Irregular Vector Turbo Codes with Low Complexity

The term Block Turbo Code typically refers to the iterative decoding of a serially concatenated two-dimensional systematic block code. This paper introduces a Vector Turbo Code that is irregular but with code rates comparable to those of a Block Turbo Code (BTC) when the Bahl Cocke Jelinek Raviv (BCJR) algorithm is used. In Block Turbo Codes, the horizontal (or vertical) blocks are encoded first and the vertical (or horizontal) blocks second. The irregular Vector Turbo Code (iVTC) uses information bits that participate in varying numbers of trellis sections, which are organized into blocks that are encoded horizontally (or vertical) without vertical (or horizontal) encoding. The decoding requires only one soft-input soft-output (SISO) decoder. In general, a reduction in complexity, in comparison to a Block Turbo Code was achieved for the same very low probability of bit error (10−5 ). Performance in the AWGN channel shows that iVTC is capable of achieving a significant coding gain of 1.28 dB for a 64QAM modulation scheme, at a bit error rate (BER) of 10−5over its corresponding Block Turbo Code. Simulation results also show that some of these codes perform within 0.49 dB of capacity for binary transmission over an AWGN channel.

Introducing perforation when applying turbo codes

The problem of adapting the degree of redundancy introduced in the process of error-correcting coding to the changing characteristics of the data transmission channel is urgent. Turbo codes, used in a variety of digital communication systems, are capable of correcting multiple errors occurring in the data transmission channel. The article compares the decoding efficiency for various options for introducing perforation into the code sequence generated by the turbo code encoder. Based on the comparison results, recommendations were made on the most appropriate option for the introduction of perforation.

Turbo-coded Ultra Long Haul System with Probabilistic Shaped 16QAM Modulation

With the rapid growth and development of 5G (5th Generation Mobile Communication Technology) and the incoming of 6G (6th Generation Mobile Communication Technology), the demand for high-speed and flexible communication solutions is becoming far more urgent. Within this paper, a novel code modulation scheme based on PS (probabilistic shaping) and Turbo code is proposed with its effectiveness is confirmed by the results of simulation. The results inform that in an optical fiber communication system with 56 Gb/s rate and 3000 km transmission distance, when the SNR (signal-noise ratio) is greater than 3.5 dB, the Turbo-coded PS-16QAM modulation format can achieve reliable transmission. The proposed scheme performs the best in BER (bit error ratio) and average launch power in the four cases of uniform 16QAM, PS-16QAM, Turbo-coded 16QAM with and itself. The proposed scheme is a potential solution in the future 5G communication.

A Parallel Turbo Decoder Based on Recurrent Neural Network

A neural network-based decoder, based on a long short-term memory (LSTM) network, is proposed to solve the problem of high decoding delay caused by the poor parallelism of existing decoding algorithms for turbo codes. The powerful parallel computing and feature learning ability of neural networks can reduce the decoding delay of turbo codes and bit error rates simultaneously. The proposed decoder refers to a unique component coding concept of turbo codes. First, each component decoder is designed based on an LSTM network. Next, each layer of the component decoder is trained, and the trained weights are loaded into the turbo code decoding neural network as initialization parameters. Then, the turbo code decoding network is trained end-to-end. Finally, a complete turbo decoder is realized. Simulation results show that the performance of the proposed decoder is improved by 0.5–1.5 dB compared with the traditional serial decoding algorithm in Gaussian white noise and t-distribution noise. Furthermore, the results demonstrate that the proposed decoder can be used in communication systems with various turbo codes and that it solves the problem of high delay in serial iterative decoding.

MIMO-Orthogonal space time block code system joint with BCH-TC in Rayleigh fading channel for performance of transmit antenna selection

Purpose To enhance the performance transmit antenna selection (TAS) of spatial modulation (SM), systems technique needs to be essential. This TAS is an effective technique for reducing the multiple input multiple output (MIMO) systems computational difficulty, and bit error rate (BER) can increase remarkably by various TAS algorithms. But these selection methods cannot provide code gain, so it is essential to join the TAS with external code to obtain cy -ode gain advantages in BER. Design/methodology/approach In this paper, Bose–Chaudhuri–Hocquenghem (BCH)-Turbo code TC is combined with the orthogonal space time block code system. Findings In some existing work, the improved BER has been perceived by joining forward error correction code and space time block code (STBC) for MIMO systems provided greater code gain. The proposed work can provide increasing code gain and the effective advantages of the TAS-OSTBC system. Originality/value To perform the system analysis, Rayleigh channel is used. In the case with multiple TAS-OSTBC systems, better performance can provide by this new joint of the BCH-Turbo compared to the conventional Turbo code for the Rayleigh fading.

Crypto-Watermarking Algorithm Using Weber’s Law and AES: A View to Transfer Safe Medical Image

We propose a novel method for medical image watermarking in the DCT domain using the AES encryption algorithm. First, we decompose the original medical image into subblocks of 8 × 8. Besides, we apply the DCT and the quantization, respectively, to each subblock. However, in the DCT domain, an adequate choice of the DCT coefficients according to the quantization table in the middle frequencies band is performed. After that, we embed the patient’s data into the corresponding medical image. The insertion step is carried out just after the quantization phase. To increase the robustness, we encrypt the watermarked medical images by using the AES algorithm based on chaotic technique. Arnold’s cat map is used to shuffle the pixel values, and a chaotic Henon map is utilized to generate an aleatory sequence for the AES algorithm. The shuffled watermarked image is encrypted using the modified AES algorithm. The constant of Weber is used to choose the suitable visibility factor for embedding a watermark with high robustness. To control identification, after application of attacks, we use the serial turbo code for correction of the watermark to recover the data inserted. The average peak signal-to-noise ratio (PSNR) of the medical images obtained is 61,7769 dB. Experimental results demonstrate the robustness of the proposed schema against various types of attacks.

Channel Coding Technique for 5G to Improve Flexibility

5G wireless network will take place after 4G. It will create many new issues. Some problems like, communication with low BER, and performance might be severe issue. In this thesis, coding methods are proposed in order to decrease the signal loss during the transmission process of data. Also, the LDPC system is explained in order to get good results with lower bit error rate over 5G standards by trying to compare it with systems like, LDPC, Convolutional and Turbo code system. Finally, a framework is designed which is a combination of LDPC codes with polar codes in order to improve information transmission efficiency.

Perceptual Data Embedding in Audio and Speech Signals

Perceptual embedding is a technique to embed extra information into multimedia signals without fidelity degradation, which is the core of many applications including watermarking and data hiding. Perceptual embedding can be viewed as a telecommunication to transmit the embedded information over the medium consisting of the host signal. This observation divides the current embedding techniques into two categories, i.e. the host-suppressing ones like the quantization-based Quantization Index Modulation (QIM) and Scalar Costa Scheme (SCS), and the non host-suppressing ones like the conventional Spread Spectrum (SS) technique. The former class has significant advantages over the latter in robustness and data rate due to significantly reduced noise levels. In this research, the conventional SS embedding technique is modified such that it can suppress the host impact mostly. Both the theoretical analysis and simulations show that the modification significantly improve the performance of the conventional scheme and further, outperform the QIM and SCS under the case of watermarking where the attacks can be expected to be very strong. To further increase the robustness and embedding rate, measures like frequency masking effects of the Human Masking Auditory system and Forward Error Correction schemes are employed, such as Turbo code. The second part of this research explores the possibility of high-capacity embedding in telephony speech signals. Another modification to improve the embedding rate is proposed for the conventional SS scheme under weak attacks, which are expected for the case of data embedding.