Design of parallel concatenated convolutional codes

A parallel concatenated convolutional coding scheme consists of two constituent systematic: convolutional encoders linked by an interleaver. The information bits at the input of the first encoder are scrambled by the interleaver before entering the second encoder. The codewords of the parallel concatenated code consist of the information bits followed by the parity check bits of both encoders. Parallel concatenated codes (turbo codes), decoded through an iterative decoding algorithm of relatively low complexity, have been shown to yield remarkable coding gains close to theoretical limits. We characterize the separate contributions that the interleaver length and constituent codes give to the overall performance of the parallel concatenated code, and present some guidelines for the optimal design of the constituent convolutional codes     

Analysis, design, and iterative decoding of double seriallyconcatenated codes with interleavers

A double serially concatenated code with two interleavers consists of the cascade of an outer encoder, an interleaver permuting the outer codeword bits, a middle encoder, another interleaver permuting the middle codeword bits, and an inner encoder whose input words are the permuted middle codewords. The construction can be generalized to h cascaded encoders separated by h-1 interleavers, where h>3. We obtain upper bounds to the average maximum likelihood bit-error probability of double serially concatenated block and convolutional coding schemes. Then, we derive design guidelines for the outer, middle, and inner codes that maximize the interleaver gain and the asymptotic slope of the error probability curves. Finally, we propose a low-complexity iterative decoding algorithm. Comparisons with parallel concatenated convolutional codes, known as “turbo codes”, and with the proposed serially concatenated convolutional codes are also presented, showing that in some cases, the new schemes offer better performance     

Serial concatenation of interleaved codes: performance analysis,design, and iterative decoding

A serially concatenated code with interleaver consists of the cascade of an outer encoder, an interleaver permuting the outer codewords bits, and an inner encoder whose input words are the permuted outer codewords. The construction can be generalized to h cascaded encoders separated by h-1 interleavers. We obtain upper bounds to the average maximum-likelihood bit error probability of serially concatenated block and convolutional coding schemes. Then, we derive design guidelines for the outer and inner encoders that maximize the interleaver gain and the asymptotic slope of the error probability curves. Finally, we propose a new, low-complexity iterative decoding algorithm. Throughout the paper, extensive comparisons with parallel concatenated convolutional codes known as “turbo codes” are performed, showing that the new scheme can offer superior performance     

Turbo-encoder design for symbol-interleaved parallel concatenatedtrellis-coded modulation

This paper addresses turbo-encoder design for coding with high spectral efficiency using parallel concatenated trellis-coded modulation and symbol interleaving. The turbo-encoder design involves the constituent encoder design and the interleaver design. The constituent encoders are optimized for symbol-wise effective free distance, and each has an infinite symbol-wise impulse response. We identify the canonical structures for the constituent encoder search space. In many cases of practical interest, the optimal structure for these constituent encoders connects the memory elements in a single row. This single row generally applies to turbo code constituent encoders for parallel concatenation and is not restricted to symbol interleaving. To lower the error floor, a new semi-random interleaver design criteria and a construction method extends the spread-interleaver concept introduced by Divsalar and Pollara (1995). Simulation results show that the proposed system employing symbol interleaving can converge at a lower signal-to-noise ratio than previously reported systems. We report simulation results between 0.5 and 0.6 db from constrained capacity for rates of 2 and 4 bits/s/Hz     

Performance of continuous and blockwise decoded turbo codes

In this letter we define and evaluate the average maximum-likelihood performance of the three ways of co-decoding turbo codes. In all cases the information sequence is split into blocks of N bits (N being the length of the interleaver used by the turbo code), that are encoded by the first constituent encoder and, after interleaving, by the second encoder. In the first operation mode, both constituent encoders work in a continuous fashion, whereas in the second, at the end of each block, a suitably chosen sequence of bits is appended to the information block in order to terminate the trellises of both constituent codes. In the third mode, the operation is similar to the second, but, instead of trellis termination, both constituent encoders are simply reset     

Nonsystematic turbo codes

In this paper, we introduce the concept of nonsystematic turbo codes and compare them with classical systematic turbo codes. Nonsystematic turbo codes can achieve lower error floors than systematic turbo codes because of their superior effective free distance properties. Moreover, they can achieve comparable performance in the waterfall region if the nonsystematic constituent encoder has a low-weight feedforward inverse. A uniform interleaver analysis is used to show that rate R=1/3 turbo codes using nonsystematic constituent encoders have larger effective free distances than when systematic constituent encoders are used. Also, mutual information-based transfer characteristics and extrinsic information transfer charts are used to show that rate R=1/3 turbo codes with nonsystematic constituent encoders having low-weight feedforward inverses achieve convergence thresholds comparable to those achieved with systematic constituent encoders. Catastrophic encoders, which do not possess a feedforward inverse, are shown to be capable of achieving low convergence thresholds by doping the code with a small fraction of systematic bits. Finally, we give tables of good nonsystematic turbo codes and present simulation results comparing the performance of systematic and nonsystematic turbo codes.     

Parallel concatenated codes with unequal error protection

We show how parallel concatenated codes (PCCs, also known as “turbo codes”) can be endowed with unequal error protection (UEP). Given the two component encoders of the PCC encoder and the desired interleaver size, UEP is achieved by: (1) suitably positioning the different importance classes of information symbols into the encoder input frame; (2) puncturing the PCC redundancy symbols with a nonuniform pattern; and (3) choosing the interleaver of the PCC encoder in a class of interleavers that guarantees isolation of the importance classes. By controlling the amount of redundancy assigned to each importance class and the class positioning in the input frame, a whole family of UEP PCCs with different UEP levels can be obtained from the same component encoders and interleaver size. From a practical viewpoint, a family of UEP PCCs can be decoded by the same “turbo” iterative decoder, provided that the decoder hardware implementation allows for programmable puncturing and interleaving     

Assembled space-time turbo trellis codes

A novel full rate space-time turbo trellis code, referred to as an assembled space-time turbo trellis code (ASTTTC), is presented in this paper. For this scheme, input information binary sequences are first encoded using two parallel concatenated convolutional encoders. The encoder outputs are split into four parallel streams and each of them is modulated by a QPSK modulator. The modulated symbols are assembled by a predefined linear function rather than punctured as in the standard schemes. This results in a lower code rate and a higher coding gain over time-varying fading channels. An extended two-dimensional (2-D) log-MAP (maximum a posteriori probability) decoding algorithm, which simultaneously calculates two a posteriori probabilities (APP), is developed to decode the proposed scheme. Simulation results show that, under the same conditions, the proposed code considerably outperforms the conventional space-time turbo codes over time-varying fading channels.     

Turbo-coded optical direct-detection CDMA system with PPMmodulation

The performance of an optical code division multiple access (CDMA) system with turbo coding is analyzed and simulated. Turbo codes are parallel concatenated convolutional codes (PCCCs) in which the information bits are first encoded by a recursive systematic convolutional code, and then, after passing through an interleaver, are encoded by a second systematic convolutional encoder. Turbo coding is superimposed on an intensity-modulated optical channel with pulse-position modulation (PPM) and direct detection of the received optical signal, and the performance is evaluated in terms of an upper bound on bit error probability. From the simulation results, it is seen that turbo coding offers considerable coding gain over other methods, with reasonable encoding/decoding complexity. Also, it is demonstrated that, for a fixed code rate, the performance of the optical CDMA system can be substantially improved by increasing the interleaver length and the number of iterations. Serially concatenated convolutional codes (SCCCs) are also considered, and are shown to perform comparably to PCCC in general and better than PCCCs for the case of large signal photocounts. The results in this paper can be applied, for example, to indoor optical wireless LANs     

Simultaneous zero-tailing of parallel concatenated codes

In a parallel concatenated convolutional code, an information sequence is encoded by a convolutional encoder, and an interleaved version of the information sequence is encoded by another convolutional encoder. We discuss the situation in which we require both convolutional encoders to end in the all-zero state. To do so, we have to split an information word in two parts. One part contains the true information bits, and the second part contains the so-called tail bits, which are special bits with values computed such that both encoders end in the all-zero state. Depending on the interleaver, a different number of tail bits are needed. By using a constructive method, we give a characterization of all interleavers for a prescribed number of tail bits. We explain the method of encoding. In addition, simulations have been carried out to investigate the performance of codes resulting from simultaneous zero-tailing. This shows that simultaneous zero-tailing is similar in performance as compared to previously known zero-tailing methods (but with fewer trellis termination bits) and that it is better than zero-tailing just one of the encoders.     

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     

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.     

Zigzag codes and concatenated zigzag codes

This paper introduces a family of error-correcting codes called zigzag codes. A zigzag code is described by a highly structured zigzag graph. Due to the structural properties of the graph, very low-complexity soft-in/soft-out decoding rules can be implemented. We present a decoding rule, based on the Max-Log-APP (MLA) formulation, which requires a total of only 20 addition-equivalent operations per information bit, per iteration. Simulation of a rate-1/2 concatenated zigzag code with four constituent encoders with interleaver length 65 536, yields a bit error rate (BER) of 10^-5 at 0.9 dB and 1.3 dB away from the Shannon limit by optimal (APP) and low-cost suboptimal (MLA) decoders, respectively. A union bound analysis of the bit error probability of the zigzag code is presented. It is shown that the union bounds for these codes can be generated very efficiently. It is also illustrated that, for a fixed interleaver size, the concatenated code has increased code potential as the number of constituent encoders increases. Finally, the analysis shows that zigzag codes with four or more constituent encoders have lower error floors than comparable turbo codes with two constituent encoders     

Concatenated codes for fading channels based on recursive space-time trellis codes

We propose a class of codes which combine the principles of turbo coding and space-time trellis codes. It is first shown that several classes of space-time codes have an equivalent recursive realization. This fact is then exploited to design serial concatenated coding schemes with an outer code, interleaver, and an inner recursive space-time encoder. Two solutions are proposed in this paper - the use of convolutional outer codes aimed mainly to improve the power efficiency and the use of very high-rate outer codes to obtain significant improvement in power efficiency with a marginal decrease in spectral efficiency. We show that single parity check based turbo product codes are a good candidate for very high-rate outer codes. Finally, we propose an automatic repeat request scheme based on recursive realizations of space-time codes and show that the proposed scheme provides significant reduction in frame error rate.     

Turbo decoding for partial response channels

The partial response channel can be viewed as a rate-1 encoder in which the output alphabet differs from the input alphabet. In serially concatenated coding schemes, the partial response channel can serve as the inner encoder. Previous work on the application of turbo decoding techniques to partial response channels has focused on using a parallel concatenation of convolutional encoders as the outer code and the partial response channel as the inner code. This system requires three a posteriori probability (APP) detectors-one matched to the channel and two matched to the constituent encoders. A simplified system is presented that uses as its outer code a single convolutional code and as its inner code the partial response channel. The simplified system requires only two APP detectors, offering significant savings in complexity and computation time. This single convolutional code system is shown to perform as well as the more complicated system, offering substantial gains over uncoded systems. Simulation results for three magnetic recording channel models are presented: a partial response channel with additive white Gaussian noise, an equalized Lorentzian channel model, and a media noise model called the microtrack model. Since the use of an outer Reed-Solomon code is anticipated in an actual system, the burst-error statistics are investigated. System performance with various interleaver designs and precoders is also investigated     

A soft-input soft-output APP module for iterative decoding ofconcatenated codes

Concatenated coding schemes consist of the combination of two or more simple constituent encoders and interleavers. The parallel concatenation known as “turbo code” has been shown to yield remarkable coding gains close to theoretical limits, yet admitting a relatively simple iterative decoding technique. The recently proposed serial concatenation of interleaved codes may offer superior performance to that of turbo codes. In both coding schemes, the core of the iterative decoding structure is a soft-input soft-output (SISO) a posteriori probability (APP) module. In this letter, we describe the SISO APP module that updates the APP's corresponding to the input and the output bits, of a code, and show how to embed it into an iterative decoder for a new hybrid concatenation of three codes, to fully exploit the benefits of the proposed SISO APP module     

The Minimum Distance of Turbo-Like Codes

Worst-case upper bounds are derived on the minimum distance of parallel concatenated turbo codes, serially concatenated convolutional codes, repeat-accumulate codes, repeat-convolute codes, and generalizations of these codes obtained by allowing nonlinear and large-memory constituent codes. It is shown that parallel-concatenated turbo codes and repeat-convolute codes with sub-linear memory are asymptotically bad. It is also shown that depth-two serially concatenated codes with constant-memory outer codes and sublinear-memory inner codes are asymptotically bad. Most of these upper bounds hold even when the convolutional encoders are replaced by general finite-state automata encoders. In contrast, it is proven that depth-three serially concatenated codes obtained by concatenating a repetition code with two accumulator codes through random permutations can be asymptotically good.      

Stream-oriented turbo codes

This work considers the design and performance of a stream-oriented approach to turbo codes which avoids the need for data framing. The stream paradigm applies to both serial and parallel turbo codes using continuous, free-running constituent encoders along with continuous, periodic interleavers. A stream-oriented turbo code based on parallel concatenated convolutional codes (PCCC) is considered and interleaver design criteria are developed for both block and nonblock periodic interleavers. Specifically, several nonblock interleavers, including convolutional interleavers, are considered. Interleaver design rules are verified using simulations where it is shown that nonblock interleavers with small-to-moderate delay and small synchronization ambiguity can outperform block interleavers of comparable delay. For large-delay designs, nonblock interleavers are found which perform within 0.8 dB of the capacity limit with a synchronization ambiguity of N=11     

Analysis and Design of Power-Efficient Coding Schemes With Parallel Concatenated Convolutional Codes

Analysis and Design of Power-Efficient Coding Schemes With Parallel Concatenated Convolutional Codes In the low signal-to-noise ratio regime, the performance of concatenated coding schemes is limited by the convergence properties of the iterative decoder. Idealizing the model of iterative decoding by an independence assumption, which represents the case in which the codeword length is infinitely large, leads to analyzable structures from which this performance limit can be predicted. Mutual information-transfer characteristics of the constituent coding schemes comprising convolutional encoders and soft-in/soft-out decoders have been shown to be sufficient to characterize the components within this model. Analyzing serial and parallel concatenations is possible just by these characteristics. In this paper, we extend the method of extrinsic information transfer charts that is limited to the case of a concatenation of two component codes, to the case of multiple turbo codes. Multiple turbo codes are parallel concatenations of three or more constituent codes, which, in general, may not be identical and may not have identical code rates. For the construction of low-rate codes, this concept seems to be very favorable, as power efficiencies close to the Shannon limit can be achieved with reasonable complexity.     

Transmission of nonuniform memoryless sources via nonsystematic turbo codes

We investigate the joint source-channel coding problem of transmitting nonuniform memoryless sources over binary phase-shift keying-modulated additive white Gaussian noise and Rayleigh fading channels via turbo codes. In contrast to previous work, recursive nonsystematic convolutional encoders are proposed as the constituent encoders for heavily biased sources. We prove that under certain conditions, and when the length of the input source sequence tends to infinity, the encoder state distribution and the marginal output distribution of each constituent recursive convolutional encoder become asymptotically uniform, regardless of the degree of source nonuniformity. We also give a conjecture (which is empirically validated) on the condition for the higher order distribution of the encoder output to be asymptotically uniform, irrespective of the source distribution. Consequently, these conditions serve as design criteria for the choice of good encoder structures. As a result, the outputs of our selected nonsystematic turbo codes are suitably matched to the channel input, since a uniformly distributed input maximizes the channel mutual information, and hence, achieves capacity. Simulation results show substantial gains by the nonsystematic codes over previously designed systematic turbo codes; furthermore, their performance is within 0.74-1.17 dB from the Shannon limit. Finally, we compare our joint source-channel coding system with two tandem schemes which employ a fourth-order Huffman code (performing near-optimal data compression) and a turbo code that either gives excellent waterfall bit-error rate (BER) performance or good error-floor performance. At the same overall transmission rate, our system offers robust and superior performance at low BERs (< 10/sup -4/), while its complexity is lower.