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Michael Lunglmayr Particle Filters for Equalization Page 1 I n f i n e o n A FEASIBILITY STUDY: PARTICLE FILTERS FOR MOBILE STATION RECEIVERS CSNDSP 2006 Michael Lunglmayr, Martin Krueger, Mario Huemer

Michael Lunglmayr Particle Filters for Equalization Page 1 Infineon A FEASIBILITY STUDY: PARTICLE FILTERS FOR MOBILE STATION RECEIVERS CSNDSP 2006 Michael

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Page 1: Michael Lunglmayr Particle Filters for Equalization Page 1 Infineon A FEASIBILITY STUDY: PARTICLE FILTERS FOR MOBILE STATION RECEIVERS CSNDSP 2006 Michael

Michael LunglmayrParticle Filters for EqualizationPage 1

Infi

neo

nA FEASIBILITY STUDY: PARTICLE FILTERS FOR MOBILE STATION RECEIVERS

CSNDSP 2006

Michael Lunglmayr, Martin Krueger, Mario Huemer

Page 2: Michael Lunglmayr Particle Filters for Equalization Page 1 Infineon A FEASIBILITY STUDY: PARTICLE FILTERS FOR MOBILE STATION RECEIVERS CSNDSP 2006 Michael

Michael LunglmayrParticle Filters for EqualizationPage 2

Contents

Introduction

Simulation Model

Particle Filters

Particle Filters for Equalization

Simulation Results

Page 3: Michael Lunglmayr Particle Filters for Equalization Page 1 Infineon A FEASIBILITY STUDY: PARTICLE FILTERS FOR MOBILE STATION RECEIVERS CSNDSP 2006 Michael

Michael LunglmayrParticle Filters for EqualizationPage 3

Introduction

Particle Filters popular in e.g. image recognition, positioning,...

Aim of this work: Equalization with particle filters

Symbol estimation for GSM/EDGE in a multipath propagation environment

Page 4: Michael Lunglmayr Particle Filters for Equalization Page 1 Infineon A FEASIBILITY STUDY: PARTICLE FILTERS FOR MOBILE STATION RECEIVERS CSNDSP 2006 Michael

Michael LunglmayrParticle Filters for EqualizationPage 4

Simulation Model

Page 5: Michael Lunglmayr Particle Filters for Equalization Page 1 Infineon A FEASIBILITY STUDY: PARTICLE FILTERS FOR MOBILE STATION RECEIVERS CSNDSP 2006 Michael

Michael LunglmayrParticle Filters for EqualizationPage 5

Simulation Model

Page 6: Michael Lunglmayr Particle Filters for Equalization Page 1 Infineon A FEASIBILITY STUDY: PARTICLE FILTERS FOR MOBILE STATION RECEIVERS CSNDSP 2006 Michael

Michael LunglmayrParticle Filters for EqualizationPage 6

Particle Filters

Connection to Equalization: Estimate p(xk|yk) and choose those state with the highest probability

Straight Forward Method: calculate p(xk|yk) for every state

Effort to high for practical systems

Page 7: Michael Lunglmayr Particle Filters for Equalization Page 1 Infineon A FEASIBILITY STUDY: PARTICLE FILTERS FOR MOBILE STATION RECEIVERS CSNDSP 2006 Michael

Michael LunglmayrParticle Filters for EqualizationPage 7

Particle Filters

Connection to Equalization: Estimate p(xk|yk) and choose those state with the highest probability

Straight Forward Method: calculate p(xk|yk) for every state

Effort to high for practical systems

Importance Sampling:Principle: If p(xk|yk) would be known, it could be sampled:

Particles:

then for N:

Page 8: Michael Lunglmayr Particle Filters for Equalization Page 1 Infineon A FEASIBILITY STUDY: PARTICLE FILTERS FOR MOBILE STATION RECEIVERS CSNDSP 2006 Michael

Michael LunglmayrParticle Filters for EqualizationPage 8

Particle Filters

Bad News: p(xk|yk) is not known because it is to be estimated!

But: If we can sample a different probability function:q(xk|xk-1,yk) (importance sampling function) and weight the particles with an importance weight:

Page 9: Michael Lunglmayr Particle Filters for Equalization Page 1 Infineon A FEASIBILITY STUDY: PARTICLE FILTERS FOR MOBILE STATION RECEIVERS CSNDSP 2006 Michael

Michael LunglmayrParticle Filters for EqualizationPage 9

Particle Filters

Bad News: p(xk|yk) is not known because it is to be estimated!

But: If we can sample a different probability function:q(xk|xk-1,yk) (importance sampling function) and weight the particles with an importance weight:

Example: q(xk|xk-1,yk) = p(xk|xk-1)

Page 10: Michael Lunglmayr Particle Filters for Equalization Page 1 Infineon A FEASIBILITY STUDY: PARTICLE FILTERS FOR MOBILE STATION RECEIVERS CSNDSP 2006 Michael

Michael LunglmayrParticle Filters for EqualizationPage 10

PF for Equalization

Probability functions for GSM/EDGE

Page 11: Michael Lunglmayr Particle Filters for Equalization Page 1 Infineon A FEASIBILITY STUDY: PARTICLE FILTERS FOR MOBILE STATION RECEIVERS CSNDSP 2006 Michael

Michael LunglmayrParticle Filters for EqualizationPage 11

PF for Equalization

Probability functions for GSM/EDGE

Until now: Sequential Importance Sampling (SIS)But not very efficient yet!

Page 12: Michael Lunglmayr Particle Filters for Equalization Page 1 Infineon A FEASIBILITY STUDY: PARTICLE FILTERS FOR MOBILE STATION RECEIVERS CSNDSP 2006 Michael

Michael LunglmayrParticle Filters for EqualizationPage 12

Resampling

Page 13: Michael Lunglmayr Particle Filters for Equalization Page 1 Infineon A FEASIBILITY STUDY: PARTICLE FILTERS FOR MOBILE STATION RECEIVERS CSNDSP 2006 Michael

Michael LunglmayrParticle Filters for EqualizationPage 13

Particle Filter Algorithm

Page 14: Michael Lunglmayr Particle Filters for Equalization Page 1 Infineon A FEASIBILITY STUDY: PARTICLE FILTERS FOR MOBILE STATION RECEIVERS CSNDSP 2006 Michael

Michael LunglmayrParticle Filters for EqualizationPage 14

Implementation

Page 15: Michael Lunglmayr Particle Filters for Equalization Page 1 Infineon A FEASIBILITY STUDY: PARTICLE FILTERS FOR MOBILE STATION RECEIVERS CSNDSP 2006 Michael

Michael LunglmayrParticle Filters for EqualizationPage 15

Simulation ResultsGMSK

Page 16: Michael Lunglmayr Particle Filters for Equalization Page 1 Infineon A FEASIBILITY STUDY: PARTICLE FILTERS FOR MOBILE STATION RECEIVERS CSNDSP 2006 Michael

Michael LunglmayrParticle Filters for EqualizationPage 16

Simulation Results

Page 17: Michael Lunglmayr Particle Filters for Equalization Page 1 Infineon A FEASIBILITY STUDY: PARTICLE FILTERS FOR MOBILE STATION RECEIVERS CSNDSP 2006 Michael

Michael LunglmayrParticle Filters for EqualizationPage 17

Conclusion

Particle Filters can outperform existing algorithms

Disadvantage: computational complexity

But: complexity depends only linearly on channel length e.g. Promising use in extremely broadband communication systems with long impulse responses