Slide 1 E3E3 ICC 2008 - Beijing 21 May 2008 Simulated Annealing-Based Advanced Spectrum Management...

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ICC 2008 - Beijing21 May 2008

Simulated Annealing-Based Advanced Spectrum Management Methodology for WCDMA Systems

Jad NasreddineJordi Pérez-RomeroOriol SallentRamon Agustí

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Outlines

• Introduction• Proposed approach• Simulation and results• Conclusions

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Actual Spectrum AllocationActual spectrum allocation is

space and time invariantTraffic distribution is non-

homogenous in time and space

A large amount of the spectrum is underutilized

Several bands are saturated

Decrease in the offered QoS to users Decrease of operators profits

Increase in a RAT traffic Network infrastructure extensions and cost

* FCC, Spectrum Policy Task Force “Report of the Spectrum Efficiency Working Group,” November 15, 2002.

Spectrum access and not spectrum scarcity reduces

spectrum efficiency*

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New paradigm of Spectrum Management

• More flexible spectrum management: Advanced Spectrum Management (ASM)– Better spectrum allocation to operator– Better spectrum allocation to RATs in each

operator– Better spectrum assignment to cells in each

RAT

A need to estimate the required amount of spectrum

per cell/area

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Problem Formulation

• PROBLEM Identify the best (medium to long-term) spectrum assignment to cells– Best spectrum assignment:

• Maximize the spectrum efficiency while the required QoS levels are guaranteed

• Release some blocks of spectrum when possible– Creating Spectrum holes

• SOLUTION Use a smart radio indicator that is able to reflect both macroscopic and microscopic properties of the radio network– smart radio indicator:

• coupling matrix

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Objectives

• Considered system– Several carriers are available– Uplink of WCDMA

• Objectives– Estimate the number of carriers needed by a WCDMA

system– Estimate the number of carriers needed by each cell– Smartly distribute the available carriers among cells in

order to increase system performance– Spare carriers that could be exchanged between

different RATs or operators without a risk of high interference

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Illustrative ExampleCarrier 1

Carrier 3

Carrier 2 The same capacity

Some carriers could be released for other RATs/operators or secondary

market

Use ASM methodology

With frequency reuse 1

All carriers are used

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Coupling Matrix

• Why Coupling Matrix?– Actual estimation of the required amount of spectrum

per cell• based on cell load estimation

– does not take into account inter-cell interference under estimation of needed carriers

• based on inter-cell interference estimation– using fixed ratio a between inter-cell and intra-cell interference

(a is highly related to the carrier-to-cell allocation)

– Coupling Matrix• Reflects interference patterns with more accuracy• Extension of Compatibility Matrix• Medium and long term scale

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• The Jacobian of interference system of equations

• Low complexity without adding signaling traffic (use available information)• Medium and long term scale (fast variations such as fading are averaged)

I NI C P

Coupling Matrix

Depends on path losses, spreading factors and Eb/N0s

Coupling MatrixTotal received power

,,

,

0 if

otherwise1

l jj l

j j

l jSCS

,,1

TN j

j j

NP

S

,,

1 ,

b o

1

1/

ll

ll l

l

ni l

l jii i j

i

LS

LE N

Sl,j: indicator of the influence of mobiles in cell l over cell j that depends only on mobile path losses and

services.

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ASM Algorithm

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Outage Probability Estimation

• Estimates outage probability without testing them on real systems– Otherwise, unacceptable

performance for significant periods of time

– Based on matrix inverse– Require path loss

distribution– complexity : O(K3)

b oo, , max

maxb o

1/

Pr Pr( | )

1 cdf 1/

jj i j j jj

j j

E NL P i

I

P IE N

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Simulation Model

• Outage Probability threshold 0.05

• System with 3 carriers• Uplink• Heterogeneous traffic

distribution• Rb = 12.2 Kbps • Compared algorithms:

– Uniform algorithm– ASM

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Release several carriers

Results (1/2)Outage probability constraint is satisfied: always less than 0.05

Approximately multiply by two the spectrum efficiency

keeps the variation of cell’s spectrum efficiency as low as

the discreet values of the bandwidth allows

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Conclusions• Introduction of a new ASM methodology:

– Objectives:• An efficient spectrum utilisation of licensed spectrum bands

– In accordance with the existing load levels • Releasing some carriers for a secondary usage in large geographical areas

– When the load levels are low enough– Based on a simulated annealing– Uses coupling matrix

• The results show that– The QoS levels (outage probability) are respected– The spectrum efficiency is significantly increased– Some carriers are released

• Future work– Utilization of the released carriers by cognitive radios without polluting

WCDMA users with harmful interference

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Thank you

Acknowledgment: This work was performed in project E2RII/E3 which has received research funding from the Community's Sixth/Seventh Framework programme. This paper reflects only the authors' views and the Community is not liable for any use that may be made of the information contained therein. The contributions of colleagues from E2RII/E3 consortium are hereby acknowledged.

Slide 1 E3E3 ICC 2008 - Beijing 21 May 2008 Simulated Annealing-Based Advanced Spectrum Management...

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