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We consider the concatenation of a convolutional code (CC) with an optimized cyclic redundancy check (CRC) code as a promising paradigm for good short blocklength codes. The resulting CRC-aided convolutional code naturally permits the use…

Information Theory · Computer Science 2022-02-11 Hengjie Yang , Ethan Liang , Minghao Pan , Richard Wesel

Recently, rate-$1/\omega$ zero-terminated and tail-biting convolutional codes (ZTCCs and TBCCs) with cyclic-redundancy-check (CRC)-aided list decoding have been shown to closely approach the random-coding union (RCU) bound for short…

Information Theory · Computer Science 2022-06-09 Wenhui Sui , Hengjie Yang , Brendan Towell , Ava Asmani , Richard D. Wesel

Recently, rate-1/n zero-terminated (ZT) and tail-biting (TB) convolutional codes (CCs) with cyclic redundancy check (CRC)-aided list decoding have been shown to closely approach the random-coding union (RCU) bound for short blocklengths.…

Information Theory · Computer Science 2023-10-11 Wenhui Sui , Brendan Towell , Ava Asmani , Hengjie Yang , Holden Grissett , Richard D. Wesel

Polarization-adjusted convolutional (PAC) codes are special concatenated codes in which we employ a one-to-one convolutional transform as a pre-coding step before the polar transform. In this scheme, the polar transform (as a mapper) and…

Information Theory · Computer Science 2020-07-13 Mohammad Rowshan , Emanuele Viterbo

Recently a powerful class of rate-compatible serially concatenated convolutional codes (SCCCs) have been proposed based on minimizing analytical upper bounds on the error probability in the error floor region. Here this class of codes is…

Information Theory · Computer Science 2007-07-13 Alexandre Graell i Amat , Fredrik Brannstrom , Lars K. Rasmussen

This paper is concerned with the ordered statistic decoding with local constraints (LC-OSD) of binary linear block codes, which is a near maximum-likelihood decoding algorithm. Compared with the conventional OSD, the LC-OSD significantly…

Information Theory · Computer Science 2024-01-31 Jifan Liang , Xiao Ma

As the first error correction codes provably achieving the symmetric capacity of binary-input discrete memory-less channels (B-DMCs), polar codes have been recently chosen by 3GPP for eMBB control channel. Among existing algorithms,…

Signal Processing · Electrical Eng. & Systems 2018-03-19 Huayi Zhou , Xiao Liang , Liping Li , Zaichen Zhang , Xiaohu You , Chuan Zhang

In this paper, we provide a new approach to the analytical estimation of the bit-error rate (BER) for convolutional codes for Viterbi decoding in the binary symmetric channel (BSC). The expressions we obtained for lower and upper BER bounds…

Information Theory · Computer Science 2022-11-22 Anastasia Kurmukova , Fedor Ivanov , Victor Zyablov

A Viterbi-like decoding algorithm is proposed in this paper for generalized convolutional network error correction coding. Different from classical Viterbi algorithm, our decoding algorithm is based on minimum error weight rather than the…

Information Theory · Computer Science 2019-02-12 Hengjie Yang , Wangmei Guo

Sequential decoding, commonly applied to substitution channels, is a sub-optimal alternative to Viterbi decoding with significantly reduced memory costs. In this work, a sequential decoder for convolutional codes over channels that are…

Information Theory · Computer Science 2026-04-02 Anisha Banerjee , Andreas Lenz , Antonia Wachter-Zeh

This paper explores list decoding of convolutional and polar codes for short messages such as those found in the 5G physical broadcast channel. A cyclic redundancy check (CRC) is used to select a codeword from a list of likely codewords.…

Information Theory · Computer Science 2022-01-21 Jacob King , Alexandra Kwon , Hengjie Yang , William Ryan , Richard D. Wesel

A successive cancellation list (SCL) decoder with limited list size for polar codes can not be analyzed as a successive cancellation (SC) decoder, nor as a maximum likelihood (ML) decoder, due to the complicated decoding errors caused by…

Information Theory · Computer Science 2019-03-25 Tao Wang , Daiming Qu , Tao Jiang

Tail-biting convolutional codes extend the classical zero-termination convolutional codes: Both encoding schemes force the equality of start and end states, but under the tail-biting each state is a valid termination. This paper proposes a…

Information Theory · Computer Science 2021-02-03 Tomer Raviv , Asaf Schwartz , Yair Be'ery

Random linear network coding (RLNC) in theory achieves the max-flow capacity of multicast networks, at the cost of high decoding complexity. To improve the performance-complexity tradeoff, we consider the design of sparse network codes. A…

Information Theory · Computer Science 2016-04-20 Ye Li , Wai-Yip Chan , Steven D. Blostein

Satellites receiving Automatic Identification System (AIS) packets in dense areas are particularly prone to AIS channel overload due to the extensive number of vessels. Thus a failure of detection might be caused by the collisions among AIS…

Information Theory · Computer Science 2025-03-04 Linda Kanaan , Karine Amis , Frédéric Guilloud , Rémi Chauvat

Due to their capacity-achieving property, polar codes have become one of the most attractive channel codes. To date, the successive cancellation list (SCL) decoding algorithm is the primary approach that can guarantee outstanding…

Information Theory · Computer Science 2016-11-18 Bo Yuan , Keshab K. Parhi

We extend earlier work on the design of convolutional code-specific CRC codes to $Q$-ary alphabets, with an eye toward $Q$-ary orthogonal signaling. Starting with distance-spectrum optimal, zero-terminated, $Q$-ary convolutional codes, we…

Information Theory · Computer Science 2022-10-04 Jacob King , William Ryan , Richard D. Wesel

Spatially coupled, parallel concatenated codes (SC-PCCs) have been shown to approach channel capacity when decoded using optimal iterative methods. However, under complexity constraints such decoding strategies can result in unacceptable…

Information Theory · Computer Science 2021-09-07 Andrew D. Cummins , David G. M. Mitchell , Daniel J. Costello,

We propose a simple yet effective model for Single Image Super-Resolution (SISR), by combining the merits of Residual Learning and Convolutional Sparse Coding (RL-CSC). Our model is inspired by the Learned Iterative Shrinkage-Threshold…

Computer Vision and Pattern Recognition · Computer Science 2019-01-01 Menglei Zhang , Zhou Liu , Lei Yu

Recently, the sparse vector code (SVC) is emerging as a promising solution for short-packet transmission in massive machine type communication (mMTC) as well as ultra-reliable and low-latency communication (URLLC). In the SVC process, the…

Information Theory · Computer Science 2022-09-02 Linjie Yang , Pingzhi Fan
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