Obtaining extra coding gain for short codes by block Markov superposition transmission

Ma, Xiao; Liang, Chulong; Huang, Kechao; Zhuang, Qiutao

doi:10.1109/isit.2013.6620587

Cited by 34 publications

(36 citation statements)

References 24 publications

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“…At time t, the sliding-window decoding (SWD) algorithm, which is an iterative message processing/passing algorithm over the corresponding normal graph of the BMST system [10], is performed with a decoding delay d and a maximum iteration number I max to recover u (t−d) by taking Pr{C Fig. 2 shows the normal graph of a BMST system with L = 4 and m = 2.…”

Section: B Decoding Of Bmstmentioning

confidence: 99%

Spatial Coupling of Generator Matrices: A General Approach to Design Good Codes at a Target BER

Liang

Zhuang

et al. 2014

IEEE Trans. Commun.

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For any given short code (referred to as the basic code), block Markov superposition transmission (BMST) provides a simple way to obtain predictable extra coding gain by spatially coupling the generator matrix of the basic code. This paper presents a systematic design methodology for BMST systems to approach the channel capacity at any given target bit error rate (BER) of interest. To simplify the design, we choose the basic code as the Cartesian product of a short block code. The encoding memory is then inferred from the genie-aided lower bound according to the performance gap of the short block code to the corresponding Shannon limit at the target BER. In addition to the sliding-window decoding algorithm, we propose to perform one more phase decoding to remove residual (rare) errors. A new technique that assumes a noisy genie is proposed to upper bound the performance. Under some mild assumptions, these genie-aided bounds can be used to predict the performance of the proposed two-phase decoding algorithm in the extremely low BER region. Using the Cartesian product of a repetition code as the basic code, we construct a BMST system with an encoding memory 30 whose performance at the BER of 10 −15 can be predicted within 1 dB away from the Shannon limit over the binary-input additive white Gaussian noise channel.Index Terms-Big convolutional codes, block Markov superposition transmission (BMST), capacity-approaching codes, genieaided bounds, spatial coupling, two-phase decoding (TPD).

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Section: B Decoding Of Bmstmentioning

confidence: 99%

Spatial Coupling of Generator Matrices: A General Approach to Design Good Codes at a Target BER

Liang

Zhuang

et al. 2014

IEEE Trans. Commun.

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“…Similar to the analyses in [12,13], for a given time t, if all the transmitted data g( e )(O :::; R :::; L -1, R cJ t) but g (t) are known to the receiver, the BMST system is reduced to an equivalent system similar to that in Fig. 3 of [13], where the only difference is that the high-order mapping 'P is replaced by the signal mapping.…”

Section: B Genie-aided Lower Boundmentioning

confidence: 66%

“…Let 'f! [71" k] be a binary linear code of length 71, and dimension k, which is referred to as the basic code [12,13]. We assume that n = lvlcN B for some positive integer B.…”

Section: A Encoding/decoding Algorithmmentioning

confidence: 99%

“…Recently, a coding scheme called block Markov super position transmission (BMST) [12][13][14] was proposed. The performance of the BMST codes can be predicted by a simple genie-aided bound [14], and the design of BMST codes is flexible in the sense that any code of any rate with fast encoding algorithm and efficient soft-in soft-out (SISO) decoding algorithm can be taken as the basic code [14].…”

Section: Introductionmentioning

confidence: 99%

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Block Markov superposition transmission for high-speed railway wireless communication systems

Wang

Zhang

2015

2015 International Workshop on High Mobility Wireless Communications (HMWC)

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Ahstract-The focus of this paper is coded orthogonal frequen cy division multiplexing (OFDM) system for high-speed railway wireless communication based on block Markov superposition transmission (BMST). The effect of Doppler spreading destroys the orthogonality among subcarriers, resulting in intercarrier interference (leI) in the OFDM systems. In order to mitigate the leI and get the soft information easily, we present a simple soft output algorithm based on zero forcing (ZF) equalization, and the soft information is given to the soft-in soft-out (SISO) demapper. We combine the OFDM system with BMST code, which can be easily designed for any given code rate with a predictable performance lower bound. Based on the iterative sliding-window decoding algorithm, BMST scheme outperforms the convolutional code (eC) scheme in the OFDM system for quadrature phase-shift keying (QPSK) and 16-quadrature ampli tude modulation (QAM). Numerical results show that the BMST OFDM system performs well over doubly selective channels. IndexTerms-Block Markov superposition transmis sion (BMST), doubly selective channels, high-speed railway, iterative sliding-window decoding, orthogonal frequency division multiplexing (OFDM), zero forcing equalization.

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“…We present the effect of channel estimation errors on the capacity bound of the high-mobility channel. In order to verifying our results, a class of spatially coupled codes, block Markov superposition transmission (BMST) code, first proposed in [12], is adopted to the time-varying OFDM system. BER performance curves are provided to analyze whether the conclusions are valid.…”

Section: Introductionmentioning

confidence: 88%

Capacity Bound and Ber Performance of Ofdm System in High-Mobility Scenarios

Lei¹

2017

Jour. Math. Sci. Adv. Appl.

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In this paper, we investigate the effect of velocity and channel information on the capacity of orthogonal frequency division multiplexing (OFDM) system in very rapidly time-varying fading channels. Lower bounds on the capacity of OFDM system in fast time-varying channels with perfect and imperfect channel state information (CSI) are derived. Simulation results show two main conclusions. One is that the capacity bounds change very little with increasing velocity in the channel with perfect CSI. Another is that the transmission performance is decreased quickly by the increased channel estimation errors due to high mobilities in the channel with imperfect CSI. Furthermore, we adopt block Markov superposition transmission (BMST) code to verify the conclusions.

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Obtaining extra coding gain for short codes by block Markov superposition transmission

Cited by 34 publications

References 24 publications

Spatial Coupling of Generator Matrices: A General Approach to Design Good Codes at a Target BER

Spatial Coupling of Generator Matrices: A General Approach to Design Good Codes at a Target BER

Block Markov superposition transmission for high-speed railway wireless communication systems

Capacity Bound and Ber Performance of Ofdm System in High-Mobility Scenarios

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