Fuzzy Applications in Wireless Communication

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FUZZY APPLICATIONS IN WIRELESS COMMUNICATION

Trisha Chowdhury

M.E(cst), 1 st year

Bengal Engineering & Science University


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CONTENTS IntroductionAbout wireless communicationChannel Estimation

Channel EqualizationDecodingUsefulnessFuture workConclusionReferenceQuestions


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INTRODUCTION

Fuzzy Logic has been successfully applied invarious areas pertaining to wirelesscommunication systems. As fuzzy logic is used tomodel systems and situations, taking intoconsideration uncertainty and ambiguity, it can bean efficient tool to be utilized in problems for which knowledge of all factors is insufficient or impossible to obtain.

In this presentation we will focus on fuzzylogic applications in channel estimation, channelequalization and decoding.


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WIRELESS COMMUNICATION

Wireless communications is a rapidly evolvingindustry, constantly challenging researchers for newtechniques in order to meet the demands of ever higher performance and efficiency.

In a wireless communication system, the channel isthe medium by which information-bearing signalsare transferred.

The wireless channel poses tough challenges for achieving reliable and fast transfers.


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CONTD. When there is no line-of-sight between the

transmitter and the receiver, distortions to the signalwill follow, all of them resulting in a phenomenoncalled Multipath Propagation.

The aim of the receiver in the communication systemis to overcome the disturbances of the channel, inter symbol interference and noise, and correctly decodethe data having been transmitted.

In this area that fuzzy techniques find their mainuses.


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CHANNEL ESTIMATION

Channel estimation is performed by tracking thechannel coefficients, applying a fuzzy trackingmethod in a Code Division Multiple Access (CDMA)channel.

The motivation for using fuzzy channel estimation isdue to fuzzy estimation not needing exact processmodels. Comparisons are made between the fuzzytracker and a non-fuzzy tracker.Channel estimation using a fuzzy approach has also

been performed with a multi-carrier modulationtechnique called Orthogonal Frequency DivisionMultiplexing (OFDM).


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CONTD Equation for calculating channel estimation:-

Channel Estimation

Takagi- Sugeno-Kang (TSK) model is used for thechannel estimation in an OFDM system. The TSKmethod is similar to that of the traditional Mamdanimethod.

Later the TSK fuzzy modeling technique has beenupdated for a multiple-input multiple-output (MIMO)OFDM system which is now a highly popular researchtopic.

1,...,1,0 N k k H

k Y k X

e

e

Estimated Channel


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CHANNEL EQUALIZATION

Channel equalization is theprocess of removing thedegradation caused by thechannel with the aim of reconstructing the transmitted

data.

Fuzzy adaptive filters areconstructed and applied tochannel equalization.

The objective of using fuzzyadaptive filters is to improve thebit error rates of the fuzzy

equalizer.


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CONTD

Adaptive filter

System design for channel Equalization.

A further development of the fuzzy adaptive filters ispresented: the type-2 fuzzy adaptive filter, which based onthe TSK fuzzy logic system.

Transmitter

filter Channelmedium

Receiver filter

FuzzyEqualizer


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DECODING

In contrast to conventional communication systemswhere encoding/decoding and channel equalizationare performed separately, fuzzy equalizationschemes combine the two mechanisms.

The fuzzy turbo equalizer is introduced with themotivation that fuzzy filters could deal withuncertainty characterized by impulse noise, and also

has lower computational complexity.

To adapt the parameters of the fuzzy equalizer, theback-propagation algorithm is used.


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USEFULNESS

Fuzzy applications is very much useful in modelingthe problems in which all the inputs are not known or are impossible to obtain.

Reduction in complexity and robustness can beachieved by the use of fuzzy logic.

When dealing with complex models that are notcompletely known and varying with time, fuzzy logicbased methods can be used for faster convergence.

It is helpful in case of non-linear mechanism.


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FUTURE WORK

Building on the study we have presented here,there are a few areas that we can consider as afurther attention.

These are:Fuzzy adaptive equalization techniques.

Fuzzy power control in OFDM systems.


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CONCLUSIONS

Conclusions that can be drawn from using fuzzy logicbased methods are:-Fuzzy logic based methods particularly perform wellunder non-linear and time-variant conditions, where

adaptive techniques have to be employed.It reduced complexity with a slight degradation inperformance compared to that of standard methods.When human expert knowledge is available, a fuzzy

approach is highly suitable to incorporate thisknowledge to complement available numerical data.


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REFERENCES

Fuzzy Logic Applications in WirelessCommunications by Maria Erman1,AbbasMohammed, Elisabeth Rakus-Andersson. http://seminarprojects.com/Thread-fuzzy-logic-applications-in-wireless-communications#ixzz2Phzuw6Da Channel Estimation in OFDM Systems by Zhibin Wu,Yan Liu, Xiangpeng Jing.http://en.wikipedia.org/wiki/Multipath_propagation
http://seminarprojects.com/Thread-fuzzy-logic-applications-in-wireless-communicationshttp://seminarprojects.com/Thread-fuzzy-logic-applications-in-wireless-communicationshttp://seminarprojects.com/Thread-fuzzy-logic-applications-in-wireless-communicationshttp://en.wikipedia.org/wiki/Multipath_propagationhttp://en.wikipedia.org/wiki/Multipath_propagationhttp://seminarprojects.com/Thread-fuzzy-logic-applications-in-wireless-communicationshttp://seminarprojects.com/Thread-fuzzy-logic-applications-in-wireless-communicationshttp://seminarprojects.com/Thread-fuzzy-logic-applications-in-wireless-communicationshttp://seminarprojects.com/Thread-fuzzy-logic-applications-in-wireless-communicationshttp://seminarprojects.com/Thread-fuzzy-logic-applications-in-wireless-communicationshttp://seminarprojects.com/Thread-fuzzy-logic-applications-in-wireless-communicationshttp://seminarprojects.com/Thread-fuzzy-logic-applications-in-wireless-communicationshttp://seminarprojects.com/Thread-fuzzy-logic-applications-in-wireless-communicationshttp://seminarprojects.com/Thread-fuzzy-logic-applications-in-wireless-communicationshttp://seminarprojects.com/Thread-fuzzy-logic-applications-in-wireless-communicationshttp://seminarprojects.com/Thread-fuzzy-logic-applications-in-wireless-communicationshttp://seminarprojects.com/Thread-fuzzy-logic-applications-in-wireless-communicationshttp://seminarprojects.com/Thread-fuzzy-logic-applications-in-wireless-communications


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Fuzzy Applications in Wireless Communication