Visible to the public Channel Coding

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Channel Coding

Channel coding, also known as Forward Error Correction, are methods for controlling errors in data transmissions over noisy or unreliable communications channels. For cybersecurity, these methods can also be used to ensure data integrity, as some of the research cited below shows. These works were presented in the first half of 2014.

  • Si, H.; Koyluoglu, O.O.; Vishwanath, S., "Polar Coding for Fading Channels: Binary and Exponential Channel Cases," Communications, IEEE Transactions on, vol.62, no.8, pp.2638, 2650, Aug. 2014. doi: 10.1109/TCOMM.2014.2345399 This work presents a polar coding scheme for fading channels, focusing primarily on fading binary symmetric and additive exponential noise channels. For fading binary symmetric channels, a hierarchical coding scheme is presented, utilizing polar coding both over channel uses and over fading blocks. The receiver uses its channel state information (CSI) to distinguish states, thus constructing an overlay erasure channel over the underlying fading channels. By using this scheme, the capacity of a fading binary symmetric channel is achieved without CSI at the transmitter. Noting that a fading AWGN channel with BPSK modulation and demodulation corresponds to a fading binary symmetric channel, this result covers a fairly large set of practically relevant channel settings. For fading additive exponential noise channels, expansion coding is used in conjunction to polar codes. Expansion coding transforms the continuous-valued channel to multiple (independent) discrete-valued ones. For each level after expansion, the approach described previously for fading binary symmetric channels is used. Both theoretical analysis and numerical results are presented, showing that the proposed coding scheme approaches the capacity in the high SNR regime. Overall, utilizing polar codes in this (hierarchical) fashion enables coding without CSI at the transmitter, while approaching the capacity with low complexity.
    Keywords: AWGN channels; Channel state information; Decoding; Encoding; Fading; Noise; Transmitters; Binary symmetric channel; channel coding; expansion coding; fading channels; polar codes (ID#:14-2651)
  • Koller, C.; Haenggi, M.; Kliewer, J.; Costello, D.J., "Joint Design of Channel and Network Coding for Star Networks Connected by Binary Symmetric Channels," Communications, IEEE Transactions on, vol.62, no.1, pp.158, 169, January 2014. doi: 10.1109/TCOMM.2013.110413.120971 In a network application, channel coding alone is not sufficient to reliably transmit a message of finite length K from a source to one or more destinations as in, e.g., file transfer. To ensure that no data is lost, it must be combined with rateless erasure correcting schemes on a higher layer, such as a time-division multiple access (TDMA) system paired with automatic repeat request (ARQ) or random linear network coding (RLNC). We consider binary channel coding on a binary symmetric channel (BSC) and q-ary RLNC for erasure correction in a star network, where Y sources send messages to each other with the help of a central relay. In this scenario RLNC has been shown to have a throughput advantage over TDMA schemes as K- and q-. In this paper we focus on finite block lengths and compare the expected throughputs of RLNC and TDMA. For a total message length of K bits, which can be subdivided into blocks of smaller size prior to channel coding, we obtain the channel code rate and the number of blocks that maximize the expected throughput of both RLNC and TDMA, and we find that TDMA is more throughput-efficient for small message lengths K and small q.
    Keywords: channel coding; network coding; time division multiple access; wireless channels; ARQ; BSC; RLNC; TDMA schemes; TDMA system; automatic repeat request; binary channel coding; binary symmetric channels; channel code rate; erasure correction; file transfer; joint design; random linear network coding; star network; star networks; time division multiple access; Automatic repeat request; Encoding; Network coding; Relays; Silicon; Throughput; Time division multiple access; Random linear network coding; joint channel and network coding; star networks (ID#:14-2652)
  • Aguerri, IE.; Varasteh, M.; Gunduz, D., "Zero-delay Joint Source-Channel Coding," Communication and Information Theory (IWCIT), 2014 Iran Workshop on, pp.1,6, 7-8 May 2014. doi: 10.1109/IWCIT.2014.6842482 In zero-delay joint source-channel coding each source sample is mapped to a channel input, and the samples are directly estimated at the receiver based on the corresponding channel output. Despite its simplicity, uncoded transmission achieves the optimal end-to-end distortion performance in some communication scenarios, significantly simplifying the encoding and decoding operations, and reducing the coding delay. Three different communication scenarios are considered here, for which uncoded transmission is shown to achieve either optimal or near-optimal performance. First, the problem of transmitting a Gaussian source over a block-fading channel with block-fading side information is considered. In this problem, uncoded linear transmission is shown to achieve the optimal performance for certain side information distributions, while separate source and channel coding fails to achieve the optimal performance. Then, uncoded transmission is shown to be optimal for transmitting correlated multivariate Gaussian sources over a multiple-input multiple-output (MIMO) channel in the low signal to noise ratio (SNR) regime. Finally, motivated by practical systems a peak-power constraint (PPC) is imposed on the transmitter's channel input. Since linear transmission is not possible in this case, nonlinear transmission schemes are proposed and shown to perform very close to the lower bound.
    Keywords: Gaussian channels; MIMO communication; block codes; combined source-channel coding; decoding; delays; fading channels; radio receivers; radio transmitters; MIMO communication; PPC; SNR; block fading channel; correlated multivariate Gaussian source transmission; decoding; encoding delay reduction; end-to-end distortion performance; information distribution; multiple input multiple output channel; nonlinear transmission scheme; peak power constraint; receiver; signal to noise ratio; transmitter channel; uncoded linear transmission; zero delay joint source channel coding; Channel coding; Decoding; Joints; MIMO; Nonlinear distortion; Signal to noise ratio (ID#:14-2653)
  • Taotao Wang; Soung Chang Liew, "Joint Channel Estimation and Channel Decoding in Physical-Layer Network Coding Systems: An EM-BP Factor Graph Framework," Wireless Communications, IEEE Transactions on, vol.13, no.4, pp.2229, 2245, April 2014. doi: 10.1109/TWC.2013.030514.131312 This paper addresses the problem of joint channel estimation and channel decoding in physical-layer network coding (PNC) systems. In PNC, multiple users transmit to a relay simultaneously. PNC channel decoding is different from conventional multi-user channel decoding: specifically, the PNC relay aims to decode a network-coded message rather than the individual messages of the users. Although prior work has shown that PNC can significantly improve the throughput of a relay network, the improvement is predicated on the availability of accurate channel estimates. Channel estimation in PNC, however, can be particularly challenging because of 1) the overlapped signals of multiple users; 2) the correlations among data symbols induced by channel coding; and 3) time-varying channels. We combine the expectation-maximization (EM) algorithm and belief propagation (BP) algorithm on a unified factor-graph framework to tackle these challenges. In this framework, channel estimation is performed by an EM subgraph, and channel decoding is performed by a BP subgraph that models a virtual encoder matched to the target of PNC channel decoding. Iterative message passing between these two subgraphs allow the optimal solutions for both to be approached progressively. We present extensive simulation results demonstrating the superiority of our PNC receivers over other PNC receivers.
    Keywords: channel coding; channel estimation; expectation-maximisation algorithm; graph theory; network coding; BP algorithm; EM algorithm;E M-BP factor graph framework; PNC channel decoding; PNC receivers; PNC systems;belief propagation; data symbols; expectation maximization joint channel estimation; multiuser channel decoding; network coded message; overlapped signals; physical layer network coding systems; unified factor graph framework; Channel estimation; Decoding; Iterative decoding; Joints; Message passing; Receivers; Relays; Physical-layer network coding; belief propagation; expectation-maximization; factor graph; message passing (ID#:14-2654)
  • Feng Cen; Fanglai Zhu, "Codeword Averaged Density Evolution For Distributed Joint Source And Channel Coding With Decoder Side Information," Communications, IET, vol.8, no.8, pp.1325,1335, May 22 2014. doi: 10.1049/iet-com.2013.1005 The authors consider applying the systematic low-density parity-check codes with the parity based approach to the lossless (or near lossless) distributed joint source channel coding (DJSCC) with the decoder side information for the non-uniform sources over the asymmetric memoryless transmission channel. By using an equivalent channel coding model, which consists of two parallel subchannels: a correlation and a transmission sub-channel, respectively, they derive the codeword averaged density evolution (DE) for the DJSCC with the decoder side information for the asymmetrically correlated non-uniform sources over the asymmetric memoryless transmission channel. A new code ensemble definition of the irregular codes is introduced to distinguish between the source and the parity variable nodes, respectively. Extensive simulations demonstrate the effectiveness of the codeword averaged DE.
    Keywords: channel coding; combined source-channel coding; decoding; parity check codes; DE; DJSCC; asymmetric memoryless transmission channel; codeword averaged density evolution; decoder side information; distributed joint source channel coding; equivalent channel coding model; parity variable nodes; systematic low-density parity-check codes (ID#:14-2655)
  • Muramatsu, J., "Channel Coding and Lossy Source Coding Using a Generator of Constrained Random Numbers," Information Theory, IEEE Transactions on, vol.60, no.5, pp.2667, 2686, May 2014. doi: 10.1109/TIT.2014.2309140 Stochastic encoders for channel coding and lossy source coding are introduced with a rate close to the fundamental limits, where the only restriction is that the channel input alphabet and the reproduction alphabet of the lossy source code are finite. Random numbers, which satisfy a condition specified by a function and its value, are used to construct stochastic encoders. The proof of the theorems is based on the hash property of an ensemble of functions, where the results are extended to general channels/sources and alternative formulas are introduced for channel capacity and the rate-distortion region. Since an ensemble of sparse matrices has a hash property, we can construct a code by using sparse matrices.
    Keywords: channel capacity; channel coding; random number generation; source coding; channel capacity; channel coding; channel input alphabet; constrained random number generator; hash property; lossy source coding; rate distortion region; reproduction alphabet;s parse matrices; stochastic encoders; Channel capacity; Channel coding; Manganese; Probability distribution; Random variables; Rate-distortion; Sparse matrices; LDPC codes; Shannon theory; channel coding; information spectrum methods; lossy source coding (ID#:14-2656)
  • Bocharova, IE.; Guillen i Fabregas, A; Kudryashov, B.D.; Martinez, A; Tauste Campo, A; Vazquez-Vilar, G., "Source-Channel Coding With Multiple Classes," Information Theory (ISIT), 2014 IEEE International Symposium on, pp.1514,1518, June 29 2014-July 4 2014. doi: 10.1109/ISIT.2014.6875086 We study a source-channel coding scheme in which source messages are assigned to classes and encoded using a channel code that depends on the class index. While each class code can be seen as a concatenation of a source code and a channel code, the overall performance improves on that of separate source-channel coding and approaches that of joint source-channel coding as the number of classes increases. The performance of this scheme is studied by means of random-coding bounds and validated by simulation of a low-complexity implementation using existing source and channel codes.
    Keywords: combined source-channel coding; class code; random coding bounds; source channel coding; source messages; AWGN; Decoding; Joints; Presses (ID#:14-2657)
  • Romero, S.M.; Hassanin, M.; Garcia-Frias, J.; Arce, G.R., "Analog Joint Source Channel Coding for Wireless Optical Communications and Image Transmission," Lightwave Technology, Journal of, vol.32, no.9, pp.1654, 1662, May1, 2014. doi: 10.1109/JLT.2014.2308136 An analog joint source channel coding (JSCC) system is developed for wireless optical communications. Source symbols are mapped directly onto channel symbols using space filling curves and then a non-linear stretching function is used to reduce distortion. Different from digital systems, the proposed scheme does not require long block lengths to achieve good performance reducing the complexity of the decoder significantly. This paper focuses on intensity-modulated direct-detection (IM/DD) optical wireless systems. First, a theoretical analysis of the IM/DD wireless optical channel is presented and the prototype communication system designed to transmit data using analog JSCC is introduced. The nonlinearities of the real channel are studied and characterized. A novel technique to mitigate the channel nonlinearities is presented. The performance of the real system follows the simulations and closely approximates the theoretical limits. The proposed system is then used for image transmission by first taking samples of a set of images using compressive sensing and then encoding the measurements using analog JSCC. Both simulation and experimental results are shown.
    Keywords: combined source-channel coding; compressed sensing; image coding; intensity modulation; optical communication; optical modulation; wireless channels; IM/DD wireless optical channel; JSCC; analog joint source channel coding; channel nonlinearities; compressive sensing; distortion reduction; image encoding; image transmission; intensity-modulated direct-detection optical wireless systems; nonlinear stretching function; space filling curves; wireless optical communications; Channel coding; Decoding; Noise; Nonlinear optics; Optical receivers; Optical transmitters; Wireless communication; Compressive sensing (CS);Shannon mappings; intensity-modulation direct-detection (IM/DD); joint source channel coding (JSCC); optical communications (ID#:14-2658)
  • Suhan Choi, "Functional Duality Between Distributed Reconstruction Source Coding and Multiple-Access Channel Coding in the Case of Correlated Messages," Communications Letters, IEEE , vol.18, no.3, pp.499, 502, March 2014. doi: 10.1109/LCOMM.2014.012214.140018 In this letter, functional duality between Distributed Reconstruction Source Coding (DRSC) with correlated messages and Multiple-Access Channel Coding (MACC) with correlated messages is considered. It is shown that under certain conditions, for a given DRSC problem with correlated messages, a functional dual MACC problem with correlated messages can be obtained, and vice versa. In particular, it is shown that the correlation structures of the messages in the two dual problems are the same. The source distortion measure and the channel cost measure for this duality are also specified.
    Keywords: channel coding; correlation theory; distortion measurement; duality (mathematics);functional analysis; source coding; DRSC; MACC; channel cost measure; correlated messages; distributed reconstruction source coding; functional duality; multiple access channel coding; source distortion measure; Bipartite graph; Channel coding; Correlation; Decoding; Distortion measurement; Source coding; Functional duality; correlated messages; distributed reconstruction source coding; multiple-access channel coding (ID#:14-2659)
  • Jie Luo, "Generalized Channel Coding Theorems For Random Multiple Access Communication," Communications Workshops (ICC), 2014 IEEE International Conference on , vol., no., pp.489,494, 10-14 June 2014. doi: 10.1109/ICCW.2014.6881246 This paper extends the channel coding theorems of [1][2] to time-slotted random multiple access communication systems with a generalized problem formulation. Assume that users choose their channel codes arbitrarily in each time slot. When the codeword length can be taken to infinity, fundamental performance limitation of the system is characterized using an achievable region defined in the space of channel code index vector each specifies the channel codes of all users. The receiver decodes the message if the code index vector happens to locate inside the achievable region and reports a collision if it falls outside the region. A generalized system error performance measure is defined as the maximum of weighted probabilities of different types of communication error events. Upper bounds on the generalized error performance measure are derived under the assumption of a finite codeword length. It is shown that "interfering users" can be introduced to model not only the impact of interference from remote transmitters, but also the impact of channel uncertainty in random access communication.
    Keywords: channel coding; decoding; probability; radio receivers; radio transmitters; radiofrequency interference; channel code index vector; channel uncertainty impact; communication error events; finite codeword length; generalized channel coding theorems; generalized system error performance measurement; interference impact; message decoding; receiver; remote transmitters; time-slotted random multiple access communication systems; weighted probabilities; Channel coding; Decoding; Error probability; Indexes; Receivers; Vectors (ID#:14-2660)
  • Hye Won Chung; Guha, S.; Lizhong Zheng, "Superadditivity of Quantum Channel Coding Rate With Finite Blocklength Quantum Measurements," Information Theory (ISIT), 2014 IEEE International Symposium on, pp.901,905, June 29 2014-July 4 2014. doi: 10.1109/ISIT.2014.6874963 We investigate superadditivity in the maximum achievable rate of reliable classical communication over a quantum channel. The maximum number of classical information bits extracted per use of the quantum channel strictly increases as the number of channel outputs jointly measured at the receiver increases. This phenomenon is called superadditivity. We provide an explanation of this phenomenon by comparing a quantum channel with a classical discrete memoryless channel (DMC) under concatenated codes. We also give a lower bound on the maximum accessible information per channel use at a finite length of quantum measurements in terms of V, which is the quantum version of channel dispersion, and C, the classical capacity of the quantum channel.
    Keywords: channel coding; concatenated codes; DMC; concatenated codes; discrete memoryless channel; finite blocklength quantum measurements; quantum channel; quantum channel coding rate; superadditivity; Binary phase shift keying; Concatenated codes; Decoding; Length measurement; Photonics; Quantum mechanics; Receivers (ID#:14-2661)
  • Vaezi, M.; Labeau, F., "Distributed Source-Channel Coding Based on Real-Field BCH Codes," Signal Processing, IEEE Transactions on, vol.62, no.5, pp.1171,1184, March 1, 2014. doi: 10.1109/TSP.2014.2300039 We use real-number codes to compress statistically dependent sources and establish a new framework for distributed lossy source coding in which we compress sources before, rather than after, quantization. This change in the order of binning and quantization blocks makes it possible to model the correlation between continuous-valued sources more realistically and compensate for the quantization error partially. We then focus on the asymmetric case, i.e., lossy source coding with side information at the decoder. The encoding and decoding procedures are described in detail for a class of real-number codes called discrete Fourier transform (DFT) codes, both for the syndrome- and parity-based approaches. We leverage subspace-based decoding to improve the decoding and by extending it we are able to perform distributed source coding in a rate-adaptive fashion to further improve the decoding performance when the statistical dependency between sources is unknown. We also extend the parity-based approach to the case where the transmission channel is noisy and thus we perform distributed joint source-channel coding in this context. The proposed system is well suited for low-delay communications, as the mean-squared reconstruction error (MSE) is shown to be reasonably low for very short block length.
    Keywords: BCH codes; combined source-channel coding; correlation methods; decoding; discrete Fourier transforms; mean square error methods; quantisation (signal); DFT codes; MSE; discrete Fourier transform; distributed lossy source coding; distributed source-channel coding; mean-squared reconstruction error; quantization blocks; quantization error; real-field BCH codes; real-number codes; subspace-based decoding; transmission channel; Correlation; Decoding; Delays; Discrete Fourier transforms; Quantization (signal);Source coding; BCH-DFT codes; distributed source coding; joint source-channel coding; parity; real-number codes; syndrome (ID#:14-2662)
  • Tao Wang; Wenbo Zhang; Maunder, R.G.; Hanzo, L., "Near-Capacity Joint Source and Channel Coding of Symbol Values from an Infinite Source Set Using Elias Gamma Error Correction Codes," Communications, IEEE Transactions on, vol.62, no.1, pp.280,292, January 2014. doi: 10.1109/TCOMM.2013.120213.130301 In this paper we propose a novel low-complexity Joint Source and Channel Code (JSCC), which we refer to as the Elias Gamma Error Correction (EGEC) code. Like the recently-proposed Unary Error Correction (UEC) code, this facilitates the practical near-capacity transmission of symbol values that are randomly selected from a set having an infinite cardinality, such as the set of all positive integers. However, in contrast to the UEC code, our EGEC code is a universal code, facilitating the transmission of symbol values that are randomly selected using any monotonic probability distribution. When the source symbols obey a particular zeta probability distribution, our EGEC scheme is shown to offer a 3.4 dB gain over a UEC benchmarker, when Quaternary Phase Shift Keying (QPSK) modulation is employed for transmission over an uncorrelated narrowband Rayleigh fading channel. In the case of another zeta probability distribution, our EGEC scheme offers a 1.9 dB gain over a Separate Source and Channel Coding (SSCC) benchmarker.
    Keywords: Rayleigh channels; channel coding; error correction codes; phase shift keying; source coding; statistical distributions; EGEC code; Infinite Source Set; QPSK modulation; UEC code; elias gamma error correction codes; monotonic probability distribution; near-capacity joint source and channel coding; near-capacity transmission; novel low-complexity joint source and channel code; quaternary phase shift keying modulation; symbol values; unary error correction code; uncorrelated narrowband Rayleigh fading channel; universal code; zeta probability distribution; Decoding; Encoding; Error correction codes; Phase shift keying; Probability distribution; Transmitters; Vectors; Source coding; channel capacity; channel coding; iterative decoding (ID#:14-2663)


Articles listed on these pages have been found on publicly available internet pages and are cited with links to those pages. Some of the information included herein has been reprinted with permission from the authors or data repositories. Direct any requests via Email to SoS.Project (at) for removal of the links or modifications to specific citations. Please include the ID# of the specific citation in your correspondence.