10,657 research outputs found

    Near-capacity iterative decoding of binary self-concatenated codes using soft decision demapping and 3-D EXIT charts

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    In this paper 3-D Extrinsic Information Transfer (EXIT) charts are used to design binary Self-Concatenated Convolutional Codes employing Iterative Decoding (SECCC-ID), exchanging extrinsic information with the soft-decision demapper to approach the channel capacity. Recursive Systematic Convolutional (RSC) codes are selected as constituent codes, an interleaver is used for randomising the extrinsic information exchange of the constituent codes, while a puncturer helps to increase the achievable bandwidth efficiency. The convergence behaviour of the decoder is analysed with the aid of bit-based 3-D EXIT charts, for accurately calculating the operating EbN0 threshold, especially when SP based soft demapper is employed. Finally, we propose an attractive system configuration, which is capable of operating within about 1 dB from the channel capacity

    Exit chart analysis of parallel data convolutional codes

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    We recently proposed a new class of turbo-like codes called parallel data convolutional codes (PDCCs). The distinct characteristics of PDCCs include parallel data input bits and a self-iterative soft-in/soft-out a posteriori probability(APP) decoder. In this paper, we analyse this turbolike code by means of the extrinsic information transfer chart (EXIT chart). Our results show that the threshold Eb/N0 point for a rate 1/2 8-state PDCC is 0.6 dB, which is the same as the threshold point for a punctured rate 1/2 16-state parallel concatenated convolutional code (turbo code)

    Multi-level Turbo Decoding Assisted Soft Combining Aided Hybrid ARQ

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    Hybrid Automatic Repeat reQuest (ARQ) plays an essential role in error control. Combining the incorrectly received packet replicas in hybrid ARQ has been shown to reduce the resultant error probability, while improving the achievable throughput. Hence, in this contribution, multi-level turbo codes have been amalgamated both with hybrid ARQ and efficient soft combining techniques for taking into account the Log- Likelihood Ratios (LLRs) of retransmitted packet replicas. In this paper, we present a soft combining aided hybrid ARQ scheme based on multi-level turbo codes, which avoid the capacity loss of the twin-level turbo codes that are typically employed in hybrid ARQ schemes. More specifically, the proposed receiver dynamically appends an additional parallel concatenated Bahl, Cocke, Jelinek and Raviv (BCJR) algorithm based decoder in order to fully exploit each retransmission, thereby forming a multi-level turbo decoder. Therefore, all the extrinsic information acquired during the previous BCJR operations will be used as a priori information by the additional BCJR decoders, whilst their soft output iteratively enhances the a posteriori information generated by the previous decoding stages. We also present link- level Packet Loss Ratio (PLR) and throughput results, which demonstrate that our scheme outperforms some of the previously proposed benchmarks

    Serial-Turbo-Trellis-Coded Modulation with Rate-1 Inner Code

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    Serially concatenated turbo codes have been proposed to satisfy requirements for low bit- and word-error rates and for low (in comparison with related previous codes) complexity of coding and decoding algorithms and thus low complexity of coding and decoding circuitry. These codes are applicable to such high-level modulations as octonary phase-shift keying (8PSK) and 16-state quadrature amplitude modulation (16QAM); the signal product obtained by applying one of these codes to one of these modulations is denoted, generally, as serially concatenated trellis-coded modulation (SCTCM). These codes could be particularly beneficial for communication systems that must be designed and operated subject to limitations on bandwidth and power. Some background information is prerequisite to a meaningful summary of this development. Trellis-coded modulation (TCM) is now a well-established technique in digital communications. A turbo code combines binary component codes (which typically include trellis codes) with interleaving. A turbo code of the type that has been studied prior to this development is composed of parallel concatenated convolutional codes (PCCCs) implemented by two or more constituent systematic encoders joined through one or more interleavers. The input information bits feed the first encoder and, after having been scrambled by the interleaver, enter the second encoder. A code word of a parallel concatenated code consists of the input bits to the first encoder followed by the parity check bits of both encoders. The suboptimal iterative decoding structure for such a code is modular, and consists of a set of concatenated decoding modules one for each constituent code connected through an interleaver identical to the one in the encoder side. Each decoder performs weighted soft decoding of the input sequence. PCCCs yield very large coding gains at the cost of a reduction in the data rate and/or an increase in bandwidth

    Orthogonal Multiple Access with Correlated Sources: Feasible Region and Pragmatic Schemes

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    In this paper, we consider orthogonal multiple access coding schemes, where correlated sources are encoded in a distributed fashion and transmitted, through additive white Gaussian noise (AWGN) channels, to an access point (AP). At the AP, component decoders, associated with the source encoders, iteratively exchange soft information by taking into account the source correlation. The first goal of this paper is to investigate the ultimate achievable performance limits in terms of a multi-dimensional feasible region in the space of channel parameters, deriving insights on the impact of the number of sources. The second goal is the design of pragmatic schemes, where the sources use "off-the-shelf" channel codes. In order to analyze the performance of given coding schemes, we propose an extrinsic information transfer (EXIT)-based approach, which allows to determine the corresponding multi-dimensional feasible regions. On the basis of the proposed analytical framework, the performance of pragmatic coded schemes, based on serially concatenated convolutional codes (SCCCs), is discussed

    Real-time minimal bit error probability decoding of convolutional codes

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    A recursive procedure is derived for decoding of rate R=1/n binary convolutional codes which minimizes the probability of the individual decoding decisions for each information bit subject to the constraint that the decoding delay be limited to Delta branches. This new decoding algorithm is similar to, but somewhat more complex than, the Viterbi decoding algorithm. A real-time, i.e. fixed decoding delay, version of the Viterbi algorithm is also developed and used for comparison to the new algorithm on simulated channels. It is shown that the new algorithm offers advantages over Viterbi decoding in soft-decision applications such as in the inner coding system for concatenated coding
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