maximizing data volume for direct to ground satellite systems
DESCRIPTION
Maximizing Data Volume for Direct to Ground Satellite Systems. David Carek Satellite Networks and Architectures Branch NASA Glenn Research Center. Overview. Study initiated as part of ACAD (Advanced Communications Architecture Demonstration) Direct to ground communication system for ISS - PowerPoint PPT PresentationTRANSCRIPT
David Andrew Carek, P.E. at Lewis FieldGlenn Research Center
Maximizing Data Volume for Direct to Ground Satellite Systems
David Carek
Satellite Networks and Architectures Branch
NASA Glenn Research Center
David Andrew Carek, P.E. at Lewis FieldGlenn Research Center
Overview
• Study initiated as part of ACAD (Advanced Communications Architecture Demonstration)– Direct to ground communication system for ISS– Reliable transmission of latency tolerant payload
data
• Objective –maximize data volume
David Andrew Carek, P.E. at Lewis FieldGlenn Research Center
ACAD Link
• Initially examined ACK based protocol - TCP– Requires one ACK for every other packet – Large bandwidth asymmetry requires large packet size
on downlink• E.g. 622Mbps down; 622Kbps up => 1000:1 asymmetry• Required large downlink packet size to prevent ACK
feedback congestion on uplink– > 20Kbyte downlink packet required for 40byte uplink ACK
packet
– Needed to determine implication of bit errors on large packet transfers
David Andrew Carek, P.E. at Lewis FieldGlenn Research Center
Factors Affecting Data Volume
• Contact time (satellites)– Satellite altitude and orbit inclination (fixed)
– Ground station minimum elevation angle (design parameter tied to link budget)
– Ground station latitude (design parameter)
• Transmission Rate – Function of link budget transmitter power, antenna size,
etc.(design parameter)
• Protocol Efficiency
David Andrew Carek, P.E. at Lewis FieldGlenn Research Center
STK SimulationGround Contacts with ISS
ISS Orbit Inclination: 51.6
degAverage Alt: 380 km
Ground StationLattitude: 45 degMin Elevation Angle: 10 deg.
Factors Affecting Data Volume(Contact Time)
David Andrew Carek, P.E. at Lewis FieldGlenn Research Center
ISS Access time vs. Ground Station Latitude
0
5
10
15
20
25
30
35
0 10 20 30 40 50 60
Ground Station Latitude (deg)
Acc
ess
Tim
e (m
in/d
ay)
70 dayAverage
Maximizing Contact Time
White Sands
GRC
David Andrew Carek, P.E. at Lewis FieldGlenn Research Center
• Function of Link Budget with many interrelated factors– Ground Segment
• Antenna size – Goal for small transportable ground terminal (1.2 meter dish)
– Space Segment• Transmit antenna type/beam width (gimbaled horn)• Frequency/Bandwidth (~27GHz/500MHz)• RF amplifier power
Factors Affecting Data Volume(Transmission Rate)
David Andrew Carek, P.E. at Lewis FieldGlenn Research Center
• Protocol algorithm (e.g. TCP)– Congestion control
• degrades efficiency when actual loss is corruption
– Acknowledgment feedback congestion• high bandwidth asymmetry degrades efficiency
• Information efficiency– Amount of end user data carried over link
relative to total data transmitted
Factors Affecting Data Volume(Protocol Efficiency)
David Andrew Carek, P.E. at Lewis FieldGlenn Research Center
• Information Efficiency
– Packet delivery efficiency (driven by bit errors)• Function of error free packets received
• Increased packet size = decreased efficiency
– Header efficiency (for fixed size header)• Function of data allocated to header vs. user data
• Increased packet size = increased efficiency
Factors Affecting Data Volume(Protocol Efficiency)
hpi eee
David Andrew Carek, P.E. at Lewis FieldGlenn Research Center
Types of Bit Errors• Gaussian Bit Errors
– Random RF Noise
• Burst Errors– Random occurrence of multiple bit errors– E.g. rain, snow, particles, etc.
• Systematic Errors– Often caused by internal electronics– Can be periodic distribution of single bit error or burst error
• Pattern Sensitive Bit Errors– Form of Systematic Errors– Influenced by data pattern within stream
*Reference: An Introduction to Error Location Analysis, Are all your errors truly random?, Application Note 1550-2; Agilent Technologies, 2000
David Andrew Carek, P.E. at Lewis FieldGlenn Research Center
Packet 3Packet 2Packet 1
Packet 3Packet 2Packet 1
Packet 3Packet 2Packet 1
X X X
XXX
X X X
Random
Burst
Periodic
Packet Delivery EfficiencyData Stream with BER = 1x10-1 Bit efficiency = 90%
- Packet Efficiency = 33%
- Packet Efficiency = 67%
- Packet Efficiency = 0%
David Andrew Carek, P.E. at Lewis FieldGlenn Research Center
Header EfficiencyQuantities for Illustrative Purposes Only
XXX H H H H H I I I I I H H H H H I I I I IPacket 3Packet 2Packet 1
X = ErrorH = Header bitI = Information bit (user data)
Burst Error Example• BER = 1x10-1; Packet Size = 10 bits; Header Size = 5 bits
– Bit efficiency = 90%– Packet delivery efficiency = 67%– Information efficiency = 33%
David Andrew Carek, P.E. at Lewis FieldGlenn Research Center
p
hpERi S
S
n
SBe 11
Deterministic EfficiencyAssumes n can be determinedn = average # bit errors per errored packet
p
hSERi S
SBe p 11
Probabilistic Efficiency
Information EfficiencyInformation Efficiency
David Andrew Carek, P.E. at Lewis FieldGlenn Research Center
0%
20%
40%
60%
80%
100%
10 100 1000 10000 100000
Packet Size (bytes)
Info
rmat
ion
Eff
icie
ncy
(%
of
tota
l ban
dw
idth
)
Packet loss dominatesHeader loss dominates
p
hpERi S
S
n
SBe 11
Deterministic Efficiency
p
hSERi S
SBe p 11
Probabilistic Efficiency
BER
10-5
10-4
10-3
David Andrew Carek, P.E. at Lewis FieldGlenn Research Center
15%
20%
25%
30%
50 60 70 80 90 100 110
Packet Size (bytes)
Info
rmat
ion
Eff
icie
ncy
(%
of
tota
l ban
dw
idth
)2% Actual Difference
BER = 10-3
Sh = 40 bytes
Deterministic Equation(worse case periodic error distribution; n=1)
Probabilistic Equation(random single bit errors)
Packet Size vs. Information Efficiency
(71, 19%)
(71, 25%)
(93, 27%)
David Andrew Carek, P.E. at Lewis FieldGlenn Research Center
p
hpERi S
S
n
SBe 11
ER
hp B
nSS
Deterministic EfficiencyAssumes n can be determinedn = average # bit errors per errored packet
Optimal Packet Size
p
hSERi S
SBe p 11
)1ln(
411
2 ERh
hp BS
SS
Probabilistic Efficiency
Optimal Packet Size
Information EfficiencyInformation Efficiency
David Andrew Carek, P.E. at Lewis FieldGlenn Research Center
Information Efficiency – Periodic Error Distribution(Sp = variable, Sh = 40 bytes; n = 1)
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
1.E-08 1.E-07 1.E-06 1.E-05 1.E-04 1.E-03 1.E-02
Bit Error Ratio
Info
rmat
ion
Eff
icie
ncy
(%
of
tota
l b
and
wid
th)
65536 byte
1500 byte
128 byte
64 byte
Max. Efficiency
David Andrew Carek, P.E. at Lewis FieldGlenn Research Center
VME Bus
Mass StorageDevice
Main
Pro
cesso
r
An
alo
g/D
iscrete
I/O
TB
D R
/W IF
Dual LVDS
HR
DL/1
55
3/1
00
BT IF
100Mbps
APS
CORto HRFM
to Ku
Payload
HRDL
1553 PL/MDM
Ethernet
RS232
Ethernet
RS232
Gimbal Assembly
ISS Subsystems and Internal PayloadsACAD Processor/Storage Segment
L-band Up
RS232
Data Flow Unreliable
Data Flow Reliable
Data Flow Reliable NAK’s
OMT
Modulator B
Modulator A
Upconverter A
Upconverter B
HPA A
HPA B
RHCP Ka
LHCP Ka
Antenna
Pointing
Controller
Ka DownLNA
Uplink Antenna
Downconverter
Demodulator
David Andrew Carek, P.E. at Lewis FieldGlenn Research Center
Conclusions
• BER alone is not enough to design a link– Bit error distribution must be accounted for
– Upper layer protocol must be considered
• Properly sizing packet sizes can maximize information efficiency and extend link availability
• Auto-tuning protocols based on packet error ratios could extend link availability and efficiency