrival rate, λ 0.05ns-1
Cluster power-decay constant, γ 15ns
K-factor 6dB
AOA Elevation: U[AOAG0:AOAD0]
Azimuth: U[-60:60˚ ]
AOD Elevation: U[AODG0:AODD0]
Azimuth: U[-60:60˚ ]
Parameter Value
Post-cursor rays K-factor, K 6 dB for LOS ray, 4 dB for NLOS*
Post-cursor rays power decay time, 4.5 ns
Post-cursor arrival rate, 0.31 ns-1
Post-cursor rays amplitude distribution Rayleigh
Number of post-cursor rays, N 4
*
*
*Note: Parameters may be refined by new experimental measurement results
Submission
doc.: IEEE 11-15/0614r01May 2015
Slide 11
Street canyon access channel model
• The ray-tracing analysis shows that in street canyon scenario only 4 rays have significant impact on the signal power (D-rays):– Direct LOS ray– Ground ray– Nearest wall ray– Ground-Nearest wall ray
6,0m 16,0m 6,0m
Building #1 Building #2Road
4,5m
4,5m
Sidewalk #2
Sidewalk #1
4,5m
100m
50m
Access points
UE dropareas
0,5m 0,5m
Reflected rays power PDF
Submission
doc.: IEEE 11-15/0614r01May 2015
Slide 12
Street canyon access channel model
• D-ray parameters definition is similar to Open-area case: Direct ray, two first order reflections and one second-order reflection are calculated from the geometry and material parameters (see table)
• R-rays: Poisson• Intra-cluster components: Poisson
TX
RX
Ground reflected RX image
Wall-reflected RX image
Ground and wall reflected RX
image
Parameter Value
AP height, Htx 6 m
UE height, Hrx 1.5m
AP distance from nearest wall, Dtx 4.5 m
Sidewalk width 6 m
Road width 16 m
Street length 100 m
AP-AP distance, same side 100 m
AP-AP distance, different sides 50 m
Road and sidewalk material asphalt
Road and sidewalk r 4+0.2j
Road and sidewalk roughness σg (standard deviation)
0.2 mm
Building walls material concrete
Building walls r 6.25+0.3j
Building walls roughness σw
(standard deviation) 0.5 mm
Submission
doc.: IEEE 11-15/0614r01May 2015
Slide 13
Hotel lobby access
• The ray tracing analysis of the hotel lobby shows that in such bordered area all rays up to second order are significant and should be treated as D-rays• R-rays represents reflections from
various objects in the room. Modeled as Poisson distribution with specified parameters• Intra-cluster parameters are taken from
802.11ad 60GHz indoor channel model.
15,0m
10,0
m
5,0m
1,0m
0,2m
Access point
UE droparea
Submission
doc.: IEEE 11-15/0614r01May 2015
Slide 14
Backhaul and D2D channel models
• ART Backhaul scenario– Backhaul link between two ART relay stations typically armed with very high gain and
high directional antennas. This leads to the absolute dominance of the direct LOS ray, and the other rays (which may present in this environment) are much weaker.
– D-Ray: LOS component plus small cluster
• Street canyon backhaul/fronthaul– The Street canyon backhaul/fronthaul channel model is derived from the Street canyon
access channel models by setting RX antenna height equal to AP height. The other parameters are not changed.
• D2D channel models– D2D channel models for Open area, Street canyon and Hotel lobby are derived from the
corresponding access channel models by setting TX antenna height equal to UE height. The other parameters are not changed.
Submission
doc.: IEEE 11-15/0614r01May 2015
Alexander Maltsev, Intel
802.11ad and Q-D model application for NG60: areas for development
• Update 802.11ad and Q-D model to support all NG60 use cases•MIMO mode support
– D-rays parameters are calculated on the base of antenna positions– R-rays parameters correlation for closely spaced antennas need to be
defined• Channel bonding
– Check for potential issues for double-band channels (4GHz)• Intra-cluster parameters update
– For now, all intra-cluster parameters are taken directly from IEEE 802.11ad channel model
– Intra-cluster parameters need to be refined for all new scenarios and use cases on the base of experimental measurements and ray-tracing
Slide 15
Submission
doc.: IEEE 11-15/0614r01May 2015
Alexander Maltsev, Intel
Summary / Next steps•Organization issues
– Summary of existing models– Summary of available measurement results– Identifying required experimental campaigns
•Q-D channel model update– New scenarios– Intra-cluster structure verification– MIMO mode / antenna signals correlation support
Slide 16
Submission
doc.: IEEE 11-15/0614r01May 2015
Alexander Maltsev, Intel
References1. “NG60 usage scenarios”, http://mentor.ieee.org/802.11/dcn/14/11-14-1185-00-ng60-ng60-usage-scenarios.pptx2. "Channel Models for 60 GHz WLAN Systems," IEEE 802.11ad 09/0334r8, 2010.3. MiWEBA Project #608637 homepage: http://www.miweba.eu, FP7-ICT-2013-EU-Japan, 20134. MiWEBA project #608637, ‘Deliverable D5.1, Channel Modeling and Characterization’, Public Deliverable, Intel
Editor, June 2014. 5. R. J. Weiler, M. Peter, W. Keusgen, H. Shimodaira, K. T. Gia and K. Sakaguchi, "Outdoor Millimeter-Wave Access
for Heterogeneous Networks – Path Loss and System Performance," in PIMRC, 2014.6. A. Maltsev, A. Pudeyev, I. Karls, I. Bolotin, G. Morozov , R.J. Weiler, M. Peter, W. Keusgen, M. Danchenko, A.
Kuznetsov, WWRF’ 33, 2014, Guildford, GB, “Quasi-Deterministic Approach to MmWave Channel Modeling in the FP7 MiWEBA Project”
7. METIS 2020 channel model deliverable 1.4:http://www.metis2020.com/documents/deliverables8. T. S. Rappaport, et.al., "Broadband Millimeter-Wave Propagation Measurements and Models Using Adaptive-
Beam Antennas for Outdoor Urban Cellular Communications," IEEE Trans. on Antennas and Propagation, vol. 61, pp. 1850-1859, 2013.
9. “Channel models for NG60”, http://mentor.ieee.org/802.11/dcn/14/11-14-1486-00-ng60-channel-models-in-ng60.pptx
10.A. Maltsev, A. Pudeyev, I. Karls, I. Bolotin, G. Morozov , R.J. Weiler, M. Peter, W. Keusgen “Quasi-deterministic Approach to mmWave Channel Modeling in a Non-stationary Environment”, IEEE GLOBECOM 2014, Austin, Texas, USA
11.“MU-MIMO-schemes for NG60”, http://mentor.ieee.org/802.11/dcn/15/11-15-0356-00-ng60-mu-mimo-schemes-for-ng60.pptx
12.A. Maltsev, A. Sadri, A. Pudeyev, A. Davydov, I. Bolotin, G. Morozov, “Performance evaluation of the MmWave Small Cells communication system in MU-MIMO mode”, EuCNC’2015
Slide 17