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MLS Band Sounding Measurements: Channel Characterization for Mobile and Fixed Airport Surface Communications
ACAST Workshop16 August 2005
David W. Matolak, Indranil SenSchool of EECS and Avionics Engineering Center
Ohio UniversityAthens, OH 45701
phone: 740.593.1241fax: 740.593.0007
email: matolak@ohiou.edu, is809902@ohio.edu
OHIO UNIVERSITYOHIO UNIVERSITYSchool of Electrical Engineering & Computer ScienceSchool of Electrical Engineering & Computer Science
Rafael ApazaFederal Aviation Administration
Aviation Research OfficeBelleville, MI
phone: (734) 487-7327fax: (734) 487-7428
email: rafael.Apaza@faa.gov
Ohio University2
Outline• Introduction
– Motivation and Band Selection– Importance of channel characterization
• Measurement Coordination• Channel characterization overview
– Method, sounder, example photos – Example results: mobile measurements– Comparison highlights (MIA and CLE)– Point-to-Point measurement results
• Summary & future work
Ohio University3
Introduction•• MotivationMotivation
–– Civilian aviation anticipates both a near and longCivilian aviation anticipates both a near and long--term need term need for new communications capabilitiesfor new communications capabilities
•• VHF spectral congestionVHF spectral congestion•• New services desired, both for mobile and New services desired, both for mobile and ““fixedfixed”” servicesservices
•• Band selectionBand selection–– Easiest to quickly deploy system in Easiest to quickly deploy system in ““cleanclean”” spectrumspectrum–– Deployment of new systems to Deployment of new systems to ““protectprotect”” reserved reserved
aeronautical spectrum (aeronautical spectrum (““use it or lose ituse it or lose it””))–– Both these points apply to the MLS extension band, 5.091Both these points apply to the MLS extension band, 5.091--
5.15 GHz, which is not widely used in many regions5.15 GHz, which is not widely used in many regions
Ohio University4
Introduction (2)• Importance of channel characterization
– Simply: if you don’t know your channel, system performance will be suboptimal, possibly very poor, with
• irreducible channel error rate that can preclude reliable message transfer
• spatial coverage “holes” where communication is not possible
• severely limited data carrying capacity which would require costly system additions to circumvent
– Very little work done for MLS band channel• Zero wideband experimental work for this band
around airport surfaces
Sounder Rx in FAA van, MIA
Ohio University5
Measurement Coordination• Miami International Airport (MIA) is the 12th busiest
airport in the US; Cleveland Hopkins (CLE) is one of the 50th busiest
• Access to airport movement area has become more complicated in the post 9/11 era – Strict security procedures must be followed to gain access to
the airport surface area—requires careful coordination with airport management
• Principle objective when planning a measurement activity is to minimize the impact to airport operations
MIA ATCT
Ohio University6
Measurement Coordination (2)• Prior to any measurements, FAA Spectrum Office
conducted an RFI study (clean!)• Obtained a Special Temporary Authorization to
transmit at the test frequency
TxIndranil(OU)
Selected “cat walk” at (old) ATCT sub-junction level for Tx• Good field of view• Access to AC power
Tx Setup
Omni Antenna
Horn Antenna
Ohio University7
Measurement Coordination (3)• Updated CLE measurement plan and for MIA, refined
– Data recording locations– Procedural approach– Airport ingress and egress requirements, driving rules– # personnel required to complete measurements
• Desired measurement locations evaluated with FAA for– accessibility– time of day– aircraft traffic activity– measurement execution
• Final measurement plan evaluated and approved by FAA
Ohio University8
Measurement Coordination (4)• MIAMI aerial view, with numbered measurement locations
• Covered─Taxiways─Gates─Cargo areas─Access roads • Both LOS and NLOS sites• Also conducted mobile tests w/Tx at P2
P2
P1
Ohio University9
∑−
=
−−−=1
0, )]([)]}()())(([exp{)();(
N
kkkckkDk ttttttjtth τδτωτωατ
Channel Characterization Overview• Thorough and accurate channel characterization
requires combination of 3 inter-related components:– Analysis: validate against theory, guide measurements– Simulations: create models for consistent evaluation of
comparative system designs– Measurements: data to build models, affirm theory, help
classify, and identify unforeseen conditions• Analytical and measurement results we obtain will be
directly usable by engineers evaluating and/or designing communication systems for this application
Ohio University10
Airport Surface Environment• Airport movement area is a dynamic environment
– airline ramp activities such as baggage handling, fueling, catering taking place throughout the day
– aircraft also taxiing, pushing and pulling out of gates– airport security vehicles, other ground vehicles moving about
• Airport surface area classification– LOS-O: Open areas, e.g., runways, some taxiways– NLOS-S: mostly NLOS w/dominant Specular component
plus low energy multipath components, e.g., near terminals– NLOS: obstructed LOS, largest DS, e.g., near gates
• Aircraft inhabit all three regions—non-stationary channel, in contrast to most terrestrial models
• Large buildings present persistent, long-delay multipath, also in contrast to most terrestrial models
Ohio University11
Channel Sounder• For sounding, we have purchased and employed a
wideband channel sounder with adjustable center frequency, transmit power, and bandwidth
– Modified version of Berkeley Varitronics Inc. “Raptor”model, with several upgrades• faster data output rate• wider bandwidth • increased output power
– Multiple antenna types
Tx Rx
Mobile Multiuser Communications Labat Ohio University
High-gain horn, Miami
Ohio University12
Measurements: Example Photos (1)
OU AEC Van FAA Van
Mobile Measurements, CLE, March 2005
Ohio University13
Measurements: Example Photos (2)Point-to-Point Measurements, MIA, June 2005
ATCT
Brian(NASA)
Wenhui(OU)
Dave(OU)
Ohio University14
Example Results• Power delay profiles—PDPs (received power vs.
delay), after noise thresholding
CLE, NLOS-S caseSignificant multipath (~ 9 dB) up to
3Tc (0.06 µsec) + numerous weaker components
MIA, NLOS caseSignificant multipath (~ 0 dB)
up to 15Tc (0.3 µsec)
0 1 2 3 4 5-130
-120
-110
-100
-90
-80
-70
Delay in us ec
Pow
er in
dB
m
0 1 2 3 4 5-130
-125
-120
-115
-110
-105
-100
-95
-90
-85Exam ple PDP for a scenario
Delay in usec
Pow
er in
dB
m
στ~500ns στ~1430ns
Ohio University15
0 10 20 30 40 50 60 70 8050
100
150
200
250
300
350
400
450
PDP Index
In N
ano-
Sec
onds
Cleveland: Mix of LOS and NLOS
RMS Delay Spread
Example Results (2)• Useful statistic is RMS delay spread (DS)• Plots of RMS-DS vs. profile index (time)
CLE: Single transition from LOS to NLOS
MIA: Multiple transitions to/from NLOS/LOS/NLOS
0 20 40 60 80 100 1200
500
1000
1500
2000
2500
IRE number
In N
ano-
Sec
onds
RMS Delay spread in nanosecond
RMS Delay Spread
Ohio University16
Example Results (3)• MIA PDP: power vs. delay and vs. time, NLOS
τ (µsec)t (sec) 0
12
34
56
00.2
0.40.6
0.81
1.21.4
-130
-125
-120
-115
-110
-105
-100
-95
-90
-85
-80
X: 0.06Y: 0Z: -91.22
X: 0.06Y: 0.25
Z: -98.73
X: 0.06Y: 0.75
Z: -85.14
Rel
ativ
e M
agni
tude
Ohio University17
MIA: Two Regions Measured
MIA Statistics
0.72313822.6380Mean
0.995100130.532.8Min
0.417239411000Max
BWc(MHz)
NLOS(nsec)
BWc(MHz)
NLOS-S(nsec)
στStatistic
• NLOS-Specular (NLOS-S) –Majority of airport surface area (approx 65% of time)–Mostly NLOS conditions with dominant specular component and a number of low energy multipath components
• NLOS– Obstructed or grazing specular component, and significant number of high-relative-energy multipath components
CLE στ Stats
76331140149.5
2306395
MR(nsec)
LOSO(nsec)
Ohio University18
Example Modeling Result, MIA• Tap probability of occurrence (fraction of time)• Threshold = 20 dB from main tap
• NLOS-S– Number of taps =19
• NLOS– Number of taps =69
0 10 20 30 40 50 60 700
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
Tap-Index
Pro
babi
lity
of h
avin
g ta
p
Probability for existence of tap
NLOS - 69 TapsNLOS-S - 12 Taps
Ohio University19
Example Modeling Result (2)• Average power versus tap index
•NLOS-S– Number of taps =19
– 4 taps total within ~20 dB of main tap
•NLOS– Number of taps=69
– 5 taps total within ~20 dB of main tap
0 10 20 30 40 50 60 70-40
-35
-30
-25
-20
-15
-10
-5
0
Tap-Index
Pow
er
Curve fit for different Taps
NLOS - 69 TapsNLOS-S - 19 Taps
Ohio University20
Example Modeling Result (3)• Amplitude distribution, MIA
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
D a ta
Dens
ity
D a taR ic e : K = 5.7 7 dBW e ib ull: b= 3 .4
0 0.5 1 1.5 20
0.2
0.4
0.6
0.8
1
1.2
1.4
Data
Den
sity
DataNakagami : m = 0.75W eibull: b = 1.629
Tap #1 (Specular) Tap #2
NLOS-S
0 1 2 3 4 5 60
0.2
0.4
0.6
0.8
1
1.2
Data
Den
sity
DataLognormal: mean=1.33, var = 0.6Nakagami : m=0.89Weibull : 1.72
0 0.5 1 1.5 2 2.5 3 3.50
0.5
1
1.5
Data
Den
sity
DataNakagami : m = 0.73Weibull : b = 1.57
Tap #1
NLOS
Tap #2
Ohio University21
MIA Airport
Airport Comparisons• MIA= LARGE airport; CLE= MEDIUM airport• Some similarities in channel characteristics
– Both have 3 regions: LOS-Open, NLOS-S, and NLOS– Both have correlated scattering, in all regions– Amplitude statistics for some taps worse than Rayleigh
• Significant differences in channel characteristics– Reflectors much bigger in MIA (larger planes and larger
buildings), yielding persistent, strong, long-delay multipath• Generally larger delay spreads in MIA
– RMS-DS shows multiple transitions within single data set
Ohio University22
Point-to-Point Measurements• From ATCT to ground sites• Envisioned use of ground sites
– Data transfer from sensors to ATCT– Relay of information from mobile platforms to/from ATCT
• Characterized received power and delay spread vs. azimuth angle
Ohio University23
P2
P1
ILS Site Orientations
-35-30
-25-20
-15-10
-5 0
30
330
0 90°
270°180°
Tx atATCT
Rx atILS
0
15°
30°45°
60° 75°90°
105°
120°
135°
150°
165°
±180°
-165°
-150°
-135°
-120°-105°-90°
-75°
-60°
-45°
-30°
-15
-60-40
-200
max=16.7234dB
Ohio University24
Example Results: ILS Site• Power delay profile, after noise thresholding
0° (Boresight)• Multipath (~ -10 dB) from
ground reflection• All other multipath more than
25 dB down from LOS signal
0 1 2 3 4 5-130
-120
-110
-100
-90
-80
-70
-60E x am ple P DP for a sc enario
Delay in us ec
Pow
er in
dB
m
15° Orientation• Multipath (~ -8 dB) at ~0.3 µsec• All other multipath more than 20
dB down from LOS signal
0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5-130
-120
-110
-100
-90
-80
-70
-60
-50
Delay in usec
Pow
er in
dB
m
στ~241 ns στ~388 ns
Ohio University25
Example Results (2)• PDP: power vs. delay and vs. time
τ (µsec)t (sec) 0
12
34
56
00.2
0.40.6
0.81
1.21.4
-130
-125
-120
-115
-110
-105
-100
-95
-90
-85
-80
Rel
ativ
e M
agni
tude
105° Orientation• Direct signal and
stable multipath at 0.3, 2.5 and 4 µsec
• Stable multipath from large buildings
Ohio University26
Example Results (3)
Received power vs. azimuth angle, ILS site (P2)
-180 -150 -100 -100 0 50 100 150 180
-20
-18
-16
-14
-12
-10
-8
-6
-4
-2
0
Angle (degree)
Rel
ativ
e P
ower
(dB
)
0 50 100 150 200 250 300 3500
200
400
600
800
1000
1200
1400
1600
1800
Angle in degreesR
MS
in n
sec
GEM Site MFA Site
P1
RMS-DS vs. azimuth angle
P2
Ohio University27
Example Result (4)• FCE and RMS-DS vs. time, 165° GEM (P1)• PDP can vary in time with mobile scatterers (vehicles,
people)
-25 -20 -15 -10 -5 0 5 10 15 20 25
0.4
0.5
0.6
0.7
0.8
0.9
1
Frequency in MHz
Cor
rela
tion
Coe
ffici
ent
0 10 20 30 40 50 60500
600
700
800
900
1000
1100
1200
IRE number
In N
ano-
Sec
onds
RMS Delay Spread
Ohio University28
Point to Point Link Summary• Both CLE & MIA measurements show MLS band use
feasible– Link closure easy with typical components– Lower channel dispersion (than mobile settings)– Larger coherence BW (than mobile)– Potential for angular (spatial) diversity for
improved security and performance– Measurements of received power and RMS-DS vs.
azimuth useful for siting (e.g., help determine where NOT to locate relay stations)
Ohio University29
Summary• Provided update on characterization of the 5 GHz MLS
“extension” band channel– Need for effort from the point of view of efficient
communication link design, and band protection• Recent measurement campaigns at CLE and MIA
airports described, including – Coordination w/ local authorities required for successful tests– Short description of equipment, measurement process– Example measured results– Example modeling results– Results for point-to-point links
Ohio University30
Future Work• Gather additional measurement data at one (or two)
more large airports– JFK, 28-31, Aug 2005– Detroit? Fall 2005?
• Completion of data processing • Completion of channel modeling for
– Mobile settings– Point to point settings– “Relay” settings
Ohio University32
t
s(t)
A
-A
-3A
3A
t
s(t)
A
-A
-3A
3A
Impact of Channel Characteristics• Channel characteristics affect
– modulation(s)– forward error correction coding schemes– antenna characteristics, and physical facility siting rules – receiver processing methods (synchronization, interference
suppression, combining, etc., all generally adaptive)– power spectrum and bandwidths– attainable data rates and latencies, message block sizes– adaptation algorithms for allocating resources in T/F/S domains – authentication and user ingress/egress latencies– duplexing and multiplexing methods– security measures and performance (against
eavesdropping, jamming, spoofing, etc.)
Ohio University33
Channel Characterization Method• “Sounding” = transmission and subsequent reception of
a test signal, from which we can infer channel characteristics: the impulse response
• Common test signal is a direct-sequence spread spectrum signal, whose known correlation properties can be exploited to estimate channel’s impulse response
What is the channel?A wireless channel is the (set of) transmission path(s) taken by an electromagnetic signal from transmitter to receiver. The mobile channel is the wireless channel with at least one platform (Tx or Rx) in motion.
Ohio University34
Regulatory Issues• Through industry support functions such as I-CNS
2004, ACAST 2004, NASA has identified protection of the 5000-5150 MHz band for aviation use as one of the top priorities for ACAST– Emphasis on the MLS extension band 5091-5150 MHz
• First, GPS navigation and WAAS/LAAS enhancements circumventing need for MLS deployments, leaving much of the MLS band either quiet or underutilized
• Second, spectrum at 5 GHz presents enormous potential for revenue to short range, wideband wireless networking OEMs (e.g., 802.11)
• Third, spectrum auctions in or near this band present potential revenue streams for the federal government
– Combination of these factors has heightened need to justify the continued use of this spectrum for aviation purposes
Ohio University35
Regulatory Issues (2)• It is NASA’s intent to demonstrate, through ACAST,
the applicability of this band for wideband surface area signaling, and how this usage may alleviate some of the congested VHF voice bands for ATC
• The first step in this effort is proper characterization of the MLS radio channel
• Radio Communication group of the International Telecommunication Union (ITU-R) holds a World Radio Conference (WRC) every 3-4 years – Member nations discuss and decide upon the global use of
radio spectrum at these conferences
Ohio University36
Regulatory Issues Detail• On agenda of WRC-2007 is use of aviation spectrum:
“To consider allocations for the aeronautical mobile (R) service in parts of the bands between 108 MHz to 6 GHz, and to study current frequency allocations that will support the modernization of civil aviation telecommunication systems.”
• This agenda item affords opportunity to have areas of spectrum between 108 MHz to 6 GHz characterized for aeronautical mobile route services (AM(R)S– Results of channel characterization being presented to domestic and
international governing bodies so that there is a sound engineering argument for use of this band for wideband signaling on the airport surface, and that this band may be included in regards to Agenda Item 1.6. It is intended that this effort support inclusion of MLS band as an integral piece of modernization of civil aviation communication systems
Ohio University37
Channel Characterization Plan• Today’s focus on measurements and analysis
Analysis• Channel Class Definition• Parameter Estimation
TM, Bc, fD, tc, α, L, ρs, ρt, PDP
and statistics, e.g., max, min, mean, variance
Simulations• Closed-form models
TM, fD, α, L• Statistical Models
p(α), p(θ), p(L),…
Measurements• Channel class definition (e.g., small airport, medium,
large open, large cluttered, long range, etc.)• Channel sounding: specific values and statistics for all
1. Impulse response: TM, L, Bc, α, PDP2. Frequency selectivity and time variation: fD, tc, ρt3. Attenuation and coverage: α, ρs
Inputs• Physical location
description• Carrier frequency• Antenna
characteristics • Velocities• Scatterer properties: electrical, kinematic
Ohio University38
Channel Sounder Spectrum• Transmitted signal measured power spectrum
• Chip rate 50 Mcps• fc=5.12 GHz• Span=100 MHz• 99% power BW equal to 52.76 MHz
Ohio University39
CLE Pt-to-Pt Channel StatisticsRMS-DS and Coherence Bandwidth
Three Point-to-Point Settings
[1.75, 3.2, 4.2][1.7, 3.2, 4.5][2, 3.25, 4][2.2, 3.7, 4.5]146239294403 (1.3 km)
[1.5, 2.75, 3.2][2, 3.5, 4.5][4, 7.25, 8.5][2, 3.25, 4]31217010148.22 (3.3 km)
[1.5, 4.25, 5][2, 3.5, 4.5][2.3, 4.5, 5.6][2.3, 3.9, 5.4]2737010131.81 (1.4 km)
270°180°90°0°270°180°
90°0°
Frequency Correlation Estimateat Correlation of [0.8, 0.5, 0.3]
for 4 Angular Orientations(MHz)
RMS Delay Spread for 4 Angular Orientations
(0° is “boresight”)(nanoseconds)
Location
Knowing delay spread and frequency correlation as function of angle and time enables selection of signal bandwidth/data rates, siting, diversity, and antenna characteristics
Ohio University40
-25-20
-15-10
-50
510
1520
25
00.5
11.5
22.5
33.5-60
-50
-40
-30
-20
-10
0
Rel
ativ
e P
ower
-dB
Example Results, MIA• Time-varying spectrum |H(f,t)|2
f (MHz)t (sec)
Ohio University41
Point-to-Point Measurements• Tx/Rx Antenna
Characteristics– Gain ~8.5/17 dB– Azimuth
• 3 dB beamwidth ~60/30°• 10 dB beamwidth ~ 100/50°
– Elevation • 3 dB beamwidth ~ 60/15°• 10 dB beamwidth ~ 120/30°
• RSSI and power delay profile (PDP) measurements taken at 24 angles in azimuth, 15° apart
Tx
0
15°
30°
45°
60°
75°
90°
105 °
120 °
135 °
150 °
165 °
±180
°
-165
° -150
° -135
°
-120
°-1
05°
-90 °
-75 °
-60 °
-45 °
-30 °-1
5
-60
-40
-20
0
1672
34dB
Rx
-35-30-25-20-15-10-5 0 30
210
60
240
90270
120
300
150
330
180
0Antenna Radiation Pattern for Horn in Azimuth Azimuth Patterns
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