infostation overlays in cellular systems joan borràs & roy yates
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Infostation overlays in cellular systems
Joan Borràs & Roy Yates
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Outline
Cellular systemsInfostationsCell area vs Coverage areaSystem modelPerformance measuresNumerical example
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Wireless Data over 2G Cellular
Cellular Voice: Anytime Anywhere Slow: 10K bps High cost/bit
v cents/min voice = 13v cents/MBData over Cellular:
Slow and Expensive:20 cents/min voice = $2.60/MB
• 100X too high
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Wireless Data over 3G Cellular
2X or 3X increase in BW efficiency reduced cost/bit
Higher speed: 144K or 384K bpsBut voice is still 10K bps
v cents/min = 13v cents/MB $/MB still to high for
anytime/anywhere data
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DATA can tolerate delay!
Messaging services: e-mail, voice mail, fax, maps, non-interactive web pages, ...
We don’t need ubiquitous coverage
Reduced coverage Higher data rates
A little wait might be worthwhile!
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Infostations
Network of wireless portsIrregularly distributedDiscontinuous coverageAsymmetric linkHigh data rate transmissionMessaging services
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Infostation System
Download a map
Internet access
Low bit-rate cellularE-mail
voice mailfax
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Isolated Infostation
•Optimization Problem:•With finite energy, how many bits can be delivered?
•Solution: Use small coverage
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Highway Infostations
•Distance attenuation time varying channel
•Xmit power profile = Time Average Capacity
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Cellular Infostations
• Infostationsat cellular sites
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Traditional Cellular
Modulation and BER SIR thresholdSIR Cluster size N
(frequency reuse)
For worst-case location!
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Cell area Coverage area
For Infostations, there is no need to provide ubiquitous coverage
Better SIR conditionsSmaller cluster sizeMore bandwidth
availableHIGHER DATA RATE!
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SIR in 2D Infostation system
6
1
SIR
i
n
i
n
Dd
P
rd
P
n
r
RN
3
6
1SIR
Rr
D 1
D 3
D 6
D 4
D 2
D 5
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Possible operating points
SIR with respect to r/R and N
2D
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Which system is better?
2M bps 6M bps
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System model
Every Infostation is modeled as an M/M/1 queue with reneging
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Parameters for 2D
User density, uCell radius, RMobile speed, v,
fV(v)Coverage radius, rData rate, cMessages per user
per second, u
Message size, m
= (2r)(u/2) E[V]1/ = E[X] = = u tc (m/c) = 2E[V]/r
Rr
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2D Cycle Time
Bias: f()=cos()/2, 0<||</2
Prob(-<<)=r/R tc= (R2)/(2r E[V])
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Mailbox
Between Infostation visits, messages accumulate in mailbox
After successful visit, ready for nextAfter unsuccessful visit, either
the residual contents of a mailbox are discarded, or
the mailbox will not accept new messages until it is emptied
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2D Performance
Throughput c (1-p0)
Delay tc / (1-Pout) + tQ
tc = (R2/2r E[V]) 1-Pout = ( /)(1-p0)
tQ calculated for M/M/1 FCFS with reneging
),()(
)( )()(
0
e
p
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2D Numerical Example
Modulation N c r/ R E[X]
BPSK 1 1 0.66 9.52 0.26
1 2 0.56 5.61 0.22QPSK 3 0.67 .97 9.72 0.38
1 4 0.37 4.25 0.15
3 1.33 0.64 7.36 0.25
4 1 0.74 8.49 0.2916 QAM
7 0.57 0.99 11.11 0.39
1 6 0.25 4.19 0.10
3 2 0.42 7.48 0.16
4 1.5 0.49 8.55 0.19
7 .86 0.65 11.28 0.2664 QAM
12 0.5 0.85 14.78 0.33
u=(0..0.0004), R=500, E[V]=2.5, m=2e6, u=0.01
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2D Throughput: 64QAM
(r/R)2
6.25%17.6%24.0%42.2%72.2%
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2D Reneging probability: 64QAM
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2D Delay: 64QAM tc / (1-Pout) + tQ
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2D Throughput: N=1
(r/R)2
6.25%13.7%31.4%43.6%
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2D Reneging probability: N=1
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2D Delay: N=1 tc / (1-Pout) + tQ
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Conclusions
Reduced coverage, allowing higher level modulations and smaller cluster sizes, provides increased throughput.
For 1D, delay is also better (see WPMC’99)
For 2D, as user density (offered load) increases, delay performance gets relatively better.