Parallel Concatenated Turbo Code Research Articles

Power Optimization of Three Dimensional Turbo Code Using a Novel Modified Symbiotic Organism Search (MSOS) Algorithm

In modern communication system error-control coding scheme is used to elevate the immunity of noisy communication channel. Turbo code (TC) is considered as one of the significant channel coding schemes which approaches to the Shannon limit. An upgraded version of TC named as 3 dimensional turbo code (3D-TC) has been emerged as a challenging research area in recent past. Meanwhile, considerable improvement in bit error rate (BER) performance of the TC has been achieved by incorporating suitable optimization algorithms. Motivated by above research trends, a modified symbiotic organisms search (MSOS) algorithm has been proposed by changing the organism structure and selection criteria of a newly developed symbiotic organisms search (SOS) algorithm. Subsequently the proposed MSOS has been used to design an improved 3D-TC. Here an optimal power allocation scheme of a new class of 3 dimensional turbo encoder has been investigated to improve its BER characteristics mainly in high SNR regions. Furthermore, the BER performance of the proposed 3D-TC code has been compared with conventional 2D serially concatenated and parallel concatenated turbo code as well as conventional 3D-TC. Finally, the BER performance of the proposed MSOS optimized 3D-TC has been compared with the SOS optimized 3D-TC and harmony search optimized 3D-TC.

Stochastic resonance in parallel concatenated turbo code decoding

In an array of threshold devices, we examine the effect of noise in improving performance of turbo code decoding. Such a phenomenon of noise-enhanced effect is termed stochastic resonance (SR). When signal is subthreshold, SR is observed by using Gaussian noise during iterative decoding. That is, the minimal bit error ratio (BER) is achieved at some non-zero noise intensity level. Besides, the larger the number of threshold devices is, the more remarkable the SR effect becomes. Especially when noise intensity is nearly optimal, BER approximates to zero after a few decoding iterations. Moreover, when Gaussian mixture noise is utilized, suprathreshold stochastic resonance (SSR) occurs in turbo decoding. These results show the beneficial effect of noise in channel coding and decoding.

Achieving near-capacity performance on multiple-antenna channels with a simple concatenation scheme

This paper proposes a capacity-approaching, yet simple scheme for multi-input multiple-output (MIMO) channels. The proposed scheme is based on a concatenation of a mixture of short memory-length convolutional codes or repetition codes and a short, and simple rate-1 linear block code, followed by either 1-dimensional (1-D) anti-Gray or Gray mapping of quadrature phase-shift keying (QPSK) modulation. By interpreting the rate-1 code and the 1-D mapping as a multi-D mapping performed over multiple transmit antennas, the error performance is analyzed in two regions. In the error-floor region, a tight union bound and the corresponding design criterion on the asymptotic performance are derived. The bound provides a useful tool to predict the error performance at relatively low bit error rate (BER) values. Based on the obtained design criterion, an optimal rate-1 code for each 1-D mapping is then constructed to achieve the best asymptotic performance. In the turbo pinch-off region, by using extrinsic information transfer (EXIT) charts, the most suitable mixed codes are selected for both symmetric and asymmetric antenna configurations. It is demonstrated that the simple concatenation scheme can achieve a near-capacity performance over the MIMO channels. Furthermore, its error performance is shown to be comparable to that obtained by using well-designed irregular LDPC and RA codes, and therefore, the proposed scheme significantly outperforms a scheme employing a parallel concatenated turbo code. Simulation results in various cases are provided to verify the analysis.