 Open Access
 Total Downloads : 474
 Authors : Ankit Emmenual Ram, Anil Kumar, Arvind Kumar Jaiswal
 Paper ID : IJERTV2IS50355
 Volume & Issue : Volume 02, Issue 05 (May 2013)
 Published (First Online): 27052013
 ISSN (Online) : 22780181
 Publisher Name : IJERT
 License: This work is licensed under a Creative Commons Attribution 4.0 International License
DWT Image Transmission By OFDM System With Adequate Energy Saving
Ankit Emmenual Ram, Anil Kumar, Arvind Kumar Jaiswal
ECE Department SHIATSDU Allahabad India 211007
Abstract
Resending of lost packets is not allowed in the field of communication as far as many applications are considered. Only some of the subset of carrier fulfils the criteria of data transmission. The data having least importance can be discarded at the receiver itself so that only good subcarriers can be transmitted over the channel, if the channel state information is available at the transmitter itself. In this paper, we present a system model which transmits any compressed image using DWT Image transmission by OFDM channels using QAM with an approach to save adequate energy. To achieve this bad subchannels are discarded at the transmitter itself with a usefulness of the proposed scheme in terms of peak signalnoise ratio.

Introduction
In communication, intersymbol interference (ISI) and frequency selective fading nature of the channel is a form of a distortion of a signal in which high rate data communication are significantly limited. Example of such channel is Rayleigh fading channel. Multicarrier modulation (MCM) is a method of transmitting data by splitting it into several components, and sending each of these components over separate carrier signals which appease the effect of ISI. Orthogonal frequency division multiplexing (OFDM) is a special case of multicarrier transmission, where a single data stream is transmitted over a number of lower rate subcarriers which allows overlapping in frequency domain. A large number of closely spaced orthogonal subcarrier signals are used to carry data on several parallel data streams or channels. Each subcarrier is modulated with a conventional modulation scheme (such as quadrature amplitude modulation or phaseshift keying) at a low symbol rate, maintaining total data rates similar to conventional singlecarrier modulation schemes in the same bandwidth..
The three types of source coding which are being used in the world of transmission are non progressive coding, progressive coding and multiple description coding.
Layered coding is performed in Stateoftheart image or video compression techniques, such as
JPEG2000 [1] (which uses Discrete Wavelet Transform DWT). In this technique, the base layer is sent first and then enhancement layers are added if the bandwidth is available. The Layers which gets lost are retransmitted to complete the processing at the receiver. This process introduces inactivity, thereby restricting the performance of the system. Layered coding produces data of unequal importance and hence special protection should be provided for important data. Scalability property of the layered coding approach allows that a fewer layers can be transmitted to reconstruct the image frame of an acceptable quality. However those layers should be received perfectly, which leads to the need for retransmissions. Thus, although progressive coding works well in lossless system, but if errors are generated during reconstruction, the image can be hampered due to resending of lost coefficients.
To avoid the above mentioned technique MDC [2] is used for the applications which do not allow inactivity in the reception. MDC is source coding for multiple channels that a decoder which receives an arbitrary subset of the channels may produce a useful reconstruction. MDC always outperforms in delay sensitive applications [3]. MDC gives a chance to evaluate the lost information from the correctly received data without retransmission Since MDC distributes the importance equally among all the coefficients; it works against its recovery quality when CSI is known. It can be explained by the fact that, for a limited correlation among the descriptions produced by MDC, the distortion for even one description loss is more than the minimum variance of the input data streams [4]. So, not to unnecessarily increase complexity by using MDC, the DWT compressed data can be directly transmitted over the errorprone subchannels leading to more important coefficients are protected from likely losses in the transmission process. In this paper, we propose a energy saving approach, where the compressed coefficients are arranged in descending order of priority and mapped over the channels starting with the good ones. The coefficients with lower importance level, which are likely mapped over the bad channels, are discarded at the transmitter
to save power without significant loss of reception quality.
The paper is organized as follows. Section II gives the DWTOFDM system model, followed by the proposed scheme. The analysis of distortion and energy saving is given in SECTION III. Simulation and analytical results are shown in Section IV. Finally the paper is concluded in Section V.

DWTOFDM System Model
The OFDM implemented by using IFFTs and FFTs have some problems. Due to these problems we need to look at other type of modulation to generate the carrier. One of these is the wavelet transform. The wavelet transform is proposed by many authors, it has a higher degree of side lobe suppression and the loss of orthogonality leads to lesser ISI and ICI. In Wavelet OFDM the FFT and IFFT is replace by DWT and IDWT respectively. For the Wavelet transform we see that from the timefrequency plot that the basic Wavelet transform offers lesser flexibility than the wavelet packet transform. For the wavelet packet transform we can construct an algorithm to do the decomposition such that the effect due
to the noise (assuming that we know the frequency that is affected most by the noise and the time when it affected most).
An OFDM transreceiver is shown in Figure 1[5]. The data generator used is a sine wave of bit stream d. It is processed using Mary modulator to map the input data into symbols Xm. These symbols are now sent through IDWT block to perform IDWT operation to generate N parallel data streams. Its output in discrete time domain is given by,
is passed through AWGN channel with proper input power set. At the receiver, the reverse operation is done to obtain the original data back. The CP is removed and processed in the DWT block and finally passed through demodulator for data recovery.
In our proposed model, an image frame is compressed using DWT, and the compressed data is arranged in data vectors, each with equal number of coefficients. These vectors are quantized and binary coded to get the bit steams, which are then packetized and intelligently mapped to the OFDM system, such that poorer subchannels can only affect the lesser important data vectors. We consider only onebit channel state information available at the transmitter, informing only about the subchannels to be good or
bad. For a good subchannel, instantaneous received power should be greater than a threshold Pth. Otherwise; subchannel is in fading state and considered
bad for that batch of coefficients. Note that the data transmitted through deeply faded subchannels are highly sensitive to error and are likely to be discarded at the receiver. Thus, the binary channel state information gives an opportunity to map the bit streams intelligently and to save a reasonable amount of power. The brief explanation of model is under:
At first DWT is applied to any original image whether gray or coloured of size A Ã— B pixels leading to four subimages denoted as HL, LH, HH, and LL, each of the size (A/2)Ã—(B/2) pixels, from these sub images four coefficient vectors are generated, each of length (A.B)/2. Post tis step uniform quantization of the coefficient vectors is done which are binary coded with L bits/coefficients to form four bit streams. These bit streams are packetized and traced on the OFDM system.
Input Image
Input Image
DWT
(1)
Serialization of Coefficients
Data Gen.
Data Gen.
QAM
Mod.
QAM
Mod.
DWT/ IFFT
DWT/ IFFT
d Xm Xk
Data Gen.
Data Gen.
QAM
Mod.
QAM
Mod.
DWT/ FFT
DWT/ FFT
+ Cyclic Prefix
+ Cyclic Prefix
dÂ´ Um Uk
DAC
+ Cyclic Prefix
+ Cyclic Prefix
AWGN
Channel
n(t)
Cipher value
Rayleigh fading channel
Rayleigh fading channel
ADC
ADC
AWGN
AWGN
Receiver
Receiver
Serialization
Compressed Four
Sub Images
Compressed Four
Sub Images
Quantization & Binary Coding With
L Bits/Coeff.
Quantization & Binary Coding With
L Bits/Coeff.
Packetization
IFFT
QAM
IFFT
QAM
Figure 1. An OFDM transceiver of FFT/ DWT OFDM
The transformed output (Xk) is now appended with cyclic prefix. The cyclic prefix (CP) is added before transmission, to mitigate ISI effect. It is usually 25% of the last part of the original OFDM symbol and this data
Figure 2. Proposed Model for DWTOFDM
According to Figure 2, bit streams are packetized by chopping them into bit vectors of size NÂ´ bits. Four such vectors are contained in a packet. Cipher Bits are added to each vector to estimate the SNR of the
subchannels at the receiver[7].The system is described by arranging 32 packets in parallel to get 128 bit streams making them mary modulated and being simultaneously transmitted via different subchannel set. Here only the feedback comes into role which takes the condition of selecting good or bad data with the help of a predefined threshold Pth and accordingly draft them to IFFT. We propose an outline which is adequate in terms of quality reception as well as energy saving. Packets are send via frequency selective, slow varying fading channel. Viceversa is done at receiver with suitable measures due to bad vectors.
In this study we use block fading channel model as in [8]. All subbands are independently faded with Rayleighdistributed envelop, which corresponds to the block fading approximation in frequency domain [9], [10].

Arithmetic and Simulation Result

Distortion involved for various loss events
As the proposed scheme gives an opportunity to reduce the distortion as much as possible for a given channel condition; only a few loss events can take place. Let x1, x2, x3, and x4 are the data vectors corresponding to the four subimages obtained from
original frame using DWT compression. Also, let 2 ,
(3)
Then, the average distortion of the proposed scheme can be written as:
(4)

Energy saving measure:
In the proposed scheme the less important data vectors are discarded at the transmitter to save power if corresponding subchannel is in fading state. Denoting the percentage of data not transmitted in a packet as a measure of the percentage of energy saving, using (3) we can write energy saving expression as:
(5)
Simulations are carried out in Matlab to validate the proposed schemes. In our proposed scheme we can use any image for transmission but here we have used the coloured image of baboon. We simulated the OFDM
2 , 2 and 2
x1
are the respective variances. Without
system with 128 subcarriers. In this way, 32 packets
x2 x3 x4
x1
x1
any loss, assume that the variances 2
to 2
are in
can be transmitted simultaneously through the OFDM
x4
x4
descending order of magnitude. Thus, the corresponding importance levels are also in descending order. These data vectors are drafted over different subchannels in such a way that only a few specific loss events are possible. The corresponding likelihood of loss events would be: only x4 is lost; x3 and x4 are lost; x2, x3, and x4 are lost; and all x1, x2, x3, and x4 are lost. Thus, according to our mapping strategy only four combinations of the loss events are possible and each individual distortion can be calculated as:
system. The modulation scheme used for the transmission can be any one from the two i.e. QPSK or QAM but here we have taken QAM for simulation purpose. This Modulation scheme gives the best of its results when it comes to the transmission of data. The results are as follows:
results for distortion and power saved
Power saving
Distortion
Power saving
Distortion
40
35
MSE distortion in dB—–
MSE distortion in dB—–
30
25
20
15
(2) 10

Block fading channel behavior:
The performance of the proposed scheme depends on probability of the loss events. In this section, the probabilities of loss events are determined with respect to the channel fading parameter. In our interleaved coefficient mapping scheme, all the four subchannels per group of four coefficients are from different sub bands. Thus, p will also be the probability of a subchannel to be bad. Let Pi = probability associated with the loss event i, for i = 0, 1, 2, 3, 4, which produces distortion Di. Thus, for an arbitrary received packet we can write:
5
0
0 2 4 6 8 10 12
Fading margin in dB—–
Figure 3. Distortion and power saved
0
10
Conditional Distortion Di(dB)
Conditional Distortion Di(dB)
20
30
40
Conditional distortions for Rx image
50
60
70
80
90
1 1.5 2 2.5 3 3.5 4 4.5 5
Number of Data vectors recieved(i)

Original Image (b) PSNR = 19

Figure 4. Conditional Distortion for Rx Image
Tradeoff between energy savings and reception
40
35
30
25
SNR=20 SNR=15
(c) PSNR = 26 (d) PSNR = 36
Figure 6. Transmitted aboon Image and its received counterpart at different PSNRs.
PSNR (dB)
PSNR (dB)
20
15
10
5
0
0 5 10 15
Power threshold Pth(dB)
Figure 5. Tradeoff between energy savings
and reception
To show the effect of fading we have not considered Gaussian Noise in our analysis and simulation. From Figure 3, it is noted that the distortion depends on the threshold value Pth and on transmitting the image of coloured baboon a adequate amount of energy of about 65 percent is saved.
Transmission through OFDM shows PSNR and energy saving quality in Figure 5, which also include the effect of AWGN. The figure also gives the optimal value of Pth about 8 dB. For lower values of Pth AWGN dominates, producing a higher distortion even if the coefficients are accepted at the receiver due to a low Pth. Therefore for higher values of Pth, i.e., at Pth > 8 dB, the effect of AWGN diminishes. But, as more subchannels are considered in fading state the quality suffers while providing a higher energy saving.
It should be noted that we halt the transmission depending upon instantaneous received power if the subchannels, and a decision is made based on the value Pth. Thus, the amount of power saved and the corresponding degradation in quality for a higher Pth can be controlled. The received baboon image at different PSNR is shown in figure.


Conclusion
Reducing distortion in transmission of data is at top priority. So, in this paper an efficient scheme is proposed in which the coefficients with lower importance are discarded at the transmitter itself leading to saving of power without much loss in reception quality.
As a future work, the current study can be extended to adaptive modulation and moderating the scheme for video transmission as well.

References

Athanassios Skodras, Charilaos Christopoulos, and Touradj Ebrahimi The JPEG 2000 Still Image Compression Standard, IEEE Signal Processing Magazine, Sep. 2001.

R. Puri and K. Ramchandran, Multiple description source coding through forward error correction codes, IEEE Proceedings Asilomar Conference on Signals, Systems, and Computers, Asilomar, CA, October, 1999.

J. Chakareski, S. Han, and B. Girod, Layered Coding vs. Multiple Descriptions for VideoStreaming over Multiple Paths, ACM, November 2.8, 2003.

V. K. Goyal and J. Kovacevic, Optimal multiple description transform coding of Gaussian vectors, in Proc.
IEEE data Compression Conf., Snowbird, UT, Mar. 1998, pp. 388397.

Khaizuran Abdullah and Zahir M. Hussain, Studies on DWTOFDM and FFTOFDM Systems, International Conference on Communication, Computer And Power (Icccp09) Muscat, February 1518, 2009.

Ye Geoffrey Li, Gordon L. Stuber, Orthogonal frequency division multiplexing for Wireless Communications, Amazon, 2006.

Y. Li, Pilotsymbolaided channel estimation for OFDM in wireless systems, IEEE Trans. Veh. Techn., vol. 49, no. 4, pp. 1207215, June 2000.

Y. S. Chan, P. C. Cosman, and L. B. Milstein, A cross layer diversity technique for multicarrier OFDM multimedia networks, IEEE Trans. Image Proc., vol. 15, no. 4, pp. 833 847, Apr. 2006.

R. J. McEliece and W. E. Stark, Channels with block interference, IEEE Trans. info. Theory, vol. 30, no. 1, pp. 4453, Jan. 1984.

R. Knopp and P. A. Humblet, On coding for block fading channels, IEEE Trans. info. Theory, vol. 46, no. 1, pp. 189205,Jan.2000.