Mohamed Haj Taieb

Multi-objective genetic algorithm optimization for image watermarking based on singular value decomposition and lifting wavelet transform

In this paper, a new optimal watermarking scheme based on singular value decomposition (SVD) and lifting wavelet transform (LWT) using multi-objective genetic algorithm optimization (MOGAO) is presented. The singular values of the watermark is embedded in a detail subband of host image. To achieve the highest possible robustness without losing watermark transparency, multiple scaling factors (MSF) are used instead of single scaling factor (SSF). Determining the optimal values of the MSFs is a difficult problem. However, to find this values a multi-objective genetic algorithm optimization is used. Experimental results show a much improved performance in term of transparency and robustness of the proposed method compared to others methods.

Reliable and secure communications over Gaussian wiretap channel using HARQ LDPC codes and error contamination

This paper investigates reliable and secure transmissions over the Gaussian wiretap channel. A physical layer coding scheme based on Low-Density-Parity-Check (LDPC) codes with granular Hybrid Automatic Repeat reQuest(HARQ) protocol is presented. HARQ granularity aims at sending coded data at the minimum rate required for legitimate successful decoding while minimizing the information leakage that may benefit to eavesdropping. It will be shown that the granularity increases the frame error rate at the eavesdropping receiver. Since the secrecy level can be assessed through the bit error rate (BER) at the unintended receiver, intraframe and interframe error contaminations are employed to convert the loss of only few packets in the wiretap channel into much higher BERs at the eavesdropper. From the BERs at the legitimate and illegitimate receivers, the reliability and security regions can be determined. It is observed that with granular HARQ and interframe error contamination, signal to noise (SNR) regions that are simultaneously reliable and secure are expanded significantly.

Turbo code using adaptive puncturing for pixel domain distributed video coding

Distributed video coding is a research field which brings together error coding techniques along with video compression ones. Its core part is a Slepian-Wolf encoder which often involves turbo codes because of their strong error correction capabilities. The turbo encoder generates parity bits which are sent to refine the side information constructed at the decoder by interpolation using the neighboring key frames already received. For bit rate flexibility, these parity bits are punctured and sent gradually upon request until the receiver can correctly decode the frame. In this work, we introduce a novel distributed video coding scheme with adaptive puncturing that sends more parity bits when the virtual channel is noisy and less parity bit when it is not the case. Considerable compression performance improvement over the puncturing techniques used in literature is reported.

Spatial correlation-based side information refinement for distributed video coding

Distributed video coding (DVC) architecture designs, based on distributed source coding principles, have benefitted from significant progresses lately, notably in terms of achievable rate-distortion performances. However, a significant performance gap still remains when compared to prediction-based video coding schemes such as H.264/AVC. This is mainly due to the non-ideal exploitation of the video sequence temporal correlation properties during the generation of side information (SI). In fact, the decoder side motion estimation provides only an approximation of the true motion. In this paper, a progressive DVC architecture is proposed, which exploits the spatial correlation of the video frames to improve the motion-compensated temporal interpolation (MCTI). Specifically, Wyner-Ziv (WZ) frames are divided into several spatially correlated groups that are then sent progressively to the receiver. SI refinement (SIR) is performed as long as these groups are being decoded, thus providing more accurate SI for the next groups. It is shown that the proposed progressive SIR method leads to significant improvements over the Discover DVC codec as well as other SIR schemes recently introduced in the literature.

Progressive distributed video coding with multiple passes for side information update

Distributed video coding is a new video paradigm that transfers the computational bulk from video encoders to decoders. Thus, the scenario of video transmission involving inexpensive encoders and a powerful central decoder would be possible. In a previous work, the authors have proposed a novel distributed video coding scheme with progressive decoding. The proposed architecture considers a chessboard structure for block grouping. A subset of blocks are first sent, decoded and then used to update the side information. Then, the remaining blocks are sent and decoded using the updated and more accurate side information. This progressive technique with two groups of blocks shows an improvement up to 1.7 dB over the conventional DVC architecture. In this paper, we extend the progressive architecture by splitting the frame into three and four groups of blocks rather than only two groups. Further improvement up to 0.4 dB over the progressive architecture with only two groups is obtained.

Adaptive granular HARQ LDPC-based coding for secrecy enhancement in wiretap channels

In this work, reliable and secure transmission over generic-Gaussian wiretap channel model is investigated. An Adaptive Granular Hybrid Automatic Repeat reQuest (AG-HARQ) protocol is proposed which tries to minimize the required rate for successful decoding by the legitimate parties while amplifying the privacy by minimizing the information leakage to a wiretapper. In the case of LDPC decoding failure at the legitimate receiver (Bob), a retransmission is requested until correct decoding or until the maximum number of transmitted packets is reached. As soon as Bob is able to correctly decode the LDPC codeword, the retransmissions are stopped to avoid any additional bits leakage to the eavesdropper (Eve). In our proposed method, to minimize the leakage, a confidence level index, Cj, for correct decoding is defined as the mean of absolute value of the Log-Likelihood Ratio (LLR). In the case of failure, only the sub-packets with the smallest Cj values will be retransmitted since they represent the most unreliable information sub-packets. Frame Error Rate (FER) is used as a metric to show the effectiveness of the proposed method.

Improving MIMO systems performances by concatenating LDPC decoder to the STBC and MRC receivers

Multiple-input multiple-output (MIMO) systems are commonly used in wireless communications to ensure high bit-rate and high capacity transmission. Space time block coding (STBC) is a technique used in MIMO to provide transmit diversity in communication over fading channels. Although STBC has full diversity gain, the coding gain need to be improved by using channel coding such as low density parity check (LDPC) codes or Turbo codes. This paper evaluates the performance of MIMO systems and the improvement obtained by concatenating LDPC codes. MIMO are based on spatially separated multiple transmitting and receiving antennas to provide diversity. This helps combatting the effect of multipath fading in wireless channels. For single-input multiple-output (SIMO) schemes, maximum ratio combining (MRC) receiver are used to handle redundantly the same information-bearing signal over two or more fading channel. The output of this receiver consist on soft decision metrics that can be fed to LDPC decoder for error correction. For MIMO and multiple-input single-output (MISO) systems, space time block codes (STBC) are used to generate orthogonal signals to avoid interference between signal streams. These signals are transmitted at slightly different times to benefit from temporal diversity. LDPC codes are used in conjunction with STBC to improve the error capability. This paper investigates diversity coding for MIMO systems combined with LDPC soft decoding. Performances of the proposed scheme in terms of bit error rates are reported.

Adaptive use of systematic bits in distributed video coding with multiple puncturing matrices

Distributed video coding paradigm aims at transferring the major part of the processing computation effort from the encoder to the decoder. Motion interpolation is done at the decoder to generate side information (SI) through motion compensated temporal interpolation (MCTI). SI is considered as a noisy version of the original data: channel control coding schemes, such as turbo coding, are used to eliminate the errors (SI inaccuracies). The video data is turbo encoded and the parity bits are sent to the decoder. The systematic bits, however, are discarded since the decoder already disposes of SI that can be used for the channel likelihood ratio calculations. However, when the MCTI generation of SI is highly corrupted, the channel likelihood ratios based on the SI are inefficient and even misleading. A number of parity bits number exceeding the original data length may then be required, thus leading to an undesirable expansion effect. In this paper, we propose a method to detect adaptively the situations where the SI is of lower quality. Then puncturing matrices, enabling systematic bits, are used to help computing reliable channel likelihood ratios. An improvement up to 0.5 dB is reported for PSNRs vs bit rate performances.

Physical layer secrecy for wireless communication systems using adaptive HARQ with error contamination

This paper proposes a physical layer coding scheme to provide reliability and security in wireless communication systems. An Adaptive Granular Hybrid Automatic Repeat re- Quest (AG-HARQ) scheme based on Low-Density-Parity-Check (LDPC) codes is proposed. In the AG-HARQ protocol, the whole codewords are first transmitted (by Alice) to the intended receiver (Bob) and potentially intercepted by an unauthorized receiver or eavesdropper (Eve). Whenever the legitimate receiver (Bob) fails to decode the correct message, the received codewords are splitted into sub-packets and Bob computes a decoding confidence index for each of these sub-packets. Bob can then request a retransmission of those sub-packets having the lowest confidence indexes. These sub-packets are requested by Bob until correct decoding or until a maximum number of retransmissions is reached. An error contamination (EC) mechanism is also proposed which spreads the errors in the current frame with a scrambler and to the other frames by use of block interleavers. The proposed scheme ensures reliable and secure communication even in the case of negative Security Gap (SG) where the eavesdroppers channel benefits from better channel conditions than the legitimate channel.

On the design of good LDPC codes with joint genetic algorithm and linear programming optimization

In communication systems, the transmitted data is corrupted by channel perturbations, such as noise and fading, which affect the reliability of the received data. Error correction codes are employed to mitigate channel perturbations. However, design and implementation of good and efficient error correction codes remains an open problem. In this paper, Low Density Parity Check (LDPC) codes are considered as they provide a reasonable trade-off between computational complexity and reliability. Good LDPC codes should ideally provide low complexity, close to capacity acheivable transmission rate, high coding threshold, and high decoding stability. In this paper, we investigate a joint LDPC code optimization algorithm using Genetic Algorithm (GA) and Linear Programming (LP) to determine the variable nodes and check nodes degrees distributions. EXIT chart analysis and Frame Error Rate (FER) performance are used to validate the proposed method.