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Online Spectrum Allocation for Cognitive Cellular Network Supporting Scalable Demands
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Transcript of Online Spectrum Allocation for Cognitive Cellular Network Supporting Scalable Demands
State Key Laboratory of Virtual Reality Technology and Systems
Online Spectrum Allocation for Cognitive Cellular Network Supporting Scalable Demands
Jianfei Wang, Jinzhao Su, Wei Wu 2011-6-2
State Key Laboratory of Virtual Reality Technology and Systems
Outline• Motivation• Consideration• Algorithm Detail• Evaluation• Conclusion
State Key Laboratory of Virtual Reality Technology and Systems
Motivation• To Decrease Client Waiting Time– Online Spectrum Allocation
• To Take advantage of scalable property of request– Satisfaction Degree• Satisfaction degree is equal to ratio of allocated
bandwidth versus requested bandwidth
State Key Laboratory of Virtual Reality Technology and Systems
Consideration • Don’t reclaim client’s resource by force.– Reclaim will increase system’s network cost.– Reclaim will decrease client’s experience.
• High Spectrum Utility Rate– The higher is spectrum utility rate in busy time,
the better• Low denial of service
Spectrum Utility Rate
denial of service
State Key Laboratory of Virtual Reality Technology and Systems
System Model• Complete graph– Allocation among users of the same base station
• Coordinate Network– Users must get Base station’s permission
State Key Laboratory of Virtual Reality Technology and Systems
System Assumption– Arrival of users’ request• Possion process
– Users’ service time• Exponential distribution
– Queuing rules• FCFS
– Capacity of the system• Users’s amount must be less than N0
State Key Laboratory of Virtual Reality Technology and Systems
State Machine of System
r
Normal
Normal
PoorRich
State Key Laboratory of Virtual Reality Technology and Systems
Stabilization of Normal State• According to the assumption, the system in
the normal state can be modeled as queueing system, M/M/N0/N0.
• We can get the relationship among satisfaction degree , departure rate and arrival rate. 0*
*a
f wr
w
0 0
0
0!
0
k
kk
p k Np k
k N
State Key Laboratory of Virtual Reality Technology and Systems
Indentify State Transform• Boundary between Normal and Poor,
• Boundary between Rich and Normal,
• Target Frequency Ratio of Normal State,– From Frequency Utility Ratio’s aspect, the larger is
f , the better.– From denial of service’s aspect, the lower is f, the
better.
1,( | )poor t t nnP f f R
2( | , )rich t n t nP f f R
poorf
richf
normalf
State Key Laboratory of Virtual Reality Technology and Systems
Estimation of Arrival Rate• From the pictrure, we can see that the arrival
rate has the seasonal propersty. So we use the seasonal arma model to estimate the arrival rate.
24
( ) ( )
( )(1 ) ( )
( ) ( )
B z t
B B z t
B a t
State Key Laboratory of Virtual Reality Technology and Systems
Estimation of Departure Rate• Maximum likelihood– The Customers who recently depart• The number of Customers who recently depart is• The service time of customer i is
– The customers who are active• The number of active customers is • The service time of active customers which has elapsed
is 1 1* ( )
1ˆ ( )
est
i activei N
est
t T N t
N N t
activeT
itestN
( )N t
State Key Laboratory of Virtual Reality Technology and Systems
Evaluation• Evaluation Data– Wifidog[7] which were collected from a large
number of free Wi-Fi hotspots in Canada for three years.
• Evaluation Parameters– Target Frequency Utility Ratio of Normal State is
80%– Boundary between Normal and Poor and Boundary
between Rich and Normal are derived from training with part of wifidog data.
State Key Laboratory of Virtual Reality Technology and Systems
Evaluation Result
Active Consumers vs Satisfaction System Free Spectrum Statistics
State Key Laboratory of Virtual Reality Technology and Systems
Conclusion• we propose an algorithm for online spectrum allocation for
scalable demands in cognitive cellular network.• We introduce a concept of users’ satisfaction degree to make
good use of scalable property of demand.• To handle the issues produced by online property, we involve
queueing system and estimations of arrival and departure rate to balance the spectrum utilization and future demands.
• With theoretical analysis of system, we give the method of calculating parameters of system.
• At last we use collections of real wireless data to evaluate our algorithm.
State Key Laboratory of Virtual Reality Technology and Systems
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