Performance Evaluation of Image Transmission over MC-CDMA System using two Interleaving Schemes Shikha Jindal1, Diwakar Agarwal2 Department of Electronics & Communication Engineering G.L.A. University Mathura, India 1 [email protected], [email protected] Abstract - In the present time, there is a rapid increase in demand for faster and reliable transmission of multimedia data through wireless channels. When multimedia data specially an image is to be transferred through the wireless channel, image is highly degraded due to wireless channel errors such as fading, interference and bursty errors. Multi-Carrier Code Division Multiple Access (MC-CDMA) technique is considered as the most promising technique for efficient wireless data transmission. This paper presents the performance comparison of image transmission over MC-CDMA system with two interleaving techniques; Helical interleaving and chaotic interleaving. At the receiver, Linear Minimum Mean Square Error (LMMSE) equalization is employed. System performance is measured through Peak Signal-to-Noise Ratio (PSNR) and Root Mean square Error (RMSE) values. From results, it has been evaluated that MC-CDMA system having chaotic interleaving and LMMSE performs better instead of having helical interleaving for image transmission over wireless channels. Keywords-Chaotic interleaving; Helical interleaving; LMMSE; MC-CDMA; PSNR; RMSE

I. INTRODUCTION With the fast development in wireless communication techniques along with mobile internet and multimedia services, the demand for high data rate transmission is increased significantly. The reliable transmission of data through wireless channels offer great challenge including fading, interference and multipath propagation [1]. Orthogonal Frequency Division Multiplexing (OFDM) [2] has become an auspicious wireless technique for fulfilling the demand of high-data rate multimedia services through wireless channels. In OFDM, the transmitting high rate data stream is split into multiple numbers of lower rate streams which are transmitted over a number of sub-carriers in parallel. Hence, Symbol duration is increased and the effect of multipath delay spread is decreased. Therefore, each subcarrier will suffer only flat fading and inter-symbol interference (ISI). However, when deep fading occurs in the wireless channels, the amplitude of channel response is highly degraded and corresponding subcarriers will experience high noise interference. It causes degradation in the signal-to noise ratio (SNR) at the receiver and symbols suffer from the excessive burst-errors.

c 978-1-4799-3080-7/14/$31.00 2014 IEEE

As the demand for multi-user communication such as cellular systems is increasing, it is required to have multiple access capability to transmit multiple signals simultaneously through the channel. In recent years, a new transmission technique called Multicarrier Code Division Multiple Access (MC-CDMA) [3, 4] which is the combination of CodeDivision Multiple-Access (CDMA) [5] and Orthogonal Frequency Division Multiplexing (OFDM) has become most promising data transmission scheme in wireless communications. This multicarrier transmission scheme has received great attention because these combined systems possess many desirable properties for high data rate and efficient data transmission over wireless channels. The major advantage of the multicarrier technique is that it needs a lower symbol rate as compared to other transmission techniques. With a multicarrier CDMA system, for N carriers, the whole bandwidth of the system is divided into N subbands hence the symbol rate for each subcarrier can be made low. MC-CDMA technique combines the capabilities of both OFDM and CDMA schemes to provide a communication system which has the advantages of both. This combined scheme has become attractive for broadband communications due to the parallel transmission nature of OFDM technique and has the ability to provide larger capacity and flexibility of resource allocation due to advanced allocation technique of CDMA. Another important property of MC-CDMA is that it is bandwidth efficient [6] due to the use of OFDM. In OFDM, the modulation or demodulation can be performed easily by using IFFT or FFT algorithms respectively [7]. MC-CDMA is a suitable candidate for the downlink of a cellular system because of having high spectral efficiency. As shown in Fig. 1, the basic MC-CDMA signal is generated by a serial combination of OFDM and CDMA. Thus with MC-CDMA, each data bit of a user is transmitted in parallel on multiple independently fading sub-carriers (orthogonal) as in OFDM. Each carrier is modulated by a single spreading code as in CDMA. In an MC-CDMA system, spreading is implemented in the frequency domain and the signals of multiple users are separated in the code domain as in CDMA. The MC-CDMA technique is capable not only to combat the ISI, but also exploit the multipath as well. This paper studies the performance of image transmission over MC-CDMA systems.

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S1

Cos (w1t)

C1 Input data (dn) C2

Cos (w1t)

C1

S2

Cos (w2t)

To wireless channel

From transmitter

Cos (w2t)

Output data

C2

...

... Sn

Cn

Cos (wnt)

(a)

Transmitter

Cos (wnt)

Cn

(b) Receiver

Fig. 1 . General MC-CDMA system model (a) Transmitter (b) Receiver

Data transmissions over wireless channels are error prone due to wireless channel impairments such as fading and interference. When multimedia data, specially an image is to be transmitted through wireless channel it is highly imposed to fading, interference and multipath propagation which increase the probability of errors [1]. Another technique which is being considered in this paper is the data interleaving technique to improve the performance of image transmission system. It is known that transmission of an image over wireless channels may face many detrimental conditions because wireless channel is highly imposed to bursty errors which degrade the quality of image being transmitted. Bursty errors can be defined as a group of successive error bits in the onedimensional (1-D) case or connected error bits in multidimensional (M-D) cases. To transmit data efficiently over wireless channels and combat the effect of these bursty errors interleaving techniques have become essential in wireless communication systems. For reliable image transmission over wireless channels and reducing the effect of burst errors which commonly occur in wireless communication channels, interleaving of the binary image data prior to modulation is required. In recent years, several interleaving schemes have been proposed [8, 9]. The simplest of such techniques is block interleaving [10]. Block interleaving gives good result in case of data transmission through wireless channels. But if image is to be transferred over wireless channel then it does not give better result because block interleaving can remove only 1-D error burst. Block interleaving cannot remove 2-D error burst in data which is common when data is transmitted through the wireless channel. Hence there is a need of much powerful and 2-D error correcting interleaving scheme for wireless communication. Another interleaving technique such as helical interleaving [11] has been given for reducing the random errors caused by wireless channels. It has been analyzed that the helical

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interleaving scheme can correct the burst errors imposed by wireless channels more efficiently than block interleaving. It was noticed that Helical interleaving and block interleaving schemes yield identical performances for a given interleaving depth. Helical interleaving is different from block interleaving because of two factors, synchronization and error forecasting. For many applications, helical interleaving performs well as compared to block interleaving but the performance of such interleaver is limited. Hence a more powerful interleaving scheme is required that can combat the severe channel errors in wireless communication systems. A new interleaving technique called Chaotic interleaving which is based on Chaotic Baker maps was proposed [12, 13]. Chaotic interleaving can ameliorate both 1-D error burst as well as 2-D error burst more efficiently than another interleaving scheme. When an image is to be transferred through wireless channel than the error burst caused by the wireless channel degrades the quality of image and sometimes some information of the image can also be lost due to consequent errors in the image data. Hence chaotic interleaving randomize the error in the image data to minimize the image degradation caused by bursty errors. The main contribution of this paper is to analyze the performance of the image transmission through MC-CDMA system. To transmit the image data efficiently over wireless channels, interleaving technique is applied on the image data prior to modulation. The two interleaving techniques named helical interleaving and chaotic interleaving are individually applied on the image data. The performance of MC-CDMA system for image transmission with both interleaving techniques is evaluated and compared in the form of quality of received image.

II. INTERLEAVING TECHNIQUES Since the wireless channel is affected by fading and imposes channel errors in the data transmitted through it.

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Many error correction codes have been applied to protect the data transmitted through wireless channels. Most of these error correction codes are good at correcting random errors caused by the wireless channels but the wireless channel causes bursty channel errors. Burst error can be defined as contiguous sequence of error symbols either in one dimensional (1-D) form or in multi-dimensional form. Therefore, interleaving is performed to randomize the bursty errors caused due to multipath fading environment of wireless channels and to improve the performance of the errorcorrecting codes.

The data symbols which are to be interleaved with helical interleaving are first arranged row wise and column wise in form of a matrix. Then, data symbols are read out diagonally from the matrix as shown in Fig. 2. If the data symbols are arranged in a matrix via rows and columns, the index for helically reading the symbols is given as [14]:

In general, interleaving is the process of rearranging the order of data symbols to be transmitted based on a predefined rule so as to spread error bursts over multiple symbols rather than effecting consecutive symbols. At the receiver, the original data symbols are restored according to the reverse rule. In recent years, several interleaving techniques [8, 9] were considered. Block interleaving was considered to be simplest and effective interleaving technique. It has been studied that block interleaving can remove 1-D error burst but it cannot degrade the effect of 2-D error burst and the main aim of this paper is to transmit an image through wireless channel. It is known that quality of image is highly degraded due to 2-D error burst. Therefore, this paper takes two interleaving techniques called helical and chaotic interleaving into consideration to minimize the effect of error burst on the transmission of an image.

nx is the number of symbols in the x dimension of the matrix and n y is the number of symbols in the y

A. Helical Interleaving Helical interleaving [14] reduces the effect of burst error occurring in the data transmission through wireless channels. At the transmitting side, helical interleaver defines the order of the data symbols to be read out from the transmitter to the modulator. At the receiving side, helical de-interleaver defines the order of the data symbols to be read out from the demodulator to the receiver. Internal matrix

A:X

A1

B1

C1

D1

E1

F1

G1

H1

I1

J1

K1

L1

M1

N1

O1

P1

Q1

R1

S1

T1

U1

V1

W1

X1

nx= 4

j = i(nx + 1) mod(nx ny ),

i = {0,1,2,..., nxny −1}

Where, i is the value of original index,

j is the helical

index value,

dimension of the matrix. Helical interleaving process can be explained as: first generate an internal matrix having nx rows and ny columns by rearranging the data symbols row by row in this matrix, then sending the matrix contents in a helical fashion to the final interleaved matrix. Helical fashion means, sending the data symbols along diagonals of the internal matrix. B. Chaotic Interleaving As wireless channel imposes bursty errors in the data transmitted through it, hence interleaving is necessary in the wireless communication system. The Chaotic interleaving is based on the chaotic Baker map [12, 13], which is an efficient tool to randomize the data in a square matrix. In its discretized form, the chaotic Baker map converts a square into itself using a 2-D map. Therefore, chaotic interleaving is more appropriate for randomizing the data to prevent 2-D error burst which very commonly occurs in the wireless channel. Chaotic interleaving is applied on the data which is arranged in a two-dimensional format. Chaotic interleaving constructs permuted sequences with less correlation between their samples. However, the Baker map adds a degree of encryption for the transmitted signal. Let P ( n1 , ….., n k ) denotes the discretized map, where the

ny=6

vector n1, …… n k denotes the secret key Skey. If M is the number of data items in one row, the secret key (Skey) is selected such that M must be divisible by each integer n i , and n1 +…. + n k = M . Let M i = n1 +…..n i . The pixel is moved to the indices [15]: §M · §M · n § § M ·· P(n1,....,nk ) ( p, q) = ¨ ( p − Mi ) + q mod ¨ ¸ , i ¨ q − q mod ¨ ¸ ¸ + Mi ¸ ¨ ¸ ¨ ni ¸ n M n © i¹ © i ¹¹ © © ¹

A1

F1

K1

P1

E1

J1

O1

T1

( p, q )

(2)

Where, M i ≤ p < M i + ni and 0 ≤ q < M .

I1

N1

S1

X1

The chaotic interleaving is performed as follows [15]:

M1

P1

W1

D1

1.

Q1

V1

C1

H1

U1

B1

G1

L1

2. Helically interleaved matrix

(1)

A square matrix having dimension of M × M is divided into M rectangles in which each rectangle consist M number of elements and having width n i . The elements of each rectangle are rearranged in the form of a row in the final interleaved matrix. Rectangles are arranged as left one goes to the bottom and the right one

Fig. 2. Helical interleaving

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3.

goes to the top of the final interleaved matrix, beginning with upper rectangle then lower rectangle. The scanning of elements from each rectangle begins from the bottom left corner element towards upper element.

D1

D2 D3 D4 D5 D6 D7

D17 D18 D19 D20 D21 D22 D23 D24 D25 D26 D27 D28 D29 D30 D31 D32

This above method which is given for performing chaotic interleaving is explained below.

B (4 X 8)

A square matrix (A) of dimension (8 x 8) (i.e. M=8) is considered as an example as shown in Fig. 3. For this square matrix (A), the secret key is chosen as Skey = ª¬n1 , n 2 , n 3 º¼ = [ 2, 4, 2] . As shown in Fig. 3, the (8 x

B1

8) square matrix (A) is divided into two rectangles (B) and (C) of equal dimension of 4 x 8. D1

D2 D3 D4 D5 D6

D7

D8

B2 D3 D4 D5 D6

D7 D8

D9 D10

D11 D12 D13 D14

D15 D16

D17 D18

D19 D20 D21 D22

D23 D24

D25 D26

D27 D28 D29 D30

D31 D32

Fig. 4. Division of rectangle B. B21 (2 X 4)

D17 D18 D19 D20 D21 D22 D23 D24 D25 D26 D27 D28 D29 D30 D31 D32 D33 D34 D35 D36 D37 D38 D39 D40

D3 D4 D5 D6

D3 D4 D5 D6

D11 D12 D13 D14

D11 D12 D13D14

D19 D20 D21 D22

D41 D42 D43 D44 D45 D46 D47 D48

D19 D20 D21D22

D27 D28 D29 D30

D27 D28 D29 D30

D49 D50 D51 D52 D53 D54 D55 D56

A (8 X 8)

D1

D2 D3 D4 D5 D6 D7

B3

D1 D2

D9 D10 D11 D12 D13 D14 D15 D16

D57 D58 D59 D60 D61 D62 D63 D64

D8

D9 D10 D11 D12 D13 D14 D15 D16

B22 (2 X 4)

B2 (4 X 4) . Fig. 5. Division of square B2

D8

D9 D10 D11 D12 D13 D14 D15 D16 D17 D18 D19 D20 D21 D22 D23 D24 D25 D26 D27 D28 D29 D30 D31 D32 B (4 X 8) D33 D34 D35 D36 D37 D38 D39 D40 D41 D42 D43 D44 D45 D46 D47 D48 D49 D50 D51 D52 D53 D54 D55 D56 D57 D58 D59 D60 D61 D62 D63 D64 C (4 X 8) Fig. 3. Division of square A into two rectangles.

As shown in Fig. 6, the new permuted matrix (P) is formed by rearranging the elements in a row from each rectangle. P is the final interleaved matrix after applying chaotic interleaving on the square matrix named A. D31 D23 D15 D7 D32 D24 D16 D8 D63 D55 D47 D39 D64 D56 D48 D40 D11 D3

D12 D4

D13 D5 D14 D6

D27 D19 D28 D20 D29 D21 D30 D22 D43 D35 D44 D36 D45 D37 D46 D38 D59 D51 D60 D52 D61 D53 D62 D54 D25 D17 D9 D1

D26 D18 D10 D2

D57 D49 D41 D33 D58 D50 D42 D34 P (8 X 8)

As shown in Fig. 4, the rectangle (B) is further divided into two rectangles (B1) and (B3) having dimension of 4 x n1 and 4 x n3 respectively and a square (B2) of dimension 4 x n2. As shown in Fig. 5, B2 is further horizontally divided into two rectangles (B21) and (B22) having equal dimension of 2 x 4. Similarly, the same procedure is used for dividing the rectangle (B) will be repeated for the rectangle (C). Thus, total number of rectangles divided from the square matrix (A) is 8.

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Fig. 6. Final square matrix P after chaotic interleaving.

III.

PROPOSED MC-CDMA IMAGE TRANSMISSION MODEL

The block diagram for the proposed image transmission system model is depicted in Fig.7.

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OFDM modulator

Input image

Interleaving

Image formatting

dn

Sn

Spreading & Scrambling

CP +

IFFT

Sn (t)

Wireless channel h(n) Output image

OFDM demodulator Image reconstruction

Deinterleaving

De-spreading & De-Scrambling

LMM -SE

CP -

FFT

r (t)

Fig. 7. MC-CDMA system model for image transmission.

As illustrated in Fig, first stage is the image formatting stage in which the gray input image is first transformed to binary format for further processing. The size of the binary image data is updated according to the need to further transmit it over the system. In next stage, interleaving is applied on the binary data to randomize the order of bits for reducing the effect of bursty channel errors. In this paper, two interleaving schemes named helical interleaving and chaotic interleaving are applied separately on the binary image data. The performance of both interleaving schemes is evaluated in this paper. Now, MC-CDMA modulation is applied on the interleaved data to transmit it over wireless channel. At the receiver, the reverse operations as performed at the transmitter are performed and the output image is recovered from the binary data. The Linear Minimum Mean Square Error (LMMSE) equalization [15] which is a frequency domian equalization is applied at the reciever to improve the performance of the proposed MC-CDMA system. As explained above, the basic MC-CDMA signal is generated by the serial combination of two modulation techniques called CDMA and OFDM. With, MC-CDMA an orthogonal spreading code in the frequency domain. As shown in Fig. 7, at the transmitter, after applying interleaving, dn is the data symbol which is assigned to the n-th user. In spreading stage, each data symbol dn is multiplied by the n-th user’s spreading code, cn of length N [15], which is given as:

cn = (c0 , c1 ,......, cN −1 )T

(3)

As in CDMA, the chip rate of spreading code cn is N times higher than the data symbol rate : 1 N = Tc Td Where

(5)

This spreading sequence Sn is applied to the OFDM modulator. It multiplies the spreading sequence separately by different carriers and then combines all to produce a transmitting signal. As given in Fig, 7, the OFDM modulator comprises Inverse Fast Fourier Transform (IFFT) and Cyclic Prefix (CP) block. The IFFT block converts the frequency domain signal into its corresponding time domain. CP is added to the transmitting data to reduce the effect of delay spread and Inter-Symbol Interference (ISI) as in OFDM. To recover the transmitted data sequence, the receiver performs reverse operations as applied at the transmitter as shown in Fig. 7. At the receiver side, the received data sequence from the channel is given as : r = Hs + n = (r0 , r1 ,...., rN −1 )T

(6)

Where H is the N × N channel response matrix and n is the noise vector of length N . Here, the noise ( n ) inserted by the wireless channel is the Additive White Gaussian Noise (AWGN) having zero mean and variance of σ = 2

N0 . 2

IV. PERFORMANCE INDICATORS In this paper, two parameters have been used to measure the quality of reconstructed image as compared to the original input image. A. Root Mean Square Error (RMSE) The first parameter RMSE can be defined as the square root of the mean squared error of the entire image. It is defined as:

(4)

1 1 is the is the chip rate of spreading code cn and Tc Td

data symbol rate. The sequence can be expressed as:

Sn = dncn = (S0 , S1,....., SN −1 )T

S n obtained after spreading

N

RMSE =

N

¦¦ ( I

0

(i, j ) − I r (i, j )) 2

i =1 j =1

N2

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(7)

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2

Where N is the total number of pixels in the input image.

I0

Ir are the original and reconstructed images respectively.

and

B. Peak Signal-to-noise Ratio (PSNR) The second parameter PSNR has been used to measure the quality of the received image. PSNR can be defined as the ratio of the maximum possible power of a signal to the power of corrupting noise which affects the reliability of the signal. The PSNR is defined as follows [15]:

§ f 2 max · PSNR = 10 log10 ¨ 2 ¸ © RMSE ¹

(8)

TABLE II.

RMSE values for the received Lena images

SNR (dB) (a)

15

20

25

30

47.68

43.79

43.65

43.61

(b)

46.47

43.67

43.01

42.73

(c)

44.38

43.17

42.08

41.29

(d)

42.70

42.02

41.74

40.32

From the tables given above, it can be seen that the quality of the system degrades at lower SNR with respect to low PSNR and high RMSE values. Fig. 8 and Fig. 9 show the variation of the PSNR and RMSE with different values of SNR.

Where, fmax is the maximum possible pixel value in an image. V.

RESULTS AND DISCUSSION

The performance of MC-CDMA system has been evaluated for a single user through PSNR and RMSE. For this purpose, the 128X128 Lena image has been used as an input to the system. A user transmits Binary Phase Shift keying (BPSK) data symbols to the given MC-CDMA system. The wireless channel considered here is AWGN channel with zero mean and variance of N0/2. In this work, LMMSE equalization is applied at the receiver. The LMMSE equalizer can be expressed as [15]: −1

1 · § W =¨HHH + I¸ HH SNR ¹ ©

(9)

Where H is the channel matrix. The Lena image of size 128 x 128 has been transmitted with MC-CDMA. In this paper, following four cases for image transmission are considered and compared.

Fig. 8. PSNR versus SNR for the Lena image transmission with the abovementioned cases.

a)

Conventional MC-CDMA without equalization and interleaving. b) MC-CDMA with LMMSE equalization. c) MC-CDMA with helical interleaving and LMMSE equalization. d) MC-CDMA with chaotic interleaving and LMMSE equalization.

The above defined four cases have been analyzed for the proposed MC-CDMA system over AWGN channel. The PSNR and RMSE values for the following four cases are summarized in Table I and Table II, respectively. TABLE I. PSNR values for the received Lena images in dB SNR (dB)

15

20

25

30 15.52

(a)

14.56

15.30

15.33

(b)

14.78

15.32

15.45

15.61

(c)

15.18

15.42

15.64

15.81

(d)

15.52

15.67

15.71

16.28 Fig. 9. RMSE versus SNR for the Lena image transmission with abovementioned cases.

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From the results shown in Fig. 8 and Fig. 9, it can be concluded that a MC-CDMA image transmission system having chaotic interleaving and LMMSE equalization performs well as compared to MC-CDMA image transmission system having helical interleaving and LMMSE equalization. V.

CONCLUSION

The main contribution of this paper is to analyze the performance of the image transmission through MC-CDMA system. From results, it has been concluded that the MCCDMA image transmission system having chaotic interleaving with LMMSE equalization transmits image efficiently as compared to system having helical interleaving with LMMSE.

REFERENCES [1] [2] [3] [4] [5] [6] [7]

[8]

[9]

[10]

[11] [12]

[13]

[14]

[15]

T. S. Rappaport, Wireless communications principles and practice, 2nd ed. New Jersey: Pearson Education, 2002. R. V. Nee and R. Prasad, OFDM for wireless multimedia communications. London: Artech House, Dec. 2000. K. Fazel and S. Kaiser, Multi-carrier and spread spectrum systems. Chichester: Wiley, 2003. S. Hara and R. Prasad, “Overview of multicarrier CDMA,” IEEE communications magazine,vol. 35, no. 12, pp. 126-133, 1997. H. Schulze and C. Luders, Theory and application of OFDM and CDMA. New York : Willey, 2005. S. B. Slimane, “Bandwidth efficiency of MC-CDMA signals,” Electron. Lett., vol. 35, pp. 1797–1798, Oct. 14, 1999. S. B. Weinstein and P. M. Ebert, “Data transmission by frequencydivision multiplexing using the discrete Fourier transform,” IEEE Trans. Commun. Technol., vol. COM-19, no. 5, pp. 628–634, Oct. 1971. Y. Q. Shi, X. M. Zhang, Z.C. Ni and N. Ansari, “Interleaving for combating burst of errors,” IEEE circuits and systems magazine ,vol.4, 2004. X. Peng X. Peng, A. S. Madhukumar and F. Chin, “Performance studies of interleaving schemes for MC-CDMA systems,” Wireless Communications and Networking Conference, IEEE, vol. 4, pp. 20812086, March, 2004. V. D. Nguyen and H. Kuchenbecker, “Block interleaving for soft decision viterbi decoding in ofdm systems,” Vehicular Technology Confrence,IEEE,vol. 1, pp. 470-474, 2001. E. R. Berlekamp, P. Tong, U.S. Patent, 4559625, 1985. E.S. Hassan et al. “A chaotic interleaving scheme for the continuous phase modulation based single-carrier frequency-domain equalization system,” Wireless Pers Com. Springer Science, vol. 62, no. 1, pp. 183199, Jan. 2012. B. Jovic and C.P. Unsworth, “Choas-based multi-user time division multiplexing communication system,” IET communications, vol. 1, no.4, pp. 549-555 Aug 2007. D. Hao and P. A. Hoeher, “Helical Interleaver Set Design for InterleaveDivision Multiplexing and Related Techniques,” IEEE Communications Letters, vol. 12, pp. 843-845, Nov. 2008. E. M. El-Bakary, E. S. Hassan, O. Zahran, S. A. El-Dolil and F. E. Abd El-Samie, “Efficient image transmission with multi-carrier CDMA,” Wireless Pers Com. Springer Science,

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I. INTRODUCTION With the fast development in wireless communication techniques along with mobile internet and multimedia services, the demand for high data rate transmission is increased significantly. The reliable transmission of data through wireless channels offer great challenge including fading, interference and multipath propagation [1]. Orthogonal Frequency Division Multiplexing (OFDM) [2] has become an auspicious wireless technique for fulfilling the demand of high-data rate multimedia services through wireless channels. In OFDM, the transmitting high rate data stream is split into multiple numbers of lower rate streams which are transmitted over a number of sub-carriers in parallel. Hence, Symbol duration is increased and the effect of multipath delay spread is decreased. Therefore, each subcarrier will suffer only flat fading and inter-symbol interference (ISI). However, when deep fading occurs in the wireless channels, the amplitude of channel response is highly degraded and corresponding subcarriers will experience high noise interference. It causes degradation in the signal-to noise ratio (SNR) at the receiver and symbols suffer from the excessive burst-errors.

c 978-1-4799-3080-7/14/$31.00 2014 IEEE

As the demand for multi-user communication such as cellular systems is increasing, it is required to have multiple access capability to transmit multiple signals simultaneously through the channel. In recent years, a new transmission technique called Multicarrier Code Division Multiple Access (MC-CDMA) [3, 4] which is the combination of CodeDivision Multiple-Access (CDMA) [5] and Orthogonal Frequency Division Multiplexing (OFDM) has become most promising data transmission scheme in wireless communications. This multicarrier transmission scheme has received great attention because these combined systems possess many desirable properties for high data rate and efficient data transmission over wireless channels. The major advantage of the multicarrier technique is that it needs a lower symbol rate as compared to other transmission techniques. With a multicarrier CDMA system, for N carriers, the whole bandwidth of the system is divided into N subbands hence the symbol rate for each subcarrier can be made low. MC-CDMA technique combines the capabilities of both OFDM and CDMA schemes to provide a communication system which has the advantages of both. This combined scheme has become attractive for broadband communications due to the parallel transmission nature of OFDM technique and has the ability to provide larger capacity and flexibility of resource allocation due to advanced allocation technique of CDMA. Another important property of MC-CDMA is that it is bandwidth efficient [6] due to the use of OFDM. In OFDM, the modulation or demodulation can be performed easily by using IFFT or FFT algorithms respectively [7]. MC-CDMA is a suitable candidate for the downlink of a cellular system because of having high spectral efficiency. As shown in Fig. 1, the basic MC-CDMA signal is generated by a serial combination of OFDM and CDMA. Thus with MC-CDMA, each data bit of a user is transmitted in parallel on multiple independently fading sub-carriers (orthogonal) as in OFDM. Each carrier is modulated by a single spreading code as in CDMA. In an MC-CDMA system, spreading is implemented in the frequency domain and the signals of multiple users are separated in the code domain as in CDMA. The MC-CDMA technique is capable not only to combat the ISI, but also exploit the multipath as well. This paper studies the performance of image transmission over MC-CDMA systems.

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S1

Cos (w1t)

C1 Input data (dn) C2

Cos (w1t)

C1

S2

Cos (w2t)

To wireless channel

From transmitter

Cos (w2t)

Output data

C2

...

... Sn

Cn

Cos (wnt)

(a)

Transmitter

Cos (wnt)

Cn

(b) Receiver

Fig. 1 . General MC-CDMA system model (a) Transmitter (b) Receiver

Data transmissions over wireless channels are error prone due to wireless channel impairments such as fading and interference. When multimedia data, specially an image is to be transmitted through wireless channel it is highly imposed to fading, interference and multipath propagation which increase the probability of errors [1]. Another technique which is being considered in this paper is the data interleaving technique to improve the performance of image transmission system. It is known that transmission of an image over wireless channels may face many detrimental conditions because wireless channel is highly imposed to bursty errors which degrade the quality of image being transmitted. Bursty errors can be defined as a group of successive error bits in the onedimensional (1-D) case or connected error bits in multidimensional (M-D) cases. To transmit data efficiently over wireless channels and combat the effect of these bursty errors interleaving techniques have become essential in wireless communication systems. For reliable image transmission over wireless channels and reducing the effect of burst errors which commonly occur in wireless communication channels, interleaving of the binary image data prior to modulation is required. In recent years, several interleaving schemes have been proposed [8, 9]. The simplest of such techniques is block interleaving [10]. Block interleaving gives good result in case of data transmission through wireless channels. But if image is to be transferred over wireless channel then it does not give better result because block interleaving can remove only 1-D error burst. Block interleaving cannot remove 2-D error burst in data which is common when data is transmitted through the wireless channel. Hence there is a need of much powerful and 2-D error correcting interleaving scheme for wireless communication. Another interleaving technique such as helical interleaving [11] has been given for reducing the random errors caused by wireless channels. It has been analyzed that the helical

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interleaving scheme can correct the burst errors imposed by wireless channels more efficiently than block interleaving. It was noticed that Helical interleaving and block interleaving schemes yield identical performances for a given interleaving depth. Helical interleaving is different from block interleaving because of two factors, synchronization and error forecasting. For many applications, helical interleaving performs well as compared to block interleaving but the performance of such interleaver is limited. Hence a more powerful interleaving scheme is required that can combat the severe channel errors in wireless communication systems. A new interleaving technique called Chaotic interleaving which is based on Chaotic Baker maps was proposed [12, 13]. Chaotic interleaving can ameliorate both 1-D error burst as well as 2-D error burst more efficiently than another interleaving scheme. When an image is to be transferred through wireless channel than the error burst caused by the wireless channel degrades the quality of image and sometimes some information of the image can also be lost due to consequent errors in the image data. Hence chaotic interleaving randomize the error in the image data to minimize the image degradation caused by bursty errors. The main contribution of this paper is to analyze the performance of the image transmission through MC-CDMA system. To transmit the image data efficiently over wireless channels, interleaving technique is applied on the image data prior to modulation. The two interleaving techniques named helical interleaving and chaotic interleaving are individually applied on the image data. The performance of MC-CDMA system for image transmission with both interleaving techniques is evaluated and compared in the form of quality of received image.

II. INTERLEAVING TECHNIQUES Since the wireless channel is affected by fading and imposes channel errors in the data transmitted through it.

2014 International Conference on Advances in Computing,Communications and Informatics (ICACCI)

Many error correction codes have been applied to protect the data transmitted through wireless channels. Most of these error correction codes are good at correcting random errors caused by the wireless channels but the wireless channel causes bursty channel errors. Burst error can be defined as contiguous sequence of error symbols either in one dimensional (1-D) form or in multi-dimensional form. Therefore, interleaving is performed to randomize the bursty errors caused due to multipath fading environment of wireless channels and to improve the performance of the errorcorrecting codes.

The data symbols which are to be interleaved with helical interleaving are first arranged row wise and column wise in form of a matrix. Then, data symbols are read out diagonally from the matrix as shown in Fig. 2. If the data symbols are arranged in a matrix via rows and columns, the index for helically reading the symbols is given as [14]:

In general, interleaving is the process of rearranging the order of data symbols to be transmitted based on a predefined rule so as to spread error bursts over multiple symbols rather than effecting consecutive symbols. At the receiver, the original data symbols are restored according to the reverse rule. In recent years, several interleaving techniques [8, 9] were considered. Block interleaving was considered to be simplest and effective interleaving technique. It has been studied that block interleaving can remove 1-D error burst but it cannot degrade the effect of 2-D error burst and the main aim of this paper is to transmit an image through wireless channel. It is known that quality of image is highly degraded due to 2-D error burst. Therefore, this paper takes two interleaving techniques called helical and chaotic interleaving into consideration to minimize the effect of error burst on the transmission of an image.

nx is the number of symbols in the x dimension of the matrix and n y is the number of symbols in the y

A. Helical Interleaving Helical interleaving [14] reduces the effect of burst error occurring in the data transmission through wireless channels. At the transmitting side, helical interleaver defines the order of the data symbols to be read out from the transmitter to the modulator. At the receiving side, helical de-interleaver defines the order of the data symbols to be read out from the demodulator to the receiver. Internal matrix

A:X

A1

B1

C1

D1

E1

F1

G1

H1

I1

J1

K1

L1

M1

N1

O1

P1

Q1

R1

S1

T1

U1

V1

W1

X1

nx= 4

j = i(nx + 1) mod(nx ny ),

i = {0,1,2,..., nxny −1}

Where, i is the value of original index,

j is the helical

index value,

dimension of the matrix. Helical interleaving process can be explained as: first generate an internal matrix having nx rows and ny columns by rearranging the data symbols row by row in this matrix, then sending the matrix contents in a helical fashion to the final interleaved matrix. Helical fashion means, sending the data symbols along diagonals of the internal matrix. B. Chaotic Interleaving As wireless channel imposes bursty errors in the data transmitted through it, hence interleaving is necessary in the wireless communication system. The Chaotic interleaving is based on the chaotic Baker map [12, 13], which is an efficient tool to randomize the data in a square matrix. In its discretized form, the chaotic Baker map converts a square into itself using a 2-D map. Therefore, chaotic interleaving is more appropriate for randomizing the data to prevent 2-D error burst which very commonly occurs in the wireless channel. Chaotic interleaving is applied on the data which is arranged in a two-dimensional format. Chaotic interleaving constructs permuted sequences with less correlation between their samples. However, the Baker map adds a degree of encryption for the transmitted signal. Let P ( n1 , ….., n k ) denotes the discretized map, where the

ny=6

vector n1, …… n k denotes the secret key Skey. If M is the number of data items in one row, the secret key (Skey) is selected such that M must be divisible by each integer n i , and n1 +…. + n k = M . Let M i = n1 +…..n i . The pixel is moved to the indices [15]: §M · §M · n § § M ·· P(n1,....,nk ) ( p, q) = ¨ ( p − Mi ) + q mod ¨ ¸ , i ¨ q − q mod ¨ ¸ ¸ + Mi ¸ ¨ ¸ ¨ ni ¸ n M n © i¹ © i ¹¹ © © ¹

A1

F1

K1

P1

E1

J1

O1

T1

( p, q )

(2)

Where, M i ≤ p < M i + ni and 0 ≤ q < M .

I1

N1

S1

X1

The chaotic interleaving is performed as follows [15]:

M1

P1

W1

D1

1.

Q1

V1

C1

H1

U1

B1

G1

L1

2. Helically interleaved matrix

(1)

A square matrix having dimension of M × M is divided into M rectangles in which each rectangle consist M number of elements and having width n i . The elements of each rectangle are rearranged in the form of a row in the final interleaved matrix. Rectangles are arranged as left one goes to the bottom and the right one

Fig. 2. Helical interleaving

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3.

goes to the top of the final interleaved matrix, beginning with upper rectangle then lower rectangle. The scanning of elements from each rectangle begins from the bottom left corner element towards upper element.

D1

D2 D3 D4 D5 D6 D7

D17 D18 D19 D20 D21 D22 D23 D24 D25 D26 D27 D28 D29 D30 D31 D32

This above method which is given for performing chaotic interleaving is explained below.

B (4 X 8)

A square matrix (A) of dimension (8 x 8) (i.e. M=8) is considered as an example as shown in Fig. 3. For this square matrix (A), the secret key is chosen as Skey = ª¬n1 , n 2 , n 3 º¼ = [ 2, 4, 2] . As shown in Fig. 3, the (8 x

B1

8) square matrix (A) is divided into two rectangles (B) and (C) of equal dimension of 4 x 8. D1

D2 D3 D4 D5 D6

D7

D8

B2 D3 D4 D5 D6

D7 D8

D9 D10

D11 D12 D13 D14

D15 D16

D17 D18

D19 D20 D21 D22

D23 D24

D25 D26

D27 D28 D29 D30

D31 D32

Fig. 4. Division of rectangle B. B21 (2 X 4)

D17 D18 D19 D20 D21 D22 D23 D24 D25 D26 D27 D28 D29 D30 D31 D32 D33 D34 D35 D36 D37 D38 D39 D40

D3 D4 D5 D6

D3 D4 D5 D6

D11 D12 D13 D14

D11 D12 D13D14

D19 D20 D21 D22

D41 D42 D43 D44 D45 D46 D47 D48

D19 D20 D21D22

D27 D28 D29 D30

D27 D28 D29 D30

D49 D50 D51 D52 D53 D54 D55 D56

A (8 X 8)

D1

D2 D3 D4 D5 D6 D7

B3

D1 D2

D9 D10 D11 D12 D13 D14 D15 D16

D57 D58 D59 D60 D61 D62 D63 D64

D8

D9 D10 D11 D12 D13 D14 D15 D16

B22 (2 X 4)

B2 (4 X 4) . Fig. 5. Division of square B2

D8

D9 D10 D11 D12 D13 D14 D15 D16 D17 D18 D19 D20 D21 D22 D23 D24 D25 D26 D27 D28 D29 D30 D31 D32 B (4 X 8) D33 D34 D35 D36 D37 D38 D39 D40 D41 D42 D43 D44 D45 D46 D47 D48 D49 D50 D51 D52 D53 D54 D55 D56 D57 D58 D59 D60 D61 D62 D63 D64 C (4 X 8) Fig. 3. Division of square A into two rectangles.

As shown in Fig. 6, the new permuted matrix (P) is formed by rearranging the elements in a row from each rectangle. P is the final interleaved matrix after applying chaotic interleaving on the square matrix named A. D31 D23 D15 D7 D32 D24 D16 D8 D63 D55 D47 D39 D64 D56 D48 D40 D11 D3

D12 D4

D13 D5 D14 D6

D27 D19 D28 D20 D29 D21 D30 D22 D43 D35 D44 D36 D45 D37 D46 D38 D59 D51 D60 D52 D61 D53 D62 D54 D25 D17 D9 D1

D26 D18 D10 D2

D57 D49 D41 D33 D58 D50 D42 D34 P (8 X 8)

As shown in Fig. 4, the rectangle (B) is further divided into two rectangles (B1) and (B3) having dimension of 4 x n1 and 4 x n3 respectively and a square (B2) of dimension 4 x n2. As shown in Fig. 5, B2 is further horizontally divided into two rectangles (B21) and (B22) having equal dimension of 2 x 4. Similarly, the same procedure is used for dividing the rectangle (B) will be repeated for the rectangle (C). Thus, total number of rectangles divided from the square matrix (A) is 8.

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Fig. 6. Final square matrix P after chaotic interleaving.

III.

PROPOSED MC-CDMA IMAGE TRANSMISSION MODEL

The block diagram for the proposed image transmission system model is depicted in Fig.7.

2014 International Conference on Advances in Computing,Communications and Informatics (ICACCI)

OFDM modulator

Input image

Interleaving

Image formatting

dn

Sn

Spreading & Scrambling

CP +

IFFT

Sn (t)

Wireless channel h(n) Output image

OFDM demodulator Image reconstruction

Deinterleaving

De-spreading & De-Scrambling

LMM -SE

CP -

FFT

r (t)

Fig. 7. MC-CDMA system model for image transmission.

As illustrated in Fig, first stage is the image formatting stage in which the gray input image is first transformed to binary format for further processing. The size of the binary image data is updated according to the need to further transmit it over the system. In next stage, interleaving is applied on the binary data to randomize the order of bits for reducing the effect of bursty channel errors. In this paper, two interleaving schemes named helical interleaving and chaotic interleaving are applied separately on the binary image data. The performance of both interleaving schemes is evaluated in this paper. Now, MC-CDMA modulation is applied on the interleaved data to transmit it over wireless channel. At the receiver, the reverse operations as performed at the transmitter are performed and the output image is recovered from the binary data. The Linear Minimum Mean Square Error (LMMSE) equalization [15] which is a frequency domian equalization is applied at the reciever to improve the performance of the proposed MC-CDMA system. As explained above, the basic MC-CDMA signal is generated by the serial combination of two modulation techniques called CDMA and OFDM. With, MC-CDMA an orthogonal spreading code in the frequency domain. As shown in Fig. 7, at the transmitter, after applying interleaving, dn is the data symbol which is assigned to the n-th user. In spreading stage, each data symbol dn is multiplied by the n-th user’s spreading code, cn of length N [15], which is given as:

cn = (c0 , c1 ,......, cN −1 )T

(3)

As in CDMA, the chip rate of spreading code cn is N times higher than the data symbol rate : 1 N = Tc Td Where

(5)

This spreading sequence Sn is applied to the OFDM modulator. It multiplies the spreading sequence separately by different carriers and then combines all to produce a transmitting signal. As given in Fig, 7, the OFDM modulator comprises Inverse Fast Fourier Transform (IFFT) and Cyclic Prefix (CP) block. The IFFT block converts the frequency domain signal into its corresponding time domain. CP is added to the transmitting data to reduce the effect of delay spread and Inter-Symbol Interference (ISI) as in OFDM. To recover the transmitted data sequence, the receiver performs reverse operations as applied at the transmitter as shown in Fig. 7. At the receiver side, the received data sequence from the channel is given as : r = Hs + n = (r0 , r1 ,...., rN −1 )T

(6)

Where H is the N × N channel response matrix and n is the noise vector of length N . Here, the noise ( n ) inserted by the wireless channel is the Additive White Gaussian Noise (AWGN) having zero mean and variance of σ = 2

N0 . 2

IV. PERFORMANCE INDICATORS In this paper, two parameters have been used to measure the quality of reconstructed image as compared to the original input image. A. Root Mean Square Error (RMSE) The first parameter RMSE can be defined as the square root of the mean squared error of the entire image. It is defined as:

(4)

1 1 is the is the chip rate of spreading code cn and Tc Td

data symbol rate. The sequence can be expressed as:

Sn = dncn = (S0 , S1,....., SN −1 )T

S n obtained after spreading

N

RMSE =

N

¦¦ ( I

0

(i, j ) − I r (i, j )) 2

i =1 j =1

N2

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(7)

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2

Where N is the total number of pixels in the input image.

I0

Ir are the original and reconstructed images respectively.

and

B. Peak Signal-to-noise Ratio (PSNR) The second parameter PSNR has been used to measure the quality of the received image. PSNR can be defined as the ratio of the maximum possible power of a signal to the power of corrupting noise which affects the reliability of the signal. The PSNR is defined as follows [15]:

§ f 2 max · PSNR = 10 log10 ¨ 2 ¸ © RMSE ¹

(8)

TABLE II.

RMSE values for the received Lena images

SNR (dB) (a)

15

20

25

30

47.68

43.79

43.65

43.61

(b)

46.47

43.67

43.01

42.73

(c)

44.38

43.17

42.08

41.29

(d)

42.70

42.02

41.74

40.32

From the tables given above, it can be seen that the quality of the system degrades at lower SNR with respect to low PSNR and high RMSE values. Fig. 8 and Fig. 9 show the variation of the PSNR and RMSE with different values of SNR.

Where, fmax is the maximum possible pixel value in an image. V.

RESULTS AND DISCUSSION

The performance of MC-CDMA system has been evaluated for a single user through PSNR and RMSE. For this purpose, the 128X128 Lena image has been used as an input to the system. A user transmits Binary Phase Shift keying (BPSK) data symbols to the given MC-CDMA system. The wireless channel considered here is AWGN channel with zero mean and variance of N0/2. In this work, LMMSE equalization is applied at the receiver. The LMMSE equalizer can be expressed as [15]: −1

1 · § W =¨HHH + I¸ HH SNR ¹ ©

(9)

Where H is the channel matrix. The Lena image of size 128 x 128 has been transmitted with MC-CDMA. In this paper, following four cases for image transmission are considered and compared.

Fig. 8. PSNR versus SNR for the Lena image transmission with the abovementioned cases.

a)

Conventional MC-CDMA without equalization and interleaving. b) MC-CDMA with LMMSE equalization. c) MC-CDMA with helical interleaving and LMMSE equalization. d) MC-CDMA with chaotic interleaving and LMMSE equalization.

The above defined four cases have been analyzed for the proposed MC-CDMA system over AWGN channel. The PSNR and RMSE values for the following four cases are summarized in Table I and Table II, respectively. TABLE I. PSNR values for the received Lena images in dB SNR (dB)

15

20

25

30 15.52

(a)

14.56

15.30

15.33

(b)

14.78

15.32

15.45

15.61

(c)

15.18

15.42

15.64

15.81

(d)

15.52

15.67

15.71

16.28 Fig. 9. RMSE versus SNR for the Lena image transmission with abovementioned cases.

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From the results shown in Fig. 8 and Fig. 9, it can be concluded that a MC-CDMA image transmission system having chaotic interleaving and LMMSE equalization performs well as compared to MC-CDMA image transmission system having helical interleaving and LMMSE equalization. V.

CONCLUSION

The main contribution of this paper is to analyze the performance of the image transmission through MC-CDMA system. From results, it has been concluded that the MCCDMA image transmission system having chaotic interleaving with LMMSE equalization transmits image efficiently as compared to system having helical interleaving with LMMSE.

REFERENCES [1] [2] [3] [4] [5] [6] [7]

[8]

[9]

[10]

[11] [12]

[13]

[14]

[15]

T. S. Rappaport, Wireless communications principles and practice, 2nd ed. New Jersey: Pearson Education, 2002. R. V. Nee and R. Prasad, OFDM for wireless multimedia communications. London: Artech House, Dec. 2000. K. Fazel and S. Kaiser, Multi-carrier and spread spectrum systems. Chichester: Wiley, 2003. S. Hara and R. Prasad, “Overview of multicarrier CDMA,” IEEE communications magazine,vol. 35, no. 12, pp. 126-133, 1997. H. Schulze and C. Luders, Theory and application of OFDM and CDMA. New York : Willey, 2005. S. B. Slimane, “Bandwidth efficiency of MC-CDMA signals,” Electron. Lett., vol. 35, pp. 1797–1798, Oct. 14, 1999. S. B. Weinstein and P. M. Ebert, “Data transmission by frequencydivision multiplexing using the discrete Fourier transform,” IEEE Trans. Commun. Technol., vol. COM-19, no. 5, pp. 628–634, Oct. 1971. Y. Q. Shi, X. M. Zhang, Z.C. Ni and N. Ansari, “Interleaving for combating burst of errors,” IEEE circuits and systems magazine ,vol.4, 2004. X. Peng X. Peng, A. S. Madhukumar and F. Chin, “Performance studies of interleaving schemes for MC-CDMA systems,” Wireless Communications and Networking Conference, IEEE, vol. 4, pp. 20812086, March, 2004. V. D. Nguyen and H. Kuchenbecker, “Block interleaving for soft decision viterbi decoding in ofdm systems,” Vehicular Technology Confrence,IEEE,vol. 1, pp. 470-474, 2001. E. R. Berlekamp, P. Tong, U.S. Patent, 4559625, 1985. E.S. Hassan et al. “A chaotic interleaving scheme for the continuous phase modulation based single-carrier frequency-domain equalization system,” Wireless Pers Com. Springer Science, vol. 62, no. 1, pp. 183199, Jan. 2012. B. Jovic and C.P. Unsworth, “Choas-based multi-user time division multiplexing communication system,” IET communications, vol. 1, no.4, pp. 549-555 Aug 2007. D. Hao and P. A. Hoeher, “Helical Interleaver Set Design for InterleaveDivision Multiplexing and Related Techniques,” IEEE Communications Letters, vol. 12, pp. 843-845, Nov. 2008. E. M. El-Bakary, E. S. Hassan, O. Zahran, S. A. El-Dolil and F. E. Abd El-Samie, “Efficient image transmission with multi-carrier CDMA,” Wireless Pers Com. Springer Science,

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