(c) 2014 Robert W Heath Jr. WHAT STARTS HERE CHANGES THE WORLD
Robert W. Heath Jr., Ph.D., P.E.
Wireless Networking and Communications Group Department of Electrical and Computer Engineering
The University of Texas at Austin
www.profheath.org
Coverage and Capacity Analysis of mmWave Cellular Systems
(c) 2015 Robert W. Heath Jr.
Why millimeter wave?
2
U.S. DEPARTMENT O F C O MMERCE
NATIO
NA
L TELEC
OM
M
UN I C ATI O NS & INF O RM ATION
AD
MIN
ISTR
ATIO
N
MOBI
LE (A
ERON
AUTIC
AL TE
LEME
TERI
NG)
S)
5.68
5.73
5.90
5.95
6.2
6.52
5
6.68
56.
765
7.0
7.1
7.3
7.35
8.1
8.19
5
8.81
5
8.96
59.
040
9.4
9.5
9.9
9.99
510
.003
10.0
0510
.110
.15
11.1
7511
.275
11.4
11.6
11.6
5
12.0
512
.10
12.2
3
13.2
13.2
613
.36
13.4
113
.57
13.6
13.8
13.8
714
.014
.25
14.3
5
14.9
9015
.005
15.0
1015
.10
15.6
15.8
16.3
6
17.4
117
.48
17.5
5
17.9
17.9
718
.03
18.0
6818
.168
18.7
818
.919
.02
19.6
819
.80
19.9
9019
.995
20.0
0520
.010
21.0
21.4
521
.85
21.9
2422
.0
22.8
5523
.023
.223
.35
24.8
924
.99
25.0
0525
.01
25.0
725
.21
25.3
325
.55
25.6
726
.126
.175
26.4
826
.95
26.9
627
.23
27.4
127
.54
28.0
29.7
29.8
29.8
929
.91
30.0
UNITEDSTATES
THE RADIO SPECTRUM
NON-GOVERNMENT EXCLUSIVE
GOVERNMENT/ NON-GOVERNMENT SHAREDGOVERNMENT EXCLUSIVE
RADIO SERVICES COLOR LEGEND
ACTIVITY CODE
NOT ALLOCATED RADIONAVIGATION FIXED
MARITIME MOBILEFIXED
MARITIME MOBILE
FIXED
MARITIME MOBILE
Radiolocation RADIONAVIGATION
FIXED
MARITIMEMOBILE
Radiolocation
FIXED
MARITIMEMOBILE FIXED
MARITIMEMOBILE
AERONAUTICALRADIONAVIGATION
AERO
NAUT
ICAL
RADI
ONAV
IGAT
ION
Aeron
autic
alMo
bile
Mariti
meRa
diona
vigati
on(R
adio
Beac
ons)
MARI
TIME
RADI
ONAV
IGAT
ION
(RAD
IO BE
ACON
S)Ae
ronau
tical
Radio
navig
ation
(Rad
io Be
acon
s)
3 9 14 19.9
5
20.0
5
30 30 59 61 70 90 110
130
160
190
200
275
285
300
3 kHz 300 kHz
300 kHz 3 MHz
3 MHz 30 MHz
30 MHz 300 MHz
3 GHz
300 GHz
300 MHz
3 GHz
30 GHz
AeronauticalRadionavigation(Radio Beacons)
MARITIMERADIONAVIGATION(RADIO BEACONS)
Aeron
autic
alMo
bile
Mariti
meRa
diona
vigati
on(R
adio
Beac
ons)
AERO
NAUT
ICAL
RADI
ONAV
IGAT
ION
(RAD
IO BE
ACON
S)
AERONAUTICALRADIONAVIGATION(RADIO BEACONS)
AeronauticalMobile
Aeron
autic
al Mo
bile
RADI
ONAV
IGAT
ION
AER
ONAU
TICAL
RADI
ONAV
IGAT
ION
MARI
TIME
MOBI
LE AeronauticalRadionavigation
MOB
ILE (D
ISTR
ESS
AND
CALL
ING)
MARI
TIME
MOBI
LE
MARI
TIME
MOBI
LE(S
HIPS
ONL
Y)
MOBI
LE
AERO
NAUT
ICAL
RADI
ONAV
IGAT
ION
(RAD
IO B
EACO
NS)
AERO
NAUT
ICAL
RADI
ONAV
IGAT
ION
(RAD
IO B
EACO
NS)
BROADCASTING(AM RADIO)
MARI
TIME
MOBIL
E (TE
LEPH
ONY)
MARI
TIME
MOBIL
E (TE
LEPH
ONY)
MOB
ILE (D
ISTRE
SS AN
D CA
LLIN
G)
MARITIMEMOBILE
LAND MOBILE
MOBILE
FIXED STAN
DARD
FREQ
. AND
TIME
SIGN
AL (2
500k
Hz)
STAN
DARD
FREQ
. AND
TIME
SIGN
ALSp
ace R
esea
rch MARITIMEMOBILE
LAND MOBILE
MOBILE
FIXED
AERO
NAUT
ICAL
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STAN
DARD
FREQ
.
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ICAL
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ICAL
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R)
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ICAL
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E (R)
FIXED
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Radio-location
FIXED
MOBI
LE*
AMATEUR
FIXED
FIXED
FIXED
FIXED
FIXEDMARITIME
MOBILE
MOBI
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MOBI
LE*
MOBI
LEST
ANDA
RD FR
EQ. A
ND TI
ME SI
GNAL
(500
0 KHZ
)
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R)
STAN
DARD
FREQ
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ace R
esea
rch
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ICAL
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)
AERO
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R) FIXE
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BILE
*
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DCAS
TING
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TIME
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LE
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(OR) FIX
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AMAT
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MARIT
IME M
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RONA
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(OR)
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BROA
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TING
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DARD
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TIME
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AL (1
0,000
kHz)
STAN
DARD
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ace R
esea
rchAE
RONA
UTIC
AL M
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(R)
AMAT
EUR
FIXED
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ICAL
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AL M
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(OR)
FIXED
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TING
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TIME
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LE
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TING
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ATEL
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e*FIX
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TING
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DARD
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TIME
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AL (1
5,000
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DARD
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ace R
esea
rch
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NAUT
ICAL
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R)
MARI
TIME
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TING
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DARD
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ace R
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LLITE
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TING
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TING
MARI
TIME
MOBI
LE LA
ND M
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MOB
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FIXED
MOB
ILE**
MOB
ILE
FIXED
FIXED
FIXED
FIXED
FIXED
LAND
MOB
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MOB
ILE**
AMAT
EUR
AMAT
EUR
SATE
LLITE
MOB
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LAND
MOB
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MOBI
LE
MOBI
LE
FIXED
FIXED
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FIXED
FIXED
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RADIO
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LAND
MOBI
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FIXED
FIXED
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MOBIL
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BROADCASTING(TV CHANNELS 2-4)
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FIXED
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EDMO
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RADIO-LOCATION RADIO-
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und)
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(S-E)
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SATE
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(E-S
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BILE
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SATE
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(E-S
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SATE
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(E-S
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BILE
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ED
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FIXED
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FIXED
SPAC
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SEAR
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Fixed
MOBIL
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TELL
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ED SA
TELLI
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SATE
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(S-E)
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SATE
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(S-E)
FIXED
SATE
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(S-E)
FIXED
SATE
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(E-S)
FIXED
SATE
LLITE
(E-S)
FIXED
SATE
LLITE
(E-S)
FIXED
SATE
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(E-S)
FIXED
FIXED
FIXED
FIXED
FIXED
FIXED
FIXED
MET.
SATE
LLITE
(S-E)
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ite (S-
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bileSa
tellite
(S-E)
Mobile
Satell
ite (E-
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airbo
rne)
Mobile
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S)(no
airborn
e)
Mobile
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Mobile
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(S-E)
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)
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TE (S
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ateur
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(S-E)
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MOBIL
EFIX
ED
MOBIL
EFIX
ED
MOBIL
EFIX
ED
MOBIL
EFIX
ED
MOBIL
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SPAC
E RES
EARC
H(P
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R-SA
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R-SA
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MOBILE
MOBIL
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RADIO-NAVIGATION
RADIO-NAVIGATIONSATELLITE
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MOBIL
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MOBIL
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FIXED
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RADI
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RADIO-NAVIGATION
RADIO-NAVIGATIONSATELLITE
MOBILE
MOBILE
FIXED
RADIO-ASTRONOMY
FIXEDSATELLITE
(E-S)
FIXED
3.0
3.02
5
3.15
5
3.23
0
3.4
3.5
4.0
4.06
3
4.43
8
4.65
4.7
4.75
4.85
4.99
55.
003
5.00
55.
060
5.45
MARITIMEMOBILE
AMAT
EUR
AMAT
EUR
SATE
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FIXED
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RITIM
E MOB
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MOBILE
FIXED
FIXED
Land
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EDMO
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LAN
D MO
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LAND
MOB
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MAR
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ARITI
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ND M
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FIXED
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TRON
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SATE
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Fixed
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(R) (s
pace
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(R)
(space
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tellite
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AT. (E
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T. SAT
. (E-S)
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. (E-S)
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Mobile
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RADIO
ASTR
ONOM
Y
RADI
O AS
TRON
OMY
MOB
ILE S
AT. (
E-S)
FIXED
MOBI
LE
FIXED
FIXE
D(LO
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(LOS)
SPAC
ERE
SEAR
CH(s-
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)
SPAC
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N
AMAT
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TRON
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FIXED
SAT
. (S
-E)
FIXED
MOBILE
FIXEDSATELLITE (S-E)
FIXED
MOBIL
EFIX
EDSA
TELL
ITE (E
-S)
FIXED
SATE
LLITE
(E-S
)MO
BILE
FIXED
SPAC
ERE
SEAR
CH (S
-E)(De
ep Sp
ace) AE
RONA
UTIC
AL R
ADIO
NAVIG
ATIO
N
EART
HEX
PL. S
AT.
(Passi
ve)
300
325
335
405
415
435
495
505
510
525
535
1605
1615
1705
1800
1900
2000
2065
2107
2170
2173
.521
90.5
2194
2495
2501
2502
2505
2850
3000
RADIO-LOCATION
BROA
DCAS
TING
FIXED
MOBILE
AMAT
EUR
RADI
OLOC
ATIO
N
MOBIL
EFIX
EDMA
RITIM
EMO
BILE
MARI
TIME
MOBIL
E (TE
LEPH
ONY)
MARIT
IME
MOBIL
ELA
NDMO
BILE
MOBIL
EFIX
ED
30.0
30.5
6
32.0
33.0
34.0
35.0
36.0
37.0
37.5
38.0
38.2
5
39.0
40.0
42.0
43.6
9
46.6
47.0
49.6
50.0
54.0
72.0
73.0
74.6
74.8
75.2
75.4
76.0
88.0
108.
0
117.
975
121.
9375
123.
0875
123.
5875
128.
8125
132.
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136.
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7.0
137.
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137.
175
137.
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138.
0
144.
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6.0
148.
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9.9
150.
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6.24
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7.03
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7.18
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7.45
161.
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161.
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161.
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162.
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173.
217
3.4
174.
0
216.
0
220.
022
2.0
225.
0
235.
0
300
ISM – 6.78 ± .015 MHz ISM – 13.560 ± .007 MHz ISM – 27.12 ± .163 MHz
ISM – 40.68 ± .02 MHz
ISM – 24.125 ± 0.125 GHz 30 GHz
ISM – 245.0 ± 1GHzISM – 122.5 ± .500 GHzISM – 61.25 ± .250 GHz
300.
0
322.
0
328.
6
335.
4
399.
9
400.
0540
0.15
401.
0
402.
0
403.
040
6.0
406.
1
410.
0
420.
0
450.
045
4.0
455.
045
6.0
460.
046
2.537
546
2.737
546
7.537
546
7.737
547
0.0
512.
0
608.
061
4.0
698
746
764
776
794
806
821
824
849
851
866
869
894
896
9019
0190
2
928
929
930
931
932
935
940
941
944
960
1215
1240
1300
1350
1390
1392
1395
2000
2020
2025
2110
2155
2160
2180
2200
2290
2300
2305
2310
2320
2345
2360
2385
2390
2400
2417
2450
2483
.525
0026
5526
9027
00
2900
3000
1400
1427
1429
.5
1430
1432
1435
1525
1530
1535
1544
1545
1549
.5
1558
.515
5916
1016
10.6
1613
.816
26.5
1660
1660
.516
68.4
1670
1675
1700
1710
1755
1850
MARIT
IME M
OBILE
SATE
LLITE
(space
to Ear
th)MO
BILE S
ATELL
ITE (S
-E)
RADI
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ATIO
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AVIG
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NAm
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onAE
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MOBI
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**FIX
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AT
(E-
S)FIX
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FIXED FI
XED*
*LAN
D MOB
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LM)
MOBIL
E SAT
.(Sp
ace to
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RITIME
MOB
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T.(Sp
ace to
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bile(Ae
ro. TL
M)
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ATEL
LITE
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(Space
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th)AE
RONA
UTICA
L MOB
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TELLI
TE (R
)(sp
ace to
Earth)
3.0
3.1
3.3
3.5
3.6
3.65
3.7
4.2
4.4
4.5
4.8
4.94
4.99
5.0
5.15
5.25
5.35
5.46
5.47
5.6
5.65
5.83
5.85
5.92
5
6.42
5
6.52
5
6.70
6.87
5
7.02
57.
075
7.12
5
7.19
7.23
57.
25
7.30
7.45
7.55
7.75
7.90
8.02
5
8.17
5
8.21
5
8.4
8.45
8.5
9.0
9.2
9.3
9.5
10.0
10.4
510
.510
.55
10.6
10.6
8
10.7
11.7
12.2
12.7
12.7
5
13.2
513
.4
13.7
514
.0
14.2
14.4
14.4
714
.514
.714
515
.136
5
15.3
5
15.4
15.4
3
15.6
315
.716
.617
.1
17.2
17.3
17.7
17.8
18.3
18.6
18.8
19.3
19.7
20.1
20.2
21.2
21.4
22.0
22.2
122
.5
22.5
5
23.5
5
23.6
24.0
24.0
5
24.2
524
.45
24.6
5
24.7
5
25.0
5
25.2
525
.527
.0
27.5
29.5
29.9
30.0
ISM – 2450.0 ± 50 MHz
30.0
31.0
31.3
31.8
32.0
32.3
33.0
33.4
36.0
37.0
37.6
38.0
38.6
39.5
40.0
40.5
41.0
42.5
43.5
45.5
46.9
47.0
47.2
48.2
50.2
50.4
51.4
52.6
54.2
555
.78
56.9
57.0
58.2
59.0
59.3
64.0
65.0
66.0
71.0
74.0
75.5
76.0
77.0
77.5
78.0
81.0
84.0
86.0
92.0
95.0
100.
0
102.
0
105.
0
116.
0
119.
98
120.
02
126.
0
134.
0
142.
014
4.0
149.
0
150.
0
151.
0
164.
0
168.
0
170.
0
174.
5
176.
5
182.
0
185.
0
190.
0
200.
0
202.
0
217.
0
231.
0
235.
0
238.
0
241.
0
248.
0
250.
0
252.
0
265.
0
275.
0
300.
0
ISM – 5.8 ± .075 GHz
ISM – 915.0 ± 13 MHz
INTER
-SATE
LLITE
RADIO
LOCA
TION
SATE
LLITE
(E-S)
AERO
NAUT
ICAL
RADIO
NAV.
PLEASE NOTE: THE SPACING ALLOTTED THE SERVICES IN THE SPEC-TRUM SEGMENTS SHOWN IS NOT PROPORTIONAL TO THE ACTUAL AMOUNTOF SPECTRUM OCCUPIED.
AERONAUTICALMOBILE
AERONAUTICALMOBILE SATELLITE
AERONAUTICALRADIONAVIGATION
AMATEUR
AMATEUR SATELLITE
BROADCASTING
BROADCASTINGSATELLITE
EARTH EXPLORATIONSATELLITE
FIXED
FIXED SATELLITE
INTER-SATELLITE
LAND MOBILE
LAND MOBILESATELLITE
MARITIME MOBILE
MARITIME MOBILESATELLITE
MARITIMERADIONAVIGATION
METEOROLOGICALAIDS
METEOROLOGICALSATELLITE
MOBILE
MOBILE SATELLITE
RADIO ASTRONOMY
RADIODETERMINATIONSATELLITE
RADIOLOCATION
RADIOLOCATION SATELLITE
RADIONAVIGATION
RADIONAVIGATIONSATELLITE
SPACE OPERATION
SPACE RESEARCH
STANDARD FREQUENCYAND TIME SIGNAL
STANDARD FREQUENCYAND TIME SIGNAL SATELLITE
RADI
O AS
TRON
OMY
FIXED
MARITIME MOBILE
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MARITIMEMOBILE Aeronautical
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DARD
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TIME
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AL (6
0 kHz
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ALLOCATION USAGE DESIGNATIONSERVICE EXAMPLE DESCRIPTION
Primary FIXED Capital LettersSecondary Mobi le 1st Capital with lower case letters
U.S. DEPARTMENT OF COMMERCENational Telecommunications and Information AdministrationOffice of Spectrum Management
October 2003
MOBIL
EBR
OADC
ASTIN
G
TRAVELERS INFORMATION STATIONS (G) AT 1610 kHz
59-64 GHz IS DESIGNATED FORUNLICENSED DEVICES
Fixed
AERO
NAUT
ICAL
RADI
ONAV
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ION
SPAC
E RES
EARC
H (Pa
ssive
)
* EXCEPT AERO MOBILE (R)
** EXCEPT AERO MOBILE WAVELENGTH
BANDDESIGNATIONS
ACTIVITIES
FREQUENCY
3 x 107m 3 x 106m 3 x 105m 30,000 m 3,000 m 300 m 30 m 3 m 30 cm 3 cm 0.3 cm 0.03 cm 3 x 105Å 3 x 104Å 3 x 103Å 3 x 102Å 3 x 10Å 3Å 3 x 10-1Å 3 x 10-2Å 3 x 10-3Å 3 x 10-4Å 3 x 10-5Å 3 x 10-6Å 3 x 10-7Å
0 10 Hz 100 Hz 1 kHz 10 kHz 100 kHz 1 MHz 10 MHz 100 MHz 1 GHz 10 GHz 100 GHz 1 THz 1013Hz 1014Hz 1015Hz 1016Hz 1017Hz 1018Hz 1019Hz 1020Hz 1021Hz 1022Hz 1023Hz 1024Hz 1025Hz
THE RADIO SPECTRUMMAGNIFIED ABOVE3 kHz 300 GHz
VERY LOW FREQUENCY (VLF)Audible Range AM Broadcast FM Broadcast Radar Sub-Millimeter Visible Ultraviolet Gamma-ray Cosmic-ray
Infra-sonics Sonics Ultra-sonics Microwaves InfraredP L S XC Radar
Bands
LF MF HF VHF UHF SHF EHF INFRARED VISIBLE ULTRAVIOLET X-RAY GAMMA-RAY COSMIC-RAY
X-ray
ALLOCATIONSFREQUENCY
BRO
AD
CA
STIN
GFI
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MO
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*
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FIXED
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BROA
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FIXED
BROA
DCAS
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FIXED
BROA
DCAS
TING
FIXED
BROA
DCAS
TING
FIXED
BROA
DCAS
TING
FIXED
FIXED
FIXED
FIXED
FIXED
FIXED
LAND
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FIXE
D
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NAUT
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STMO
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FIXED
LAND
MOB
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NAUT
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AERO
NAUT
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OBILE FIX
EDLA
ND M
OBILE
LAND
MOB
ILELA
ND M
OBILE
FIXED
LAND
MOB
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EDM
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ED
FIXED
FIXED
MOBIL
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ED
FIXED
FIXED
BRO
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ST
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Radio
-loc
ation
B-SA
TR-
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BFix
edMo
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Radio
locati
onFIX
EDMO
BILE*
*Am
ateur
RADI
OLOC
ATIO
N
SPAC
E RES
..(S-E
)
MOBIL
EFIX
ED MOBI
LE SA
TELL
ITE (S
-E)
MARI
TIME
MOB
ILE
Mobil
e FIXED
FIXED
BRO
ADCA
STMO
BILE
FIXED
MOBI
LE SA
TELL
ITE (E
-S)
FIXED
F
IXED
MARI
TIME
MOB
ILE
F
IXED
FIXED
MOBIL
E**
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MOBIL
E**
FIXED
SAT
(S-E
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RO.
RADI
ONAV
.
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SATE
LLITE
(E-S
)
Amate
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t (s-e)
Amate
urMO
BILE
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D SA
T(E-
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ED S
ATEL
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(S-E)(
E-S)
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FIXED
SAT
(E-S)
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LE
Radio
-loc
ation
RADIO
-LO
CATIO
NFI
XE
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AT.(E
-S)
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le**
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bile
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AT.(E
-S)L M
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E-S)
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RA
DION
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XED
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)AE
RONA
UTIC
AL R
ADIO
NAVIG
ATIO
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DIOL
OCAT
ION
Spac
e Re
s.(ac
t.)
RADI
OLOC
ATIO
NRa
dioloc
ation
Radio
loc.
RADIO
LOC.
Earth
Exp
l Sat
Spac
e Re
s.Ra
dioloc
ation
BCST
SAT
.
FIXE
DFIX
ED S
ATEL
LITE
(S-E)
FIXE
D SA
TELL
ITE
(S-E
)EA
RTH
EXPL
. SAT
.FX
SAT
(S-E
)SP
ACE
RES.
FIXE
D SA
TELL
ITE
(S-E
)FI
XED
SATE
LLIT
E (S
-E)
FIXE
D SA
TELL
ITE
(S-E
)MO
BILE
SAT.
(S-E)
FX S
AT (S
-E)
MOBI
LE S
ATEL
LITE
(S-E
)FX
SAT
(S-E
)ST
D FR
EQ. &
TIME
MOBIL
E SA
T (S-E
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RTH
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.MO
BILE
FIXE
DSP
ACE
RES. FI
XED
MOBI
LEMO
BILE
**FI
XED
EART
H EX
PL. S
AT.
FIXE
DMO
BILE*
*RA
D.AS
TSP
ACE
RES.
FIXE
DMO
BILE
INTER
-SATE
LLITE
FIXE
D
RADIO
AS
TRON
OMY
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E RE
S.(P
assiv
e)
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AMAT
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ATEL
LITE
Radio
-loc
ation
Amate
urRA
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LOCA
TION
Earth
Exp
l.Sa
tellit
e(A
ctive
)
FIXE
D
INTER
-SATE
LLITE
RADIO
NAVIG
ATIO
N
RADIO
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TION
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TELLI
TE (E-
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ER-SA
TELL
ITE
FIXE
DSA
TELL
ITE
(E-S
)RA
DIONA
VIGAT
ION
FIXE
DSA
TELL
ITE
(E-S
)FI
XED
MOBIL
E SA
TELL
ITE (E
-S)
FIXE
D SA
TELL
ITE
(E-S
)
MOBI
LEFI
XED
Earth
Ex
plorat
ionSa
tellite
(S
-S)
std fre
q &
time
e-e-sa
t (s-s
)MO
BILE
FIXE
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-e-sa
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BILE
SPAC
ERE
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CH (d
eep s
pace
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ATIO
NIN
TER-
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SPAC
E RE
S.
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DMO
BILE
SPAC
E RE
SEAR
CH(s
pace
-to-E
arth
)
SPAC
ERE
S.
FIXE
DSA
T. (
S-E)
MOBI
LEFI
XED
FIXE
D-SA
TELL
ITE
MOBIL
EFI
XED
FIXE
DSA
TELL
ITE
MOBI
LESA
T.FI
XED
SAT
MOBI
LESA
T.EA
RTH
EXPL
SAT
(E-S
)Ea
rthEx
pl.Sa
t (s -
e)SP
ACE
RES
. (E-S) FX
-SAT
(S-E
)
FIXED
MOBIL
EBR
OAD-
CAST
ING
BCST
SAT.
RADIO
ASTR
ONOM
YFI
XED
MOB
ILE*
*FI
XED
SATE
LLITE
(E-S
)
MOBI
LESA
TELL
ITE (
E-S)
FIXE
DSA
TELL
ITE (
E-S)
MOBI
LERA
DION
AV.
SATE
LLIT
EFI
XED
MOBI
LEMO
B. SA
T(E-S
)RA
DION
AV.S
AT.
MOBI
LESA
T (E
-S).
FIXE
DMO
BILE
FXSA
T(E-
S)
MOBI
LEFI
XED
INTE
R- S
ATEA
RTH
EXPL
-SAT
(Pa
ssive
)SP
ACE
RES.
INTE
R- S
ATSP
ACE
RES.
EART
H-ES
INTE
R- S
ATEA
RTH-
ESSP
ACE
RES.
MOB
ILE
FIXE
DEA
RTH
EXPL
ORAT
ION
SAT.
(Pas
sive)
SPAC
E R
ES.
MOB
ILE
FIXE
DIN
TER
- SAT
FIXE
DM
OBIL
E
INTER
-SA
TRA
DIO-
LOC.
MOB
ILE
FIXE
DEA
RTH
EXPL
ORAT
ION
SAT. (
Passi
ve)
MOBIL
EFI
XED
INTER
-SA
TELL
ITEFI
XED
MOBI
LE**
MOB
ILE*
*INT
ER-
SATE
LLITE
MOB
ILE
INTER
-SA
TELL
ITE
RADI
OLOC
.Am
ateur Am
ateu
r Sat
.Am
ateur
RADI
OLOC
.AM
ATEU
R SA
TAM
ATEU
RRA
DIOL
OC.
SPAC
ERE
SEAR
CH(Pa
ssive)
EART
HEX
PL SA
T.(Pa
ssive)
FIXE
DMO
BILE
INTER
-SA
TELL
ITESP
ACE
RESE
ARCH
(Passi
ve)
EART
HEX
PL SA
T.(Pa
ssive)
Amatu
erFI
XED
MO-
BILE
INTER
-SA
T.SP
ACE
RES.
E A R T
H EX
PL . SA
T
INTER
-SA
TELL
ITE
INTER
-SAT.
INTER
-SAT.
MOBIL
EFIX
ED
FX-S
AT (S
- E)
BCST
- SAT
.B-
SAT.
MOB*
*FX
-SAT
SPAC
E RE
SEAR
CH
SPAC
ERE
S..
This chart is a graphic single-point-in-time portrayal of the Table of Frequency Allocations used by theFCC and NTIA. As such, it does not completely reflect all aspects, i.e., footnotes and recent changesmade to the Table of Frequency Allocations. Therefore, for complete information, users should consult theTable to determine the current status of U.S. allocations.
U.S. DEPARTMENT O F C O MMERCE
NATIO
NA
L TELEC
OM
M
UN I C ATI O NS & INF O RM ATION
AD
MIN
ISTR
ATIO
N
MOBI
LE (A
ERON
AUTIC
AL TE
LEME
TERI
NG)
S)
5.68
5.73
5.90
5.95
6.2
6.52
5
6.68
56.
765
7.0
7.1
7.3
7.35
8.1
8.19
5
8.81
5
8.96
59.
040
9.4
9.5
9.9
9.99
510
.003
10.0
0510
.110
.15
11.1
7511
.275
11.4
11.6
11.6
5
12.0
512
.10
12.2
3
13.2
13.2
613
.36
13.4
113
.57
13.6
13.8
13.8
714
.014
.25
14.3
5
14.9
9015
.005
15.0
1015
.10
15.6
15.8
16.3
6
17.4
117
.48
17.5
5
17.9
17.9
718
.03
18.0
6818
.168
18.7
818
.919
.02
19.6
819
.80
19.9
9019
.995
20.0
0520
.010
21.0
21.4
521
.85
21.9
2422
.0
22.8
5523
.023
.223
.35
24.8
924
.99
25.0
0525
.01
25.0
725
.21
25.3
325
.55
25.6
726
.126
.175
26.4
826
.95
26.9
627
.23
27.4
127
.54
28.0
29.7
29.8
29.8
929
.91
30.0
UNITEDSTATES
THE RADIO SPECTRUM
NON-GOVERNMENT EXCLUSIVE
GOVERNMENT/ NON-GOVERNMENT SHAREDGOVERNMENT EXCLUSIVE
RADIO SERVICES COLOR LEGEND
ACTIVITY CODE
NOT ALLOCATED RADIONAVIGATION FIXED
MARITIME MOBILEFIXED
MARITIME MOBILE
FIXED
MARITIME MOBILE
Radiolocation RADIONAVIGATION
FIXED
MARITIMEMOBILE
Radiolocation
FIXED
MARITIMEMOBILE FIXED
MARITIMEMOBILE
AERONAUTICALRADIONAVIGATION
AERO
NAUT
ICAL
RADI
ONAV
IGAT
ION
Aeron
autic
alMo
bile
Mariti
meRa
diona
vigati
on(R
adio
Beac
ons)
MARI
TIME
RADI
ONAV
IGAT
ION
(RAD
IO BE
ACON
S)Ae
ronau
tical
Radio
navig
ation
(Rad
io Be
acon
s)
3 9 14 19.9
5
20.0
5
30 30 59 61 70 90 110
130
160
190
200
275
285
300
3 kHz 300 kHz
300 kHz 3 MHz
3 MHz 30 MHz
30 MHz 300 MHz
3 GHz
300 GHz
300 MHz
3 GHz
30 GHz
AeronauticalRadionavigation(Radio Beacons)
MARITIMERADIONAVIGATION(RADIO BEACONS)
Aeron
autic
alMo
bile
Mariti
meRa
diona
vigati
on(R
adio
Beac
ons)
AERO
NAUT
ICAL
RADI
ONAV
IGAT
ION
(RAD
IO BE
ACON
S)
AERONAUTICALRADIONAVIGATION(RADIO BEACONS)
AeronauticalMobile
Aeron
autic
al Mo
bile
RADI
ONAV
IGAT
ION
AER
ONAU
TICAL
RADI
ONAV
IGAT
ION
MARI
TIME
MOBI
LE AeronauticalRadionavigation
MOB
ILE (D
ISTR
ESS
AND
CALL
ING)
MARI
TIME
MOBI
LE
MARI
TIME
MOBI
LE(S
HIPS
ONL
Y)
MOBI
LE
AERO
NAUT
ICAL
RADI
ONAV
IGAT
ION
(RAD
IO B
EACO
NS)
AERO
NAUT
ICAL
RADI
ONAV
IGAT
ION
(RAD
IO B
EACO
NS)
BROADCASTING(AM RADIO)
MARI
TIME
MOBIL
E (TE
LEPH
ONY)
MARI
TIME
MOBIL
E (TE
LEPH
ONY)
MOB
ILE (D
ISTRE
SS AN
D CA
LLIN
G)
MARITIMEMOBILE
LAND MOBILE
MOBILE
FIXED STAN
DARD
FREQ
. AND
TIME
SIGN
AL (2
500k
Hz)
STAN
DARD
FREQ
. AND
TIME
SIGN
ALSp
ace R
esea
rch MARITIMEMOBILE
LAND MOBILE
MOBILE
FIXED
AERO
NAUT
ICAL
MOBIL
E (R)
STAN
DARD
FREQ
.
AERO
NAUT
ICAL
MOB
ILE (R
)
AERO
NAUT
ICAL
MOBIL
E (O
R)
AERO
NAUT
ICAL
MOBIL
E (R)
FIXED
MOBILE**
Radio-location
FIXED
MOBI
LE*
AMATEUR
FIXED
FIXED
FIXED
FIXED
FIXEDMARITIME
MOBILE
MOBI
LE*
MOBI
LE*
MOBI
LEST
ANDA
RD FR
EQ. A
ND TI
ME SI
GNAL
(500
0 KHZ
)
AERO
NAUT
ICAL
MOB
ILE (R
)
AERO
NAUT
ICAL
MOB
ILE (O
R)
STAN
DARD
FREQ
.Sp
ace R
esea
rch
MOBILE**
AERO
NAUT
ICAL
MOB
ILE (R
)
AERO
NAUT
ICAL
MOB
ILE (O
R) FIXE
DMO
BILE
*
BROA
DCAS
TING
MARI
TIME
MOBI
LE
AERO
NAUT
ICAL
MOB
ILE (R
)AE
RONA
UTIC
AL M
OBILE
(OR) FIX
EDMo
bile
AMAT
EUR
SATE
LLITE
AMAT
EUR
AMAT
EUR
FIXED
Mobile
MARIT
IME M
OBILE
MARITIMEMOBILE
AERO
NAUT
ICAL
MOB
ILE (R
)AE
RONA
UTIC
AL M
OBILE
(OR)
FIXE
D
BROA
DCAS
TING
FIXED
STAN
DARD
FREQ
. AND
TIME
SIGN
AL (1
0,000
kHz)
STAN
DARD
FREQ
.Sp
ace R
esea
rchAE
RONA
UTIC
AL M
OBILE
(R)
AMAT
EUR
FIXED
Mobile* AERO
NAUT
ICAL
MOB
ILE (R
)AE
RONA
UTIC
AL M
OBILE
(OR)
FIXED
FIXED
BROA
DCAS
TING
MARI
TIME
MOBI
LE
AERO
NAUT
ICAL M
OBILE
(R)
AERO
NAUT
ICAL M
OBILE
(OR)
RADIO
ASTR
ONOM
YMo
bile*
AMAT
EUR
BROA
DCAS
TING
AMAT
EUR
AMAT
EUR S
ATEL
LITE
Mobil
e*FIX
ED
BROA
DCAS
TING
STAN
DARD
FREQ
. AND
TIME
SIGN
AL (1
5,000
kHz)
STAN
DARD
FREQ
.Sp
ace R
esea
rch
FIXED
AERO
NAUT
ICAL
MOB
ILE (O
R)
MARI
TIME
MOBI
LE
AERO
NAUT
ICAL
MOB
ILE (O
R)AE
RONA
UTIC
AL M
OBILE
(R)
FIXED
FIXED
BROA
DCAS
TING
STAN
DARD
FREQ
.Sp
ace R
esea
rch
FIXED
MARI
TIME
MOBI
LE
Mobil
eFIX
ED
AMAT
EUR
AMAT
EUR
SATE
LLITE
BROA
DCAS
TING
FIXED
AERO
NAUT
ICAL
MOB
ILE (R
)
MARI
TIME
MOBI
LE
FIXED
FIXED
FIXED
Mob
ile*
MOB
ILE**
FIXED
STAN
DARD
FREQ
. AND
TIME
SIGN
AL (2
5,000
kHz)
STAN
DARD
FREQ
.Sp
ace R
esea
rch LA
ND M
OBILE
MARI
TIME
MOBI
LE LA
ND M
OBILE
MOB
ILE**
RAD
IO A
STRO
NOMY
BROA
DCAS
TING
MARI
TIME
MOBI
LE LA
ND M
OBILE
FIXED
MOB
ILE**
FIXED
MOB
ILE**
MOB
ILE
FIXED
FIXED
FIXED
FIXED
FIXED
LAND
MOB
ILE
MOB
ILE**
AMAT
EUR
AMAT
EUR
SATE
LLITE
MOB
ILE
LAND
MOB
ILE
MOBI
LE
MOBI
LE
FIXED
FIXED
MOBI
LE
MOBI
LE
FIXED
FIXED
LAND
MOBI
LE
LAND
MOBI
LE
LAND
MOBI
LE
LAND
MOB
ILERa
dio A
stron
omy
RADIO
AST
RONO
MYLA
ND M
OBILE
FIXED
FIXED
MOBI
LEMOBIL
E
MOBILE
LAND
MOB
ILE
FIXED
LAND
MOBI
LE
FIXED
FIXED
MOBI
LE
MOBIL
E
LANDMOBILE AMATEUR
BROADCASTING(TV CHANNELS 2-4)
FIXED
MOBI
LE
FIXED
MOBI
LE
FIXED
MOBI
LEFIX
EDMO
BILE
AERO
NAUT
ICAL
RAD
IONA
VIGA
TION
BROADCASTING(TV CHANNELS 5-6)
BROADCASTING(FM RADIO)
AERONAUTICALRADIONAVIGATION
AERO
NAUT
ICAL
MOBI
LE (R
)AE
RONA
UTIC
AL M
OBILE
AERO
NAUT
ICAL
MOB
ILE
AERO
NAUT
ICAL
MOBI
LE (R
)
AERO
NAUT
ICAL
MOBI
LE (R
)AE
RONA
UTIC
AL M
OBILE
(R)
MOBI
LEFI
XED
AMAT
EUR
BROADCASTING(TV CHANNELS 7-13)
MOBILE
FIXED
MOBILE
FIXED
MOBILE SATELLITE
FIXED
MOBILESATELLITE
MOBILE
FIXED
MOBILESATELLITE
MOBILE
FIXED
MOBI
LE
AERO
NAUT
ICAL
RAD
IONA
VIGA
TION
STD.
FREQ
. & TI
ME SI
GNAL
SAT.
(400.1
MHz
)ME
T. SAT
.(S-
E)SP
ACE R
ES.
(S-E)
Earth
Exp
l.Sa
tellite
(E-S
)
MOBI
LE S
ATEL
LITE
(E-S
)FIX
EDMO
BILE
RADI
OAS
TRON
OMY
RADI
OLOC
ATIO
NAm
ateur
LAND
MOB
ILE
MeteorologicalSatellite (S-E)
LAND
MOB
ILEBR
OADC
ASTIN
G(TV
CHAN
NELS
14 - 2
0)
BROADCASTING(TV CHANNELS 21-36)
TV BROADCASTINGRADI
O AS
TRON
OMY
RADI
OLOC
ATIO
N
FIXED
Amate
ur
AERONAUTICALRADIONAVIGATION
MOBI
LE**
FIXED
AERO
NAUT
ICAL
RADIO
NAVIG
ATION
Radio
locati
on
Radio
locati
onMA
RITIM
ERA
DION
AVIG
ATIO
N
MARI
TIME
RADI
ONAV
IGAT
ION
Radio
locati
on
Radiolocation
Radiolocation
RADIO-LOCATION RADIO-
LOCATION
Amateur
AERO
NAUT
ICAL
RADIO
NAVIG
ATIO
N(G
round
)RA
DIO-
LOCA
TION
Radio
-loc
ation
AERO
. RAD
IO-NA
V.(Gro
und)
FIXED
SAT.
(S-E)
RADIO
-LO
CATIO
NRa
dio-
locati
on
FIXED
FIXEDSATELLITE
(S-E)
FIXED
AERO
NAUT
ICAL
RAD
IONA
VIGA
TION MO
BILE
FIXED
MOBIL
E
RADI
O AS
TRON
OMY
Spac
e Res
earch
(Pas
sive)
AERO
NAUT
ICAL
RAD
IONA
VIGA
TION
RADI
O-LO
CATIO
NRa
dio-
locati
onRA
DION
AVIG
ATIO
NRa
dioloc
ation
RADI
OLOC
ATIO
NRa
dioloc
ation
Radio
locati
on
Radio
locati
onRA
DIOL
OCAT
ION
RADI
O-LO
CATIO
N
MARI
TIME
RADI
ONAV
IGAT
ION
MARI
TIME
RADI
ONAV
IGAT
ION
METE
OROL
OGIC
ALAID
S
Amate
urAm
ateur
FIXED
FIXED
SATE
LLITE
(E-S
)MO
BILE
FIXED
SATE
LLITE
(E-S
)
FIXED
SATE
LLITE
(E-S
)MO
BILE
FIXED FIX
ED
FIXED
FIXED
MOBIL
E
FIXED
SPAC
E RE
SEAR
CH (E
-S)
FIXED
Fixed
MOBIL
ESA
TELL
ITE (S
-E)FIX
ED SA
TELLI
TE (S
-E)
FIXED
SATE
LLITE
(S-E)
FIXED
SATE
LLITE
(S-E)
FIXED
SATE
LLITE
(S-E)
FIXED
SATE
LLITE
(E-S)
FIXED
SATE
LLITE
(E-S)
FIXED
SATE
LLITE
(E-S)
FIXED
SATE
LLITE
(E-S)
FIXED
FIXED
FIXED
FIXED
FIXED
FIXED
FIXED
MET.
SATE
LLITE
(S-E)
Mobile
Satell
ite (S-
E)Mo
bileSa
tellite
(S-E)
Mobile
Satell
ite (E-
S)(no
airbo
rne)
Mobile
Satell
ite(E-
S)(no
airborn
e)
Mobile
Sate
llite (S
-E)
Mobile
Satell
ite (E-
S)
MOBIL
ESA
TELL
ITE (E
-S)EA
RTH E
XPL.
SATE
LLITE
(S-E)
EART
H EXP
L.SA
T. (S-E
)
EART
H EXP
L.SA
TELLI
TE (S
-E)
MET.
SATE
LLITE
(E-S)
FIXED
FIXED
SPAC
E RES
EARC
H (S-
E)(de
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325
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405
415
435
495
505
510
525
535
1605
1615
1705
1800
1900
2000
2065
2107
2170
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2501
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RADIO-LOCATION
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30.0
30.5
6
32.0
33.0
34.0
35.0
36.0
37.0
37.5
38.0
38.2
5
39.0
40.0
42.0
43.6
9
46.6
47.0
49.6
50.0
54.0
72.0
73.0
74.6
74.8
75.2
75.4
76.0
88.0
108.
0
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123.
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128.
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132.
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7.0
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7.18
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173.
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216.
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220.
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2.0
225.
0
235.
0
300
ISM – 6.78 ± .015 MHz ISM – 13.560 ± .007 MHz ISM – 27.12 ± .163 MHz
ISM – 40.68 ± .02 MHz
ISM – 24.125 ± 0.125 GHz 30 GHz
ISM – 245.0 ± 1GHzISM – 122.5 ± .500 GHzISM – 61.25 ± .250 GHz
300.
0
322.
0
328.
6
335.
4
399.
9
400.
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0.15
401.
0
402.
0
403.
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6.0
406.
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420.
0
450.
045
4.0
455.
045
6.0
460.
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2.537
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2.737
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7.537
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7.737
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0.0
512.
0
608.
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4.0
698
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776
794
806
821
824
849
851
866
869
894
896
9019
0190
2
928
929
930
931
932
935
940
941
944
960
1215
1240
1300
1350
1390
1392
1395
2000
2020
2025
2110
2155
2160
2180
2200
2290
2300
2305
2310
2320
2345
2360
2385
2390
2400
2417
2450
2483
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5526
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00
2900
3000
1400
1427
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1430
1432
1435
1525
1530
1535
1544
1545
1549
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10.6
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26.5
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1700
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1755
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3.65
3.7
4.2
4.4
4.5
4.8
4.94
4.99
5.0
5.15
5.25
5.35
5.46
5.47
5.6
5.65
5.83
5.85
5.92
5
6.42
5
6.52
5
6.70
6.87
5
7.02
57.
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7.12
5
7.19
7.23
57.
25
7.30
7.45
7.55
7.75
7.90
8.02
5
8.17
5
8.21
5
8.4
8.45
8.5
9.0
9.2
9.3
9.5
10.0
10.4
510
.510
.55
10.6
10.6
8
10.7
11.7
12.2
12.7
12.7
5
13.2
513
.4
13.7
514
.0
14.2
14.4
14.4
714
.514
.714
515
.136
5
15.3
5
15.4
15.4
3
15.6
315
.716
.617
.1
17.2
17.3
17.7
17.8
18.3
18.6
18.8
19.3
19.7
20.1
20.2
21.2
21.4
22.0
22.2
122
.5
22.5
5
23.5
5
23.6
24.0
24.0
5
24.2
524
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24.6
5
24.7
5
25.0
5
25.2
525
.527
.0
27.5
29.5
29.9
30.0
ISM – 2450.0 ± 50 MHz
30.0
31.0
31.3
31.8
32.0
32.3
33.0
33.4
36.0
37.0
37.6
38.0
38.6
39.5
40.0
40.5
41.0
42.5
43.5
45.5
46.9
47.0
47.2
48.2
50.2
50.4
51.4
52.6
54.2
555
.78
56.9
57.0
58.2
59.0
59.3
64.0
65.0
66.0
71.0
74.0
75.5
76.0
77.0
77.5
78.0
81.0
84.0
86.0
92.0
95.0
100.
0
102.
0
105.
0
116.
0
119.
98
120.
02
126.
0
134.
0
142.
014
4.0
149.
0
150.
0
151.
0
164.
0
168.
0
170.
0
174.
5
176.
5
182.
0
185.
0
190.
0
200.
0
202.
0
217.
0
231.
0
235.
0
238.
0
241.
0
248.
0
250.
0
252.
0
265.
0
275.
0
300.
0
ISM – 5.8 ± .075 GHz
ISM – 915.0 ± 13 MHz
INTER
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This chart is a graphic single-point-in-time portrayal of the Table of Frequency Allocations used by theFCC and NTIA. As such, it does not completely reflect all aspects, i.e., footnotes and recent changesmade to the Table of Frequency Allocations. Therefore, for complete information, users should consult theTable to determine the current status of U.S. allocations.
300 MHz 3 GHz
30 GHz 300 GHz
cellular WiFi
note: log scale so even smaller over here
UHF (ultra high frequency) spectrum
Huge amount of spectrum possibly available in mmWave bands
Technology advances make mmWave possible for low cost consumer devices
mmWave research is as old as wireless itself, e.g. Bose 1895 and Lebedew 1895
WHAT STARTS HERE CHANGES THE WORLD(c) 2014 Robert W Heath Jr.
sub-6GHz aperture
mmWave aperture
TX
RX
isotropic radiator
Beamforming for antenna gain
The importance of antennas at mmWave
3
… to 300 GHz
1.3 GHz 2.1 GHz
28 GHz 37 / 42 GHz
10 GHz
E-Band
7 GHz(unlic)
60GHz
millimeter wave band
Shu Sun, T. Rappapport, R. W. Heath, Jr., A. Nix, and S. Rangan, `` MIMO for Millimeter Wave Wireless Communications: Beamforming, Spatial Multiplexing, or Both?,'' IEEE Communications Magazine, December 2014.
spatial multiplexing & beamforming just beamforming
Spatial multiplexing for spectral efficiency
multiple data streams
several GHz of spectrum is promising but found in many
separate bands
WHAT STARTS HERE CHANGES THE WORLD(c) 2014 Robert W Heath Jr.
Differentiating features of mmWave cellular
WHAT STARTS HERE CHANGES THE WORLD(c) 2014 Robert W Heath Jr.
Antenna scale
Large antenna arrays result inLarge-dimensional precoding/combining matrices
High channel estimation, training, and feedback overheads unless smart algorithms exploited
5Need to design low-complexity precoding and channel estimation algorithms
Large antenna arrays at Tx and Rx
Mobile StationsBase station
64 to 256elements
4 to 32 elements
WHAT STARTS HERE CHANGES THE WORLD(c) 2014 Robert W Heath Jr.
Different communication channel bandwidth
Large channel bandwidth (high noise power, low SNR before beamforming)Implementing random access, channel training and estimation functions is challenging
Broadband channels coupled with delay spreadEqualization would likely be required at the receiver
Hardware constraints may make it difficult to perform equalization entirely in baseband
6
UHF noise bandwidth
mmWave noise bandwidth
How to implement equalization?Receiver
Need new algorithms and architectures for broadband communication
Analog processing
Baseband processing
WHAT STARTS HERE CHANGES THE WORLD(c) 2014 Robert W Heath Jr.
Hardware constraints
Cost, power, and complexity limit the # of RF chains (high-resolution ADCs)Signal processing can not be done entirely in the baseband
Analog beamforming usually uses a network of phase shifters Additional constraints: Constant gain and quantized angles
7
Baseband
Precoding
Baseband Processing
ADC
ADC
ADC
RF Chain
RF Chain
RF Chain
Analog processing
Analog processing
Analog processing
Joint processing
Phase shifters
MIMO transceiver DSP algorithms need to incorporate new constraints
200mW200mW40mW
20mW20mW LNA
WHAT STARTS HERE CHANGES THE WORLD(c) 2014 Robert W Heath Jr.
Channel characteristics
8Some channel characteristics can be leveraged in the signal processing
sub-6 GHzWifi or Cellular
Mi
mmWave Wifi
mmWave 5G (???)
bandwidth 1.4 MHz to 160 MHz 2.16 GHz 100 MHz to 2 GHz# antennas @ BS or AP 1 to 8 16 to 32 64 to 256
# antennas at MS 1 or 2 16 to 32 4 to 32delay spread 100 ns to 10 us 5 to 47 ns 12 to 40 nsangle spread 1° to 60° 60° to 100° up to 50°# clusters 4 to 9 < 4 < 4
orientation sensitivity low medium highsmall-scale fading Rayleigh Nakagami non-fading or Nakagami
large-scale fading distant dependent +shadowing
distant dependent +shadowing
distant dependent +blockage
path loss exponent 2-4 2 LOS, 2.5 to 5 NLOS 2 LOS, 3.5 to 4.5 NLOSpenetration loss some varies possibly highchannel sparsity less more more
spatial correlation less more more
WHAT STARTS HERE CHANGES THE WORLD(c) 2014 Robert W Heath Jr.
Sensitivity to blockages
9
Base stationHandset
Blocked by users’ bodyX
User
self-body blocking
Need models for these forms of blockage
X
blockage due to people
hand blocking
blockage due to buildings
line-of-sight non-line-of-sight
WHAT STARTS HERE CHANGES THE WORLD(c) 2014 Robert W Heath Jr.
MmWave cellular system analysis
T. Bai and R. W. Heath Jr., “Coverage and rate analysis for millimeter wave cellular networks", IEEE Trans. Wireless Commun, 2015
Also see: T. Bai, A. Alkhateeb and R. W. Heath Jr., “Coverage and capacity in millimeter wave cellular networks", IEEE Commun. Mag., vol. 52, no.9, pp. 70-77, Sep. 2014.
WHAT STARTS HERE CHANGES THE WORLD(c) 2014 Robert W Heath Jr.
MmWave performance analysis
11
LOS & non-LOS linksDirectional Beamforming (BF)
Need to incorporate directional beamformingRX and TX communicate via main lobes to achieve array again
Steering directions at interfering BSs are random
Need to distinguish LOS and NLOS pathsIncorporate different characteristics in LOS & NLOS channels
Better characterize building blockages
Include beamforming + blockage in mmWave cellular analysis
WHAT STARTS HERE CHANGES THE WORLD(c) 2014 Robert W Heath Jr.
5
[2], we also remove the constraint that the LOS path loss exponent is 2, and extend the results
in [2] to general path loss exponents, in addition to providing derivations for all results, and new
simulation results.
This paper is organized as follows. We introduce the system model in Section II. We derive
expressions for the SINR and rate coverage in a general mmWave network in Section III. A
systematic approach is also proposed to approximate general LOS probability functions as a step
function to further simplify analysis. In Section IV, we apply the simplified system model to
analyze performance and examine asymptotic trends in dense mmWave networks, where outdoor
users observe more than one LOS base stations with high probability. Finally, conclusions and
suggestions for future work are provided in Section V.
II. SYSTEM MODEL
(a) System model for mmWave cellular networks
Mmθ
(b) Sectored model to approximate beamforming patterns.
Fig. 1: In (a), we illustrate the proposed system model for mmWave cellular networks. Blockages are modeled as a random
process of rectangles, while base stations are assumed to be distributed as a Poisson point process on the plane. An outdoor
typical user is fixed at the origin, and the base stations can be categorized into three groups: indoor base stations, outdoor base
stations that is LOS to the typical user, and outdoor base station NLOS to the user. Directional beamforming is performed at
both base stations and mobile stations to exploit directivity gains. In (b), we illustrate the sectored antenna model G
M,m,✓
,
which is used to approximate the beamforming patterns.
In this section, we introduce our system model for evaluating the performance of a mmWave
network. We focus on the downlink coverage and rate performance experienced by an outdoor
user, as illustrated in Fig. 1(a). We make the following assumptions when formulating the system
model.
Accounting for beamforming
Each base station is marked with a directional antennaAntenna directions of interferers are uniformly distributed
Assume perfect beam alignment for desired signal link
Use “sectored” pattern in analysis for simplicity Antenna pattern fully characterized by , M and m
12
1
Summary of Cellular Millimeter Wave Channels
I. MEASUREMENT RESULTS
−3 −2 −1 0 1 2 30
1
2
3
4
5
6
7
8
9
10
Angel in Rad
Ante
nna
Gai
n
Exact antenna pattern"Sector" approximation
Fig. 1.
Sectored antenna pattern approximation
Half-Power BW✓
Main lobe beamwidth
Main lobe array gain
Back lobe gain
✓
WHAT STARTS HERE CHANGES THE WORLD(c) 2014 Robert W Heath Jr.
Use the concept of the LOS probability to separate LOS/ NLOS linksA link of length is LOS with probability
LOS probability is a non-increasing function of the link length
Find the LOS probability based on the certain building modelsUsing stochastic models from random shape theory*
Using site-specific maps from geographical information system (GIS) database
Incorporating building blockages
13
Snapshots taken from google maps
*T. Bai, R. Vaze, and R. W. Heath Jr., “Analysis of blockage effects on urban cellular networks", IEEE Trans. Wireless Commun., vol. 13, no. 9, pp. 5070-5083, Sep. 2014.
Buildings in some cities, e.g. parts of Boston, form regular grids Other cities have less regular planning
r
p(r)
p(r)rp(r)
WHAT STARTS HERE CHANGES THE WORLD(c) 2014 Robert W Heath Jr.
15
Fig. 8. .
General mmWave network model
Use stochastic geometry* to model BS locations as marked PPPModel the steering directions of BSs as independent marks of the point process
User connects to the BS with smallest path loss
Use distance-dependent LOS probability function Different path loss laws (exponents) for LOS and NLOS paths
Assume independent LOS probabilities among links14
Interfering BSs
Serving BS
Typical User
Buildings
p(r)
* J. G. Andrews, F. Baccelli, and R. K. Ganti, "A Tractable Approach to Coverage and Rate in Cellular Networks", IEEE TCOM, 2011. T. Bai, A. Alkhateeb and R. W. Heath Jr., “Coverage and capacity in millimeter wave cellular networks", IEEE Commun. Mag., vol. 52, no.9, pp. 70-77, Sep. 2014.
NLOS BS
LOS BS
Typical user
LOS pathNLOS path
WHAT STARTS HERE CHANGES THE WORLD(c) 2014 Robert W Heath Jr.
11
−10 −5 0 5 10 15 20 250.7
0.75
0.8
0.85
0.9
0.95
1
SINR threshold in dB
SINR
Cov
erag
e Pr
obab
ility
ISD=200 m, p(t)=e−β t, 1/β=200 m
LOS ball approximation
Fig. 11. Comparison of mmWave and microwave massive MIMO asymptotic results. The simulations show that mmWave
massive MIMO asumptotically achieves better SINR than microwave, as RX beamforming thins the interference, and blockages
also improve SINR.
15
Fig. 8. .
Simplified model for dense networks
Approximate LOS region by an equivalent LOS ballTheorem 1 can be inefficient to compute due to the general form of
Simplify a general as a step function by matching its first moment
Enable simplified expressions for further performance analysis
15
NLOS BS
p(r)
p(r)
LOS BS
Typical user
Equivalent LOS ball
Less than 5% error in coverage
LOS ball model captures most nearby LOS interferersthat dominant the performance in dense networks
WHAT STARTS HERE CHANGES THE WORLD(c) 2014 Robert W Heath Jr.
Results on SINR coverage
WHAT STARTS HERE CHANGES THE WORLD(c) 2014 Robert W Heath Jr.
SINR coverage of mmWave cellular
SINR coverage expressions for general mmWave networksApply to general building distribution, i.e., LOS probability function
Assume Nakagami fading with different parameters for LOS and NLOS
Can be simplified in some special cases of , e.g. step function in the dense network model
17
Theorem 1 [mmWave SINR Distribution]The SINR coverage probability (CCDF of SINR) in mmWave networks is
where the conditional coverage probability by LOS BSs is
and the conditional coverage probability by NLOS BSs is
12
Now, based on Lemma 2 and Lemma 3, we present the main theorem on the SINR coverage
probability as follows
Theorem 3: The SINR coverage probability Pc
(T ) can be computed as
Pc(T ) = ALPc,L(T ) + ANPc,N(T ), (8)
where for s 2 {L,N}, Pc,s(T ) is the conditional coverage probability given that the user is
associated with a base station in �s. Further, Pc,s(T ) can be evaluated as
Pc,L(T ) ⇡
NLX
n=1
(�1)
n+1
✓NL
n
◆Z 1
0
e
�n⌘Lx
↵LT�
2
CLMrMt�Q
n
(T,x)�V
n
(T,x)ˆfL(x)dx, (9)
and
Pc,N(T ) ⇡
NNX
n=1
(�1)
n+1
✓NN
n
◆Z 1
0
e
�n⌘Nx
↵NT�
2
CNMrMt�W
n
(T,x)�Z
n
(T,x)ˆfN(x)dx. (10)
where
Qn
(T, x) = 2⇡�
4X
k=1
bk
Z 1
x
f
✓NL,
n⌘LakTx↵L
NLt↵L
◆p(t)tdt, (11)
Vn
(T, x) = 2⇡�
4X
k=1
bk
Z 1
L(x)
f
✓NN,
nCN⌘LakTx↵L
CLNNt↵N
◆(1� p(t))tdt, (12)
Wn
(T, x) = 2⇡�
4X
k=1
bk
Z 1
N(x)
f
✓NL,
nCL⌘NakTx↵N
CNNLt↵L
◆p(t)tdt, (13)
Zn
(T, x) = 2⇡�
4X
k=1
bk
Z 1
x
f
✓NN,
n⌘NakTx↵N
NNt↵N
◆(1� p(t))tdt, (14)
and f(N, x) = 1 � 1/(1 + x)N . For s 2 {L,N}, ⌘s
= Ns
(Ns
!)
� 1N
s , Ns
are the parameters of
the Nakagami small-scale fading; for 1 k 4, ak
=
a
k
MtMr, a
k
and bk
are constants defined in
Table I.
Proof: See Appendix D.
Though as an approximation of the SINR coverage probability, we will later show that the
expressions in Theorem 3 are comparable to the simulations in Section III-E. More importantly,
the expressions in Theorem 3 compute much more efficiently than prior results in [1], which
required inverting Fourier transform numerically. Last, the LOS probability function p(t) may
12
Now, based on Lemma 2 and Lemma 3, we present the main theorem on the SINR coverage
probability as follows
Theorem 3: The SINR coverage probability Pc
(T ) can be computed as
Pc(T ) = ALPc,L(T ) + ANPc,N(T ), (8)
where for s 2 {L,N}, Pc,s(T ) is the conditional coverage probability given that the user is
associated with a base station in �s. Further, Pc,s(T ) can be evaluated as
Pc,L(T ) ⇡
NLX
n=1
(�1)
n+1
✓NL
n
◆Z 1
0
e
�n⌘Lx
↵LT�
2
CLMrMt�Q
n
(T,x)�V
n
(T,x)ˆfL(x)dx, (9)
and
Pc,N(T ) ⇡
NNX
n=1
(�1)
n+1
✓NN
n
◆Z 1
0
e
�n⌘Nx
↵NT�
2
CNMrMt�W
n
(T,x)�Z
n
(T,x)ˆfN(x)dx. (10)
where
Qn
(T, x) = 2⇡�4X
k=1
bk
Z 1
x
f
✓NL,
n⌘LakTx↵L
NLt↵L
◆p(t)tdt, (11)
Vn
(T, x) = 2⇡�4X
k=1
bk
Z 1
L(x)
f
✓NN,
nCN⌘LakTx↵L
CLNNt↵N
◆(1� p(t))tdt, (12)
Wn
(T, x) = 2⇡�4X
k=1
bk
Z 1
N(x)
f
✓NL,
nCL⌘NakTx↵N
CNNLt↵L
◆p(t)tdt, (13)
Zn
(T, x) = 2⇡�4X
k=1
bk
Z 1
x
f
✓NN,
n⌘NakTx↵N
NNt↵N
◆(1� p(t))tdt, (14)
and f(N, x) = 1 � 1/(1 + x)N . For s 2 {L,N}, ⌘s
= Ns
(Ns
!)
� 1N
s , Ns
are the parameters of
the Nakagami small-scale fading; for 1 k 4, ak
=
a
k
MtMr, a
k
and bk
are constants defined in
Table I.
Proof: See Appendix D.
Though as an approximation of the SINR coverage probability, we will later show that the
expressions in Theorem 3 are comparable to the simulations in Section III-E. More importantly,
the expressions in Theorem 3 compute much more efficiently than prior results in [1], which
required inverting Fourier transform numerically. Last, the LOS probability function p(t) may
p(r)
P(SINR > T ) = ALPc,L(T ) +ANPc,N(T ),
NLOS interf. LOS interf.Noise
p(r)
T. Bai and R. W. Heath Jr., “Coverage and rate analysis for millimeter wave cellular networks”, IEEE Trans. Wireless Commun, 2015
WHAT STARTS HERE CHANGES THE WORLD(c) 2014 Robert W Heath Jr.
Coverage in dense mmWave networks
In dense network, SINR largely depends on the relative BS density is defined as the base station density normalized by the LOS region size
can be considered as the average number of BSs that are LOS to a user
Asymptotic analysis when networks become ultra densePerformance of dense networks limited by LOS interferers, which are typically strong
When LOS exponent no larger than 2, asymptotic SINR converges to 0 in probability
18
⇢
21
Theorem 5: The SINR coverage probability in a dense network can be approximated as
Pc(T ) ⇡ ⇢e
�⇢
NX
`=1
(�1)
`+1
✓N
`
◆Z 1
0exp
✓� 2
↵Lb
k
(`⌘T a
k
)
2↵L
�
✓� 2
↵L; `⌘T a
k
, `⌘T a
k
s
↵L2
◆◆dt, (17)
where �(s; a, b) =Rb
a
xs�1e
�x
dx is the incomplete gamma function, ak
= ak
/(MtMr), ak and
bk
are defined in Table I, ⌘ = N(N !)
1N , and N is the number of terms used in the approximation.
Proof: See Appendix D.
When ↵L = 2, the expression in Theorem 5 can be further simplified as follows.
Corollary 5.1: When ↵L = 2, the SINR coverage probability approximately equals
Pc(T ) ⇡ ⇢e�⇢
NX
`=1
(�1)
`+1
✓N
`
◆Z 1
0
4Y
k=1
e
⇢b
k
(
e�`⌘T a
k
t�te�`⌘T a
k
)
✓1� e
�`µ⌘T a
k
t
1� e
�`µ⌘T a
k
◆`⌘Tb
k
a
k
t
dt, (18)
where µ = e
0.577.
The results in Theorem 5 generally provide a close approximation of the SINR distribution
when enough terms are used, e.g. when N � 5, as will be shown in Section IV-D. More
importantly, we note that the expressions in Theorem 6 are very efficient to compute, as most
numerical tools support fast evaluation of the gamma function in (17), and (18) only requires a
simple integral over a finite interval. Besides, given the path loss exponent ↵L and the antenna
geometry ak
, bk
, Theorem 5 shows that the approximated SINR is only a function of the relative
density ⇢, which indicates the SIR distribution in a dense network is mostly determined on the
average number of LOS base station to a user.
C. Asymptotic Analysis in Ultra-Dense Networks
To obtain further insights into coverage in dense networks, we provide results on the asymptotic
SIR distribution when the relative density ⇢ becomes large. We use this distribution to answer
the following questions: (i) What is the asymptotic SIR distribution when the network becomes
extremely dense? (ii) Does increasing base station density always improve SIR in a mmWave
network?
First, we present the main asymptotic results as follows.
Theorem 6: In a dense network, when the LOS path loss exponent ↵L 2, the SIR converges
to zero in probability, as ⇢ ! 1. When ↵L > 2, the SIR distribution converges to a nonzero
equivalence SIR0, as ⇢ ! 1. The distribution of the asymptotic equivalent SIR0 is given in
Proposition 10 of [30], and for T > 1, it follows that P(SIR0 > T ) = ↵LT�2/↵L
2⇡ sin(2⇡/↵L).
Theorem 2 [Simplified SINR distribution in dense network]
⇢⇢
T. Bai and R. W. Heath Jr., “Coverage and rate analysis for millimeter wave cellular networks”, IEEE Trans. Wireless Commun, 2015 T. Bai and R. W. Heath Jr., “Coverage in dense millimeter wave cellular networks”, in Proc. of IEEE Asilomar, Pacific Grove, CA, Nov. 2013.
WHAT STARTS HERE CHANGES THE WORLD(c) 2014 Robert W Heath Jr.
16
5 10 15 20 25 30 35 400.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
SINR threshold in dB
SIN
R C
over
age
Prob
abili
ty
(M,m,θ)=(10 dB, −10 dB, 30°)(M,m,θ)=(20 dB, −10 dB, 30°)(M,m,θ)=(10 dB, −10dB, 45°)
Fig. 3: SINR coverage probability with different antenna
geometry. The average cell radius is rc = 100 meters. The
receiver beam pattern is fixed as G10dB,�10dB,90� .
50 100 150 200 250 3000
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
Avg. cell radius in meters
Asso
ciat
ion
Prob
abili
ty
LOS Association Prob.NLOS Association Prob.
Fig. 4: LOS association probability with density base
station densities.
E. Validation and Discussions
In this section, we provide numerical results to validate our analytical results and further
discuss their implications on system design. We assume the mmWave network is operated at 28
GHz, and the bandwidth assigned to each user is W = 100 MHz. The LOS and NLOS path
loss exponent are ↵L = 2 and ↵N = 4. The parameters of the Nakagami fading are NL = 3 and
NN = 2. We assume the LOS probability function is p(x) = e
��x, where 1/� = 141.4 meters.
For the ease of illustration, we denote the average cell radius as rc =p
1/⇡�. First, we simulate
the SINR coverage probability with different transmit antenna parameters. As shown in Fig. 3,
when the side lobe gain mt is fixed, better SINR performance is achieved by increasing main
lobe gain Mt and by decreasing the main lobe beamwidth ✓t, as indicated by the ordering results
in III-A.
Next, we compare network performance with different base station densities in Fig. 4. The
results show that the probability that a user is associated with a LOS base station increases as
the base station density grows, which also indicates the network performance will be mostly
determined by the distribution of LOS base stations in a sufficiently dense network, e.g. when
the average cell size is smaller than 100 meters in the simulation.
We also compare the SINR coverage probability with different base station densities in Fig.
5. The numerical results in Fig. 5 (a) show that our analytical results in Theorem 3 match
Coverage gain from large arrays
SINR coverage benefits from directional beamforming w/ large arraysLarger directivity improve SINR coverage by boosting signal power
Small beamwidth reduces the chance of strong interference
19
Gain from smaller beamwidth
Assume no RX beamformingSignal bandwidth: 500 MHzAvg. ISD: 200 mAvg. LOS range: =141 mCarrier frequency: 28GHzTx antenna input power: 30dBm
1/�
5
[2], we also remove the constraint that the LOS path loss exponent is 2, and extend the results
in [2] to general path loss exponents, in addition to providing derivations for all results, and new
simulation results.
This paper is organized as follows. We introduce the system model in Section II. We derive
expressions for the SINR and rate coverage in a general mmWave network in Section III. A
systematic approach is also proposed to approximate general LOS probability functions as a step
function to further simplify analysis. In Section IV, we apply the simplified system model to
analyze performance and examine asymptotic trends in dense mmWave networks, where outdoor
users observe more than one LOS base stations with high probability. Finally, conclusions and
suggestions for future work are provided in Section V.
II. SYSTEM MODEL
(a) System model for mmWave cellular networks
Mmθ
(b) Sectored model to approximate beamforming patterns.
Fig. 1: In (a), we illustrate the proposed system model for mmWave cellular networks. Blockages are modeled as a random
process of rectangles, while base stations are assumed to be distributed as a Poisson point process on the plane. An outdoor
typical user is fixed at the origin, and the base stations can be categorized into three groups: indoor base stations, outdoor base
stations that is LOS to the typical user, and outdoor base station NLOS to the user. Directional beamforming is performed at
both base stations and mobile stations to exploit directivity gains. In (b), we illustrate the sectored antenna model G
M,m,✓
,
which is used to approximate the beamforming patterns.
In this section, we introduce our system model for evaluating the performance of a mmWave
network. We focus on the downlink coverage and rate performance experienced by an outdoor
user, as illustrated in Fig. 1(a). We make the following assumptions when formulating the system
model.
Gain from large directivity gain
WHAT STARTS HERE CHANGES THE WORLD(c) 2014 Robert W Heath Jr.
SIR or SINR in dB-10 -5 0 5 10 15
CC
DF
0.6
0.65
0.7
0.75
0.8
0.85
0.9
0.95
1
SINR: ISD=200 mSIR: ISD=200 mSINR: ISD=300 mSIR: ISD=300 mSINR: ISD=400 mSIR: ISD=400 m
Coverage w/ different BS densities
SINR distribution sensitive to BS densitySINR not invariant with BS density due to LOS/NLOS links and noise power
From noise-limited to interference-limited when increasing BS density
Good coverage achieved when BSs are sufficiently dense20
Carrier freq. : 28 GHzSignal Bandwidth: 500 MHzTx power: 30 dBmTx directivity gain: 20 dB*Tx beamwidth: 30 degree*Rx directivity gain: 10 dBRx beamwidth: 90 degreeLOS probability:Avg. LOS range: =200 mISD: average inter-site distance
p(r) = e��r
1/�
Noise-limited due to insufficient link budget
Interference-limited as SINR converges to SIR
* Beamforming parameter @ 28 GHz from: Z. Pi and F. Khan, "A millimeter-wave massive MIMO system for next generation mobile broadband," In proc. of Asilomar, Nov. 2012
(c) 2015 Robert W. Heath Jr.
SINR in dB-10 -5 0 5 10 15 20 25 30 35 40
CC
DF
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
2 GHz (ISD=500 m)
28 GHz (ISD=150 m)
28 GHz (ISD=400 m)
73 GHz (ISD=150 m)
73 GHz (ISD=400 m)
SINR coverage comparison
21
2 GHz parameters:Signal bandwidth: 50 MHzISD: 500 mTX power: 46 dBm4X4 MIMO with ZF receiver
28 GHz parameters:Signal bandwidth: 500 MHzTX power: 30 dBm8-by-8 UPAs at BSs4-by-4 UPAs at MSsEach with 4 RF chains
Building statistics: LOS range: 70 m(NYU measurement)
73 GHz parameters:Signal bandwidth: 2 GHzTX power: 30 dBm20-by-20 at BSs5-by-5 at MssUsing analog beamforming only(Same aperture size as 28 GHz)
Comparison of downlink SINR Perfect CSI at TX and RX
Due to larger noise power @ 73 GHz
Gain from smaller beamwidth @ 73 GHz
[1] M. K. Samimi and T. S. Rappaport, “ Ultra-wideband statistical channel model for non-line-of-sight millimeter-wave urban channels”, Gloabalcomm 2014.
28 GHz strategy:Beamforming @LOS2 streams enabled by polarization
Mode adaptation @ NLOSOptimize # of streamsNLOS channel model from [1]No polarization
73 GHz strategy:Beamforming w/ 1 stream
WHAT STARTS HERE CHANGES THE WORLD(c) 2014 Robert W Heath Jr.
Results on rate
(c) 2015 Robert W. Heath Jr.
Rate in Mpbs102 103 104
CC
DF
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
28 GHz (ISD=150 m)28 GHz (ISD= 400 m)73 GHz (ISD=150 m)73 GHz (ISD=400 m)2 GHz (ISD=500 m)
Rate coverage comparison
23
2 GHz parameters:Signal bandwidth: 50 MHzISD: 500 mTX power: 46 dBm4X4 MIMO with ZF receiver28 GHz parameters:Signal bandwidth: 500 MHzTX power: 30 dBmUsing hybrid beamforming:8-by-8 UPAs at BSs2-by-2 UPAs at MSsEach with 4 RF chains
Building statistics: LOS range: 70 m(NYU measurement)
73 GHz parameters:Signal bandwidth: 2 GHzTX power: 30 dBmUsing analog beamforming:20-by-20 at BSs5-by-5 at MSs(Same aperture size as 28 GHz)
Comparison of per user rate
Rate computation:5 dB gap from ShannonClipping not shown in the plot
Gain from larger BW
Gain from dense BS deployment
Gain over conventional cellular system
28 GHz strategy:Beamforming @LOS2 streams enabled by polarization
Mode adaptation @ NLOSOptimize # of streamsNLOS channel model from [1]No polarization
73 GHz strategy:Beamforming w/ 1 stream
[1] M. K. Samimi and T. S. Rappaport, “ Ultra-wideband statistical channel model for non-line-of-sight millimeter-wave urban channels”, Gloabalcomm 2014.
(c) 2015 Robert W. Heath Jr.
Average rate comparison
24
scenario 5% rate （Mbps）
avg rate (Mbps)
2 GHz with 1TX 1RX 1.3 68
2 GHz with 4TX 4RX 13 149
28 GHz with sparse BSs(ISD=400 m) 4.7 1560
28 GHz with dense BSs(ISD=150 m) 500 8300
73 GHz with sparse BSs(ISD=400 m) 8.2 4200
73 GHz with dense BSs(ISD=150 m) 830 14500
2 GHz parameters:Signal bandwidth: 50 MHzISD: 500 mTX power: 46 dBmMIMO with ZF receiver28 GHz parameters:Signal bandwidth: 500 MHzTX power: 30 dBmUsing hybrid beamforming:8-by-8 UPAs at BSs2-by-2 UPAs at MSsEach with 4 RF chains
Rate computation:5 dB gap from ShannonSINR clipped by 30 dB
Downlink rate at a typical outdoor user
More rate comparison see: Tianyang Bai, Ahmed Alkhateeb, and R. W. Heath, Jr., ``Coverage and Capacity of Millimeter Wave Cellular Networks," IEEE Communications Magazine, Sept. 2014.
Building statistics: LOS range: 70 m(NYU measurement)
73 GHz parameters:Signal bandwidth: 2 GHzTX power: 30 dBmUsing analog beamforming:20-by-20 at BSs5-by-5 at MSs(Same aperture size as 28 GHz)
WHAT STARTS HERE CHANGES THE WORLD(c) 2014 Robert W Heath Jr.
Conclusions
WHAT STARTS HERE CHANGES THE WORLD(c) 2014 Robert W Heath Jr.
Going Forward with mmWaveGood rates and coverage can be achieved in dense mmWave networks
Mmwave is a small cell solution
Will magnify gains of densification
Many opportunities for further researchAnalog beamforming algorithms & hybrid beamforming
Channel estimation, exploiting sparsity, incorporating robustness
Multi-user beamforming algorithms and analysis
Microwave-overlaid mmWave systems
Going away from cells to a more ad hoc configuration
Incorporating mobility
26
questions?
WHAT STARTS HERE CHANGES THE WORLD(c) 2014 Robert W Heath Jr.
Select publications (1/4)Performance analysis of mmWave cellular networks [J1,J2, C1,C2]
[J1] T. Bai and R. W. Heath Jr., “Coverage and rate analysis for millimeter wave cellular networks”, IEEE Trans. Wireless Commun., Feb. 2015In [J1], we proposed a stochastic geometry network model that incorporated key features of mmWave cellular systems, including directional beamforming and blockage effects. The downlink rate and SINR distributions was then investigated based on the network model. Our analyses showed that mmWave performance is much sensitive to the density of base stations: a denser base station deployment is required to achieve comparable SINR coverage to the conventional cellular networks; the comparable SINR translates to a higher achievable rate, due to the larger bandwidth assumed at mmWave.
27
WHAT STARTS HERE CHANGES THE WORLD(c) 2014 Robert W Heath Jr.
Select publications (2/4)[J2] T. Bai, A. Alkhateeb and R. W. Heath Jr., “Coverage and capacity in millimeter wave cellular networks”, IEEE Commun. Mag., Sep. 2014.In [J2], we showed that dense mmWave networks can achieve comparable coverage and significantly higher data rates than the conventional networks. Moreover, sum rate gains can be achieved using more advanced beamforming techniques that allow multiuser transmission. The insights are derived using the framework proposed in [J1].[C1] T. Bai and R. W. Heath Jr., “Coverage in dense millimeter wave cellular networks”, in Proc. of IEEE Asilomar, Pacific Grove, CA, Nov. 2013.We introduced a simplified LOS-ball network model for dense mmWave network analysis. We showed that the performance of dense mmWave networks is largely determined by the average number of LOS base stations that a typical user observes. (Related results also reported in [J1].)
28
WHAT STARTS HERE CHANGES THE WORLD(c) 2014 Robert W Heath Jr.
Select publications (3/4)[C2] T. Bai and R. W. Heath Jr., “Analysis of self-body blocking effects in millimeter wave cellular networks”, in Proc. of IEEE Asilomar, Pacific Grove, CA, Nov. 2014.We developed a cone-blocking model to characterize the blocking effect from cellphone users’ bodies with potential position changes; as human bodies can block mmWave signals causing 20-40 dB attenuation. Based on the network model in [J1], we analyzed the impact of self-body blocking on the SINR coverage and rate under different base station association rules. The results showed that self-body blocking decreases the SINR coverage, and may cause 10% degradation in achievable rates with certain system parameters.
29
WHAT STARTS HERE CHANGES THE WORLD(c) 2014 Robert W Heath Jr.
Select publications (4/4)Modeling building distributions w/ random shape theory [J3]
[J3] T. Bai, R. Vaze, and R. W. Heath Jr., “Analysis of blockage effects on urban cellular networks”, IEEE Trans. Wireless Commun., Sep. 2014. Leveraging concepts from random shape theory, we modeled the distributions of buildings in urban areas as rectangular Boolean schemes, where the certain of the buildings form a Poisson point process, and their sizes and orientations follow certain distributions. Based on the Boolean scheme model, we showed that the probability that a link is not blocked by any buildings decay exponentially with its length, which matches the LOS probability proposed in 3GPP standard. Furthermore, our analysis on system performance showed that SINR and rate performance in cellular networks can benefit from blockage effects, as buildings may block more interference that often comes from longer links.
30
