Online Spectrum Allocation for Cognitive Cellular Network Supporting Scalable Demands

Jianfei Wang 2011-5-23

Outline

• Introduction• Algorithm Target• Algorithm Detail• Evaluation

Introduction

• Online Spectrum Allocation• Scalable Demands– H.264

• Satisfaction Degree

Algorithm Target

• Zero User Wait Time• High Spectrum Utility Rate

Spectrum Model

• Complete graph • Coordinate Network

System Assumption

• Queue System– Arrival of users’ request• Possion process

– Customer’s service time• Exponential distribution

– Queuing rules• FCFS

– Capacity of the system

State Machine of System

1

1 2

2 3

3

,

,

,

, 1

rich

normal

poor

terrible

S f f

S f f fState

S f f f

S f f

Stabilization of Normal State

• M/M/N0/N0

0

0 0

0

0

1

0!

0

1

1!

k

kk

N k

kk

p k Np k

k N

p

k

2 0 22

2

**

a

f wr

w

State Boundary

• Boundary between Normal and Poor

• Boundary between Rich and Normal

• Frequency Ratio of Normal State– Frequency Utility Ratio vs Block Probability.

( ( ) | ) 1%n t nP N t k 0 0

0 * 0.01!

n n

N N i

i ii k i k

p pi

( ( ) | ) 1%.m t nP N t k

Estimation of Arrival Rate

• ARMA24( ) ( ) ( )(1 ) ( ) ( ) ( )B z t B B z t B a t

Estimation of Departure Rate

• Data Source– The Customers who recently depart– The customers who are active

1ˆ

est

est

i activei N

N

t T

Evaluation

• Evaluate Parameters– f2=0.8

1 2 3 4 5 6 7 8

f1 0.564153 0.483221 0.4066 0.377457 0.322373 0.315271 0.474543 0.594657

f3 0.95 0.95 0.95 0.95 0.95 0.95 0.95 0.95

9 10 11 12 13 14 15 16

f1 0.633976 0.668163 0.68019 0.684547 0.686111 0.695397 0.696661 0.698121

f3 0.95 0.944143 0.922292 0.91273 0.914815 0.906657 0.906498 0.908398

17 18 19 20 21 22 23 24

f1 0.694996 0.686159 0.684864 0.680694 0.677629 0.658058 0.652859 0.626415

f3 0.908841 0.9181 0.920285 0.922975 0.928602 0.935905 0.95 0.95

Evaluation Result

Active Consumers vs Satisfaction System Free Spectrum Statistics

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