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Cyclic Short-Time Varying Channel

Estimation in

OFDM Power-Line Communication

Gopu.T.A

Rollno:18

S7 CSE

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CONTENTS INTRODUCTION

OFDM COMMUNICATION SYSTEM

PROPOSED NONLINEAR DECISION-DIRECTED

ESTIMATION APPROACH LINEAR PILOT AIDED METHOD

OFDM TRANSMISSION OVER A TIME VARYING

CHANNEL

CONCLUSION

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INTRODUCTION POWER-LINE communications (PLC) is the one of the

most promising technologies to provide competitivetechniques for numerous in home communication

applications, such as fast Internet access, home

automation, and telephone service..

The widely varying unstable channel characteristics

of a home power-line network that results from the

direct coupling of the home appliances to the

network.

The time-varying behavior of indoor power-line

channels is substantially produced by two causes.

The first one is the connection and disconnection of

electrical devices at the sockets ,long term veriation.

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The other one is related to the nonlinear behavior of

some electrical devices with respect to the mains

voltage, short-time variation. An orthogonal frequency-division multiplexing

(OFDM)-based system has been make considerable

interest in PLC & wireless communication.

Its main advantages in high-bit-rate transmissions overfrequency-selective and time-variant channels.

Loss of the orthogonality between the subchannels is a

great problem for OFDM.

A blind, decision-directed estimation procedure isdesired to continuously follow the channel alterations. A

number of decision-directed estimation techniques have

been proposed for wireless OFDM system..

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In this paper, we propose an adaptive estimation-

equalization method and the focus is put on tracking

the short-time variation of the channel. Nonlinear behavior at high frequencies is not

commonly considered, although a high power

amplifier can introduce amplitude and phase-

dependent non linearities.

Therefore, we have included the presence of high-

frequency nonlinearities, developing a method for

nonlinear equalization.

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OFDM COMMUNICATION SYSTEM

OFDM is a multicarrier communication system where

the modulation and the demodulation are

implemented by using the inverse fast Fourier

transform (IFFT) and the FFT, respectively.

The input data stream is divided into many symbolsdrawnfrom a quadrature amplitude modulation

(QAM) constellation and placed in the frequency

domain on a number of orthogonal subcarriers.

The array of subchannel symbols is transformed intoa baseband time-domain signal by an IFFT operation.

The signal is extended cyclically to form an OFDM

frame.

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This cyclic extension is called the cyclic prefix and

is inserted by the transmitter in order to remove the

intersymbol interference(ISI) and interchannelinterference (ICI) that would otherwise cause

degradation of system performance.

The received signal is obtained by a convolution of

the transmitted signal.The number of subcarriers isdesigned in order so that each subchannel will have a

narrow bandwidth, and we can approximately say

that the fading on each subchannel is flat.

In PLC, this hypothesis is critical because of the

strong fading characteristics of the channel.

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This problem, together with the loss of

orthogonality caused by imperfect frequency

synchronization and by time-variations in thechannel, is the main reason for investigating better

estimation and equalization methods for OFDM..

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PROPOSED NONLINEAR DECISION-

DIRECTED

ESTIMATION APPROACH

The transmitted data symbols on each subcarrierare received with a scaling of amplitude and a phase

rotation given by the channel. After the FFT in the receiver, we have,Rn=SnHn+Dn.

Rn=received value at the nth subchannel.

Hn=channel complex gain at the frequency of thenth subcarrier.

Dn=complex additive noise produced by a mixtureof Gaussian and impulsive noise.

Sn= transmitted symbol at subcarrier.

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Under this hypothesis, after several OFDM frames

are transmitted.

Considering a stationary channel, the received values

at a fixed subcarrier are disposed in the complex

plane in four clusters ideally centered.

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We propose independently tracking these four clusters

presenting the received Symbol Rn to a competitive

neural network with four neurons. Thus, for each subcarrier, we have a distinct

competitive network with four neurons.

When the symbol Rn is presented to the network, the

neuron with the minimum Euclidean distance from Rnis selected.

From this nonlinearities and disturbances can be

calculated

In this manner, the equalization decision task is

completed.

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LINEAR PILOT AIDED METHOD

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Consider the topology of PLC n/w of non linear devices.

Every link is a transmission line of length di

represented by 2X2 ABCD matrices.

We can derive the transfer function from TX to RX usingABCD matrices and considering time-variant loads.

Additive noise is the receiver is a mixture of background

Gaussian noise and impulsive noise. By this formula based calculations give the channel

variation results

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OFDM TRANSMISSION OVER A TIME

VARYING CHANNEL

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Figure shows the corresponding range of variation of

the channel frequency response from the transmitter

TX to the receiver RX. We consider that the channel is stationary during

the transmission of a single OFDM frame, and that it

changes in a continuous fashion between two

successive frames.

For each OFDM frame, a new channel response is

generated. After a complete period of 50 Hz, the

channel frequency response has changed within a

family of curves that covers the whole strip between

the higher and the lower envelopes

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The performances of the NDDE and the linear

method are similar for low signal-to-noise ratios

(SNRs), while for an SNR greater than 10 dB, NDDEout performs the linear method with BER results that

are better of an order of magnitude.

This is probably due to the fact that at low SNR, the

error is dominated by the Gaussian-impulsive noise,whereas for higher SNR, bit errors are caused by the

channel cyclic variation

Thus, we observe that the NDDE can track the cyclic

short-time variation of the channel with better BER

than the standard pilot-aided method.

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CONCLUSION

In this paper, a new adaptive identification method

has been proposed for blind power-line channel

estimation and equalization for OFDM transmission

systems.

The salient feature of the proposed method is to

enable accurate estimation and tracking of the

channel frequency response in the presence of

nonlinearities and periodically time-variant power-line channels

IT show that the proposed non linear method

provides better BER results than the linear pilot-

aided method.

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REFERENCES

S. B. Weinstein and P. M. Ebert, Data transmission by

frequency-division multiplexing using the discrete Fourier

transform, IEEE Trans. Commun., vol. COMM-19, no. 5, pt. 1,

pp. 628634, Oct. 1971.

M. Zimmermann and K. Dostert, A multipath model for thepowerline channel, IEEE Trans. Commun., vol. 50, no. 4, pp.

553559, Apr. 2002.

L. J. Cimini, Jr., Analysis and simulation of a digital mobile

channel using orthogonal frequency division multiplexing,IEEE Trans. Commun., vol. COMM-33, no. 7, pp. 665675, Jul.

1985.

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