doppler spread estimation in frequency selective rayleigh channels for ofdm systems athanasios...

Doppler Spread Estimation in

Frequency Selective Rayleigh Channels for

OFDM Systems

Athanasios Doukas, Grigorios Kalivas

University of PatrasDepartment of Electrical & Computer Engineering

Applied Electronics Laboratory

Doppler Spread Estimation219/07/2006

Conclusions

Simulation Results

Doppler Spread Estimator

Fading Channel and OFDM System

Introduction

Contents


Introduction

Orthogonal Frequency Division Multiplexing (OFDM) has been widely applied in the last years for various wireless communication systems such as Digital Video Broadcasting (DVB) and wireless local area networks (WLANs) ensuing great success.

These systems however, should be capable of working efficiently in wide range of operating conditions, such as large range of mobile unit (MU) speeds, different carrier frequencies in licensed and un-licensed bands, various delay spreads, and wide dynamic signal to-noise ratio (SNR) ranges.

This way assessing the channel quality and its rate of change is of great importance in adapting the system parameters to continuously changing channel conditions.


Necessity of Doppler Spread Estimation

1

It provides information about the fading rate of the channel. Knowledge of Doppler spread can improve detection and aid into transmission optimization in both physical layer and higher levels.

2

Doppler information can help in selection of appropriate transmission characteristics to combat ICI including proper channel estimators to enhance reception.

3

Specifically designed channel estimators can be applied and the rate of appliance can be chosen to improve throughput and an increase in the estimation rate can help to lower BER.


Switching rate of diversity branches is used for the velocityestimation but its sensitivity to the fading channel is shown.

Another type of estimators are the covariance-based estimators, which estimate the Doppler frequency from the auto- covariance of powers ofthe received signal envelope or from sums of the I/Q components.

Other methods, highly associated to LCR, are the Zero Crossing Rate (ZCR), which uses the in-phase or quadrature phase (I/Q) signal part, and some other higher order crossings of the signal envelope.

Previous Work

4 1

Doppler Estimation

Level Crossing Rate (LCR) of the received signal envelope is proportional to the Doppler frequency and thus used in Doppler estimation. However, the fading nature of the wireless channel decreases the estimator’s accuracy in low Doppler values.

2

3


Doppler Estimator Novelty

Wide Sense Stationary (WSS)Channelwith a few samples

Novel PointsOf Estimator

Low Mobility Of Systems that divide the state of the system in two operational modesa) Movingb) Still


Conclusions

Simulation Results



Introduction

Contents


Wireless Fading Channel (1/4)

)()t(),t(h

)t(r)t(tt)t(r t2*

Channel Impulse Response

where γℓ(t)’s are wide-sense stationary (WSS) narrowband complex Gaussianprocesses, which are independent for different paths.

Correlation Function rτ(Δt)



ƒ2jƒ2j e)t(de),t(h)ƒ,t(H

The frequency response of the time-varyingradio channel at time t is



ƒrtr

etr

e)t(r

)ƒ,t(ƒƒ,ttƒ,tr

ƒt2

ƒ2j2t

ƒ2j

*H

The correlation function of H(t,ƒ) can be separated into the multiplication of a time domain correlation rt(Δt) and a frequency domain correlation rƒ(Δƒ).

rt(Δt) is dependent on the vehicle speed or, equivalently, the Doppler frequency, while rƒ(Δƒ) depends on the multipath delay spread.

With the separation property, we are able to propose our Doppler estimator described in the next section.


]k[r]i[r]k,i[r ƒt

ƒtt iTr]i[r

ƒkr]k[r ƒƒ

]n[rnJ]n[r Jd0t


For an OFDM system with block length Tƒ and tone spacing (subchannel spacing) Δƒ, the correlation function for different blocks and tones can be written as

where

Jake’s Model

Time Correlation

Frequency Correlation


OFDM Physical Layer


1N

0k

N/nk2jk,i

k,in,i

1N,,0neX

}X{IFFTx

1N,,0keyN

1

}y{FFTY1N

0n

N/nk2jn,i

n,ik,i

Transmitted/Received Signal

TransmittedSignal

ReceivedSignal


Conclusions

Simulation Results


Introduction

Contents



1N

0i

*k,ik,i

rt

r

N

1][r

]n[rnJ]n[r Jd0t

Equations Used

Time Correlation

Time Correlation using

Received Data


Doppler Estimation Procedure

Nr=2, ρ=0

Nr=2, ρ=1

Combination of previous results

DopplerDopplerEstimationEstimation

1

2

3


10J0J]0[r 0d0t

1

0i

*k,ik,it

012

0n

*k,0ik,it 2

1]0[r

02

1]0[r

1

Estimation Procedure Step 1/3


dƒ0d0t ƒT2J*1J]1[r

*k,1k,0t

112

0i

*k,1ik,it ]1[r

12

1]1[r

2



1

0i

*k,ik,i

*k,1k,01

0f

d

2

1J

T2

1ƒ

3


Doppler EstimationFormula


Conclusions


Introduction

Contents


Simulation Results


0 5 10 15 20 25 30 35 40 45 500

1

2

3

4

5

6

7

8x 10

-3

Subcarrier Index

Est

imat

ion

Doppler estimation with SNR=5dB in BRAN Channel A for BPSK modulated data

Doppler estimation 0 Hz Doppler estimation 10 HzDoppler estimation 20 HzDoppler estimation 30 HzDoppler estimation 40 Hz

Simulation Results (1/4)


0 5 10 15 20 25 30 35 40 45 500

1

2

3

4

5

6

7

8x 10

-3

Subcarrier Index

Est

imat

ion

Doppler estimation with SNR=5dB in BRAN Channel A for BPSK modulated data



0 5 10 15 20 25 30 35 40 45 500

1

2

3

4

5

6

7

8x 10

-3

Subcarrier Index

Es

tim

ati

on

Doppler estimation with SNR=10 dB in BRAN Channel A for BPSK modulated data



0 5 10 15 20 25 30 35 40 45 505

5.5

6

6.5

7

7.5x 10

-3

Subcarrier Index

Estim

atio

n

Doppler estimation with SNR=10dB in BRAN Channel A for QPSK modulated data



0 5 10 15 20 25 30 35 40 45 505

5.5

6

6.5

7

7.5x 10

-3

Subcarrier Index

Es

tim

ati

on

Doppler estimation with SNR=10dB in BRAN Channel A for QPSK modulated data



0 5 10 15 20 25 30 35 40 45 500

1

2

3

4

5

6

7

8x 10

-3

Subcarrier Index

Est

imat

ion

Doppler estimation with SNR=10dB in BRAN Channel B for BPSK modulated data



0 5 10 15 20 25 30 35 40 45 500

1

2

3

4

5

6

7

8x 10

-3

Subcarrier Index

Es

tim

ati

on

Doppler estimation with SNR=10dB in BRAN Channel B for BPSK modulated data



Simulation Results


Introduction

Contents


Conclusions


We have presented a Doppler estimator for low mobility OFDM systems in Frequency Selective Rayleigh Fading Channels, using only two OFDM symbolsfor the time correlation in wireless OFDM systems.

The estimator instead of trying to estimate the accurate value of the Dopplerfrequency divides the mobility into a still and a moving mode, which for the case ofWLANs is the most important. We have examined its performance in wirelesschannels with different power delay profiles, including sparse channels.

The estimator, in most of the cases, manages to clearly distinguish the two modesof mobility, still or moving.

Conclusions

doppler spread estimation in frequency selective rayleigh channels for ofdm systems athanasios...

Documents

doppler frequency

knowledge of doppler

doppler information

estimation rate

wireless channel

low doppler values

wireless fading channel

velocity estimation