Joint source and channel coding using turbo codes over rings

Turbo codes are a practical solution for achieving large coding gains. We present a new turbo coding scheme where the component codes are convolutional codes (CCs) over the ring of integers modulo M, with M being the alphabet size of the source encoder. The a priori knowledge of the source statistics is used during the iterative decoding procedure for improved decoder performance. As an example of application, we examine differential pulse code modulation (DPCM) encoded image transmission     

Near-optimum decoding of product codes: block turbo codes

This paper describes an iterative decoding algorithm for any product code built using linear block codes. It is based on soft-input/soft-output decoders for decoding the component codes so that near-optimum performance is obtained at each iteration. This soft-input/soft-output decoder is a Chase decoder which delivers soft outputs instead of binary decisions. The soft output of the decoder is an estimation of the log-likelihood ratio (LLR) of the binary decisions given by the Chase decoder. The theoretical justifications of this algorithm are developed and the method used for computing the soft output is fully described. The iterative decoding of product codes is also known as the block turbo code (BTC) because the concept is quite similar to turbo codes based on iterative decoding of concatenated recursive convolutional codes. The performance of different Bose-Chaudhuri-Hocquenghem (BCH)-BTCs are given for the Gaussian and the Rayleigh channel. Performance on the Gaussian channel indicates that data transmission at 0.8 dB of Shannon's limit or more than 98% (R/C>0.98) of channel capacity can be achieved with high-code-rate BTC using only four iterations. For the Rayleigh channel, the slope of the bit-error rate (BER) curve is as steep as for the Gaussian channel without using channel state information     

Iterative decoding of codes over complex numbers for impulsive noise channels

We discuss the decoding of error-correcting block codes over complex numbers for the transmission over impulsive noise channels. The encoder multiplies a vector of complex information symbols resulting from a modulation scheme, e.g., quadrature amplitude modulation (QAM), with a unitary generator matrix G. Choosing the inverse Fourier transform as G, the encoding procedure is similar to orthogonal frequency-division multiplex (OFDM) modulation. The maximum a posteriori (MAP) receiver is analyzed and a suboptimum decoder based on the turbo decoding principle is derived. Simulation results show the excellent performance of the iterative decoder.     

结合6-QAM和双层LDPC码的编码调制研究

针对阶数为3 ×2p的非标准调制与纠错编码难以匹配的问题,提出了一种面向6阶正交幅度调制(QAM)的双层编码调制传输方案.在发送端,采用有限域GF(2)低密度奇偶校验(LDPC)码与GF(3)LDPC码进行分层编码,并将两种编码码字映射为6进制码字后进行6-QAM调制;在接收端,根据GF(2) LDPC码和GF(3) ...     

Design and performance of turbo Gallager codes

The most powerful channel-coding schemes, namely, those based on turbo codes and low-density parity-check (LDPC) Gallager codes, have in common the principle of iterative decoding. However, the relative coding structures and decoding algorithms are substantially different. This paper shows that recently proposed novel coding structures bridge the gap between these two schemes. In fact, with properly chosen component convolutional codes, a turbo code can be successfully decoded by means of the decoding algorithm used for LDPC codes, i.e., the belief-propagation algorithm working on the code Tanner graph. These new turbo codes are here nicknamed "turbo Gallager codes." Besides being interesting from a conceptual viewpoint, these schemes are important on the practical side because they can be decoded in a fully parallel manner. In addition to the encoding complexity advantage of turbo codes, the low decoding complexity allows the design of very efficient channel-coding schemes.     

The super-trellis structure of turbo codes

In this contribution we derive the super-trellis structure of turbo codes. We show that this structure and its associated decoding complexity depend strongly on the interleaver applied in the turbo encoder. We provide upper bounds for the super-trellis complexity. Turbo codes are usually decoded by an iterative decoding algorithm, which is suboptimum. Applying the super-trellis structure, we can optimally decode simple turbo codes and compare the associated bit-error rate results to those of iterative algorithms     

Design and decoding of optimal high-rate convolutional codes

This correspondence deals with the design and decoding of high-rate convolutional codes. After proving that every (n,n-1) convolutional code can be reduced to a structure that concatenates a block encoder associated to the parallel edges with a convolutional encoder defining the trellis section, the results of an exhaustive search for the optimal (n,n-1) convolutional codes is presented through various tables of best high-rate codes. The search is also extended to find the "best" recursive systematic convolutional encoders to be used as component encoders of parallel concatenated "turbo" codes. A decoding algorithm working on the dual code is introduced (in both multiplicative and additive form), by showing that changing in a proper way the representation of the soft information passed between constituent decoders in the iterative decoding process, the soft-input soft-output (SISO) modules of the decoder based on the dual code become equal to those used for the original code. A new technique to terminate the code trellis that significantly reduces the rate loss induced by the addition of terminating bits is described. Finally, an inverse puncturing technique applied to the highest rate "mother" code to yield a sequence of almost optimal codes with decreasing rates is proposed. Simulation results applied to the case of parallel concatenated codes show the significant advantages of the newly found codes in terms of performance and decoding complexity.     

Iterative threshold decoding without interleaving for convolutional self-doubly orthogonal codes

A novel iterative error control technique based on the threshold decoding algorithm and new convolutional self-doubly orthogonal codes is proposed. It differs from parallel concatenated turbo decoding as it uses a single convolutional encoder, a single decoder and hence no interleaver, neither at encoding nor at decoding. Decoding is performed iteratively using a single threshold decoder at each iteration, thereby providing good tradeoff between complexity, latency and error performance.     

Multilevel turbo coding with short interleavers

The impact of the interleaver, embedded in the encoder for a parallel concatenated code, called the turbo code, is studied. The known turbo codes consist of long random interleavers, whose purpose is to reduce the value of the error coefficients. It is shown that an increased minimum Hamming distance can be obtained by using a structured interleaver. For low bit-error rates (BERs), we show that the performance of turbo codes with a structured interleaver is better than that obtained with a random interleaver. Another important advantage of the structured interleaver is the short length required, which yields a short decoding delay and reduced decoding complexity (in terms of memory). We also consider the use of turbo codes as component codes in multilevel codes. Powerful coding structures that consist of two component codes are suggested. Computer simulations are performed in order to evaluate the reduction in coding gain due to suboptimal iterative decoding. From the results of these simulations we deduce that the degradation in the performance (due to suboptimal decoding) is very small     

Multilevel block codes for Rayleigh-fading channels

New multilevel block codes for Rayleigh-fading channels are presented. At high signal-to-noise ratios (SNRs), the proposed block codes can achieve better bit error performance over TCM codes, optimum for fading channels, with comparable decoder complexity and bandwidth efficiency. The code construction is based on variant length binary component block codes. As component codes for the 8-PSK multilevel block construction, the authors propose two modified forms of Reed-Muller codes giving a good trade-off between the decoder complexity and the effective code rates. Code design criteria are derived from the error performance analysis. Multistage decoding shows very slight degradation of bit error performance relative to the maximum likelihood algorithm     

An FPGA Implementation of High‐Speed Flexible 27‐Mbps 8‐StateTurbo Decoder

In this paper, we propose a flexible turbo decoding algorithm for a high order modulation scheme that uses a standard half‐rate turbo decoder designed for binary quadrature phase‐shift keying (B/QPSK) modulation. A transformation applied to the incoming I‐channel and Q‐channel symbols allows the use of an off‐the‐shelf B/QPSK turbo decoder without any modifications. Iterative codes such as turbo codes process the received symbols recursively to improve performance. As the number of iterations increases, the execution time and power consumption also increase. The proposed algorithm reduces the latency and power consumption by combination of the radix‐4, dual‐path processing, parallel decoding, and early‐stop algorithms. We implement the proposed scheme on a field‐programmable gate array and compare its decoding speed with that of a conventional decoder. The results show that the proposed flexible decoding algorithm is 6.4 times faster than the conventional scheme.     

Unveiling turbo codes: some results on parallel concatenated codingschemes

A parallel concatenated coding scheme consists of two simple constituent systematic encoders linked by an interleaver. The input bits to the first encoder are scrambled by the interleaver before entering the second encoder. The codeword of the parallel concatenated code consists of the input bits to the first encoder followed by the parity check bits of both encoders. This construction can be generalized to any number of constituent codes. Parallel concatenated schemes employing two convolutional codes as constituent codes, in connection with an iterative decoding algorithm of complexity comparable to that of the constituent codes, have been previously shown to yield remarkable coding gains close to theoretical limits. They have been named, and are known as, “turbo codes”. We propose a method to evaluate an upper bound to the bit error probability of a parallel concatenated coding scheme averaged over all interleavers of a given length. The analytical bounding technique is then used to shed some light on some crucial questions, which have been floating around in the communications community since the proposal of turbo codes     

一种短延时Turbo编码调制系统的设计

本文设计了一种比传统体制减少了一半延时的Turbo编码调制系统,介绍了交织器的相关限制.提出了一种在译码过程中对信道值的估计方法,使得外信息的计算更加趋于精确,从而提高了译码性能.这种迭代译码算法是标准格码调制译码算法的一种自然推广,同时也类似于二元Turbo码在BPSK调制下的逐比特译码算法.采用吞吐率为2bits/s/Hz的8PSK调制,比特错误率为10^-5所需的信噪比与Shannon限相距不到0.4dB.     

Joint source-channel coding using combined TCQ/CPM: iterative decoding

An iterative decoding approach to joint source and channel coding (JSCC) using combined trellis-coded quantization (TCQ) and continuous phase modulation (CPM) is proposed. The channel is assumed to be the additive white Gaussian noise channel. This iterative procedure exploits the structure of the TCQ encoder and the continuous phase modulator. The performance in terms of the signal-to-distortion ratio (SDR) is compared with that of a combined TCQ/trellis-coded modulation (TCM) system. It is shown that the combined TCQ/CPM systems are both power- and bandwidth-efficient, compared with the combined TCQ/TCM system. For source encoding rate R=2 b/sample, it is observed that the combined TCQ/CPM systems with iterative decoding working at symbol level converge faster than the systems working at bit level. The novelty of this work is the use of a soft decoder and an iterative decoding algorithm for TCQ-based JSCC systems. The combined TCQ/CPM with iterative decoding is considered for the first time.     

Achieving near-capacity on a multiple-antenna channel

Recent advancements in iterative processing of channel codes and the development of turbo codes have allowed the communications industry to achieve near-capacity on a single-antenna Gaussian or fading channel with low complexity. We show how these iterative techniques can also be used to achieve near-capacity on a multiple-antenna system where the receiver knows the channel. Combining iterative processing with multiple-antenna channels is particularly challenging because the channel capacities can be a factor of ten or more higher than their single-antenna counterparts. Using a "list" version of the sphere decoder, we provide a simple method to iteratively detect and decode any linear space-time mapping combined with any channel code that can be decoded using so-called "soft" inputs and outputs. We exemplify our technique by directly transmitting symbols that are coded with a channel code; we show that iterative processing with even this simple scheme can achieve near-capacity. We consider both simple convolutional and powerful turbo channel codes and show that excellent performance at very high data rates can be attained with either. We compare our simulation results with Shannon capacity limits for ergodic multiple-antenna channel.     

Joint estimation and compression of correlated nonbinary sources using punctured turbo codes

We propose a system to perform data compression of correlated nonbinary sources when the correlation between sources is not known, either at the encoder or the decoder. The sequences of nonbinary symbols are transformed into sequences of bits, and then source coded using punctured turbo codes, with the puncturing adjusted to achieve the desired compression rate. Each source is compressed without knowledge about the other source, and the correlation model is not assumed to be known at the encoder. The source decoder uses iterative schemes over the compressed binary sequences, and recovers the nonbinary symbol sequences from both sources. The correlation model between sources does not need to be known at the decoder, since it can be estimated jointly with the iterative decoding process. Compared with the case in which the correlation is known at the decoder, no significant performance loss is observed. The performance of the proposed scheme is close to the Slepian-Wolf theoretical limit.     

Algebraic analog decoding of linear binary codes

Bit-by-bit soft-decision decoding of binary cyclic codes is considered. A significant reduction in decoder complexity can be achieved by requiring only that the decoder correct all analog error patterns which fall within a Euclidean sphere whose radius is equal to half the minimum Euclidean distance of the code. Such a "maximum-radius" scheme is asymptotically optimum for the additive white Gaussian noise (AWGN) channel. An iterative extension of the basic algebraic analog decoding scheme is discussed, and performance curves are given for the (17,9), (21,11), and (73,45) codes on the AWGN channel.     

Performance of coded OQPSK and MIL-STD SOQPSK with iterative decoding

We show that military standard (MIL-STD) shaped-offset quadrature phase-shift keying (SOQPSK), a highly bandwidth-efficient constant-envelope modulation, can be represented in the form of a cross-correlated trellis-coded quadrature modulation. Similarly, we show that offset QPSK (OQPSK) can be decomposed into a "degraded" trellis encoder and a memoryless mapper. Based on the representations of OQPSK and MIL-STD SOQPSK as trellis-coded modulations (TCMs), we investigate the potential coding gains achievable from the application of simple outer codes to form a concatenated coding structure with iterative decoding. For MIL-STD SOQPSK, we describe the optimum receiver corresponding to its TCM form and then propose a simplified receiver. The bit-error rate (BER) performances of both receivers for uncoded and coded MIL-STD SOQPSK are simulated and compared with that of OQPSK and Feher-patented QPSK (FQPSK). The asymptotic BER performance of MIL-STD SOQPSK is also analyzed and compared with that of OQPSK and FQPSK. Simulation results show that, compared with their uncoded systems, there are significant coding gains for both OQPSK and MIL-STD SOQPSK, obtained by applying iterative decoding to either the parallel concatenated coding scheme or the serial one, even when very simple outer codes are used.     

IEEE802.16e中的BTC码编译码方案

介绍了BTC码的基本概念以及IEEE802.16e协议中的BTC编码方案,给出BTC迭代译码、每次行/列SISO译码以及扩展Hamming子码的硬判决译码方案,给出基于该译码方案的仿真结果.     

On turbo encodedBicm

The superior performance of the binary turbo codes has stimulated vigorous efforts in generating bandwidth efficient modulation schemes adhering to these codes. Several approaches for the integration of turbo-coding and modulation have emerged in recent years but none seem to dominate. In the bit interleaved coded modulation (Bicm) scheme is used to achieve high bandwidth and power efficiency, while separating coding and modulation. As is now well known, theBicm scheme achieves capacity remarkably close to the constellation channel capacity. The turbo-Bicm scheme enjoys high coding diversity (well suited for fading channels), high flexibility as well as design and implementation simplicity, while maintaining good power efficiency. The system comprises one standard turbo code, an interleaver, a mapper and a modulator at the transmitter, corresponding to a demodulator, a de-interleaver and a turbo decoder at the receiver. A modified system, which improves on performance by incorporating the demodulation in the iterative decoding procedure, is investigated, and some performance gain is demonstrated, especially for low rate codes. Information theoretic arguments for the somewhat minor potential improvement in performance are detailed. The preferred mapper and interleaver for this system are considered. Extending previous works, for higher level modulations, we analyze a system including a convolutional code, an interleaver, a differential encoder (De), a mapper and a modulator at the transmitter. As for theBpsk modulation, the serial concatenation of a convolutional code withDe outperforms the single convolutional code. The serial concatenation withDe approach is analyzed also for a turbo code, where it is found to fail in achieving performance improvement. Several structures for the serial concatenation withDe are examined. These results are substantiated through the ‘spectral thinning’ phenomena of the weight distribution of the convolutional and turbocodes.