ICI Mitigation for Pilot-Aided OFDM Mobile Systems
Download
1 / 34

老師:高永安 學生:蔡育修 - PowerPoint PPT Presentation


  • 88 Views
  • Uploaded on

ICI Mitigation for Pilot-Aided OFDM Mobile Systems Yasamin Mostofi, Member, IEEE and Donald C. Cox, Fellow, IEEE IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS, VOL. 4, NO.2, MARCH 2005. 老師:高永安 學生:蔡育修. Outline. Introduction System model Piece-Wise Linear Approximation Method I

loader
I am the owner, or an agent authorized to act on behalf of the owner, of the copyrighted work described.
capcha
Download Presentation

PowerPoint Slideshow about ' 老師:高永安 學生:蔡育修' - keane-garrison


An Image/Link below is provided (as is) to download presentation

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.


- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -
Presentation Transcript

ICI Mitigation for Pilot-Aided OFDM Mobile SystemsYasamin Mostofi, Member, IEEE and Donald C. Cox, Fellow, IEEEIEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS, VOL. 4, NO.2, MARCH 2005

老師:高永安

學生:蔡育修


Outline
Outline

  • Introduction

  • System model

  • Piece-Wise Linear Approximation

    Method I

    Method II

  • Mathematical Analysis and Simulation Result

  • Noise/Interference Reduction

  • Simulation Results and Conclusion


Introduction
Introduction

  • Transmission in a mobile communication environment is impaired by both delay and Doppler spread.

  • As delay spread increases, symbol duration should also increase.

    reasons---1.near-constant channel in each frequency subband. 2.prevent ISI.

  • OFDM system become more susceptible to time-variations as symbol length increases. Time-variations introduce ICI. be mitigated to improve the performance.


  • We introduce two new methods to mitigate ICI. Both methods use a piece-wise linear model to approximate channel time-variations.






Pilot extraction

An estimate of Hi,0 can then be acquired at pilot:

Pilot Extraction



Piece wise linear approximation
Piece-Wise Linear Approximation to estimate the channel.

  • We approximate channel time-variations with a piece-wise linear model with a constant slope over the time duration T.


For normalized Doppler of up to 20%, linear approxi- to estimate the channel.

mation is a good estimate of channel time-variations.

We will derive the frequency domain relationship.

Therefore, we approximate


Then, to estimate the channel.

we will have


Futhermore, to estimate the channel.


An FFT of y to estimate the channel.:


  • To solve for X, both H to estimate the channel.mid and Hslope should be estimated.

  • Matrix C is fixed matrix and Hmid is readily available.

  • So we show how to estimate Hslope with our two methods.


Method i ici mitigation using cyclic prefix

The output prefix vector to estimate the channel.

Method I:ICI Mitigation Using Cyclic Prefix


Then, to estimate the channel.



Method ii ici mitigation utilizing adjacent symbols
Method II for X.:ICI Mitigation Utilizing Adjacent Symbols

  • This can be done by utilizing either the previous symbol

    or both adjacent symbols.

  • A constant slope is assumed over the time duration of

    T+(N/2)*Ts for the former and T for the latter.






Mathematical analysis and simulation result
Mathematical Analysis and Simulation Result for X.

  • We define SIRave as the ratio of average signal power

    to the average interference power.

  • Our goal is to calculate SIRave when ICI is mitigated and

    compare it to the that of the “no mitigation” case.


Noise interference reduction

Estimated channel taps are compared with a for X.Threshold.

Let MAV represent the tap with maximum absolute value.

All the estimated taps with absolute values smaller than

MAV/γ for some γ>=1 will be zeros.

Noise/Interference Reduction


Simulation results
Simulation Results for X.

  • System parameters






Conclusion
Conclusion for X.

  • Both methods used a piece-wise linear approximation to

    estimate channel time-variations in each OFDM symbol.

  • These methods would reduce average Pb or the required

    received SNR to a value close to that of the case with no

    Doppler.

  • The power savings become considerable as fd,norm incre-

    ases.