EXIT Chart Analysis of Nonbinary Protograph LDPC Codes for Partial Response Channels

Phakphisut, Watid; Supnithi, Pornchai; Puttarak, Nattakan

doi:10.1109/tmag.2014.2321021

Cited by 11 publications

(5 citation statements)

References 10 publications

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“…In this section, we try to design protograph code which is suitable for the improved M -ary DSCK system. Specific protograph codes can be carefully designed for the specific communication system to further boost the system performance [30]. Besides, P-EXIT algorithm is also a powerful tool to search the ideal codeword without complex simulations.…”

Section: Proposed Protograph Code For Improved M-ary Dcsk Systemmentioning

confidence: 99%

Design of an Improved M-Ary DCSK-Aided Protograph-Coded Communication System

Dai

2023

IEEE Access

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Differential chaos shift keying (DCSK) is a promising communication technique in the Internet of Things (IoT) scenario. Among various DCSK schemes, M -ary DCSK schemes suit LDPC code especially well dispense with the channel state information in demodulator. However, traditional M -ary DCSK decoder does not make full use of the information of the repeated chaotic signals. To solve this problem, we propose an improved decoder design using a novel initial chaotic signal estimation (ICSE) algorithm. The information of each repeated chaotic signal is utilized to estimate the original chaotic signal, hence provide the accurate loglikelihood ratio (LLR) and improve the error performance. To further boost the system performance, A novel protograph code is proposed using protograph extrinsic information transfer (P-EXIT) algorithm. Both analytical and simulated results show that both the improved decoder design and the proposed protograph code are competitive. The M -ary protograph-coded DCSK system using our improved decoder with ICSE algorithm is a promising solution for low-power and low-complexity devices.INDEX TERMS M -ary DCSK system, protograph LDPC codes, improved protograph decoder, chaotic signal estimation.

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Section: Proposed Protograph Code For Improved M-ary Dcsk Systemmentioning

confidence: 99%

Design of an Improved M-Ary DCSK-Aided Protograph-Coded Communication System

Dai

2023

IEEE Access

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“…Proof of Lemma 3 Proof: In Case 1.1, the number of instances is the number of ways to choose 2 overlaps out of t {i1,i2} overlaps (the pattern has two c 1 − c 2 overlaps), which is given by (6). In Case 1.2, the number of instances is the number of ways to choose 1 overlap out of t {i1,i2} and 1 overlap out of t {i1+(r−e)γ,i2+(r−e)γ} , which is given by (7).…”

Section: Appendix a Proofs Of Pattern Pmentioning

confidence: 99%

“…Moreover, F k≥2 P1,1 is the sum of function B P1 in (7), with r = 1 and e = k, over all possible values of {i 1 , i 2 }. Here, {i 1 , i 2 } can take any distinct two values in the range from the start of R k to the end of R 1 , i.e., from (k − 1)γ to (m + 1)γ − 1 (see also Fig.…”

Section: B Proof Of Theoremmentioning

confidence: 99%

A Channel-Aware Combinatorial Approach to Design High Performance Spatially-Coupled Codes

Hareedy

Dolecek

2020

IEEE Trans. Inform. Theory

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Because of their capacity-approaching performance and their complexity/latency advantages, spatially-coupled (SC) codes are among the most attractive error-correcting codes for use in modern dense data storage systems. SC codes are constructed by partitioning an underlying block code and coupling the partitioned components. Here, we focus on circulant-based SC codes. Recently, the optimal overlap (OO), circulant power optimizer (CPO) approach was introduced to construct high performance SC codes for additive white Gaussian noise (AWGN) and Flash channels. The OO stage operates on the protograph of the SC code to derive the optimal partitioning that minimizes the number of graphical objects that undermine the performance of SC codes under iterative decoding. Then, the CPO optimizes the circulant powers to further reduce this number. Since the nature of detrimental objects in the graph of a code critically depends on the characteristics of the channel of interest, extending the OO-CPO approach to construct SC codes for channels with intrinsic memory is not a straightforward task. In this paper, we tackle one relevant extension; we construct high performance SC codes for practical 1-D magnetic recording channels, i.e., partial-response (PR) channels. Via combinatorial techniques, we carefully build and solve the optimization problem of the OO partitioning, focusing on the objects of interest in the case of PR channels. Then, we customize the CPO to further reduce the number of these objects in the graph of the code. SC codes designed using the proposed OO-CPO approach for PR channels outperform prior state-of-the-art SC codes by up to around 3 orders of magnitude in frame error rate (FER) and 1.1 dB in signal-to-noise ratio (SNR). More intriguingly, our SC codes outperform structured block codes of the same length and rate by up to around 1.8 orders of magnitude in FER and 0.4 dB in SNR. The performance advantage of SC codes designed using the devised OO-CPO approach over block codes of the same parameters is not only pronounced in the error floor region, but also in the waterfall region. I. INTRODUCTIONAs other data storage systems, magnetic recording (MR) systems operate at very low frame error rate (FER) levels [2]-[5]. Consequently, to ensure high error correction capability in such systems, binary [3], [4], [6] and non-binary (NB) [5], [7]-[10]graph-based codes are used. Under iterative decoding, the objects that dominate the error floor region of low-density paritycheck (LDPC) codes simulated in partial-response (PR) and additive white Gaussian noise (AWGN) systems are different in their combinatorial nature because of the detector-decoder looping and the intrinsic memory in PR systems [5]. In particular, the authors in [5] introduced balanced absorbing sets (BASs) to characterize the detrimental objects in the case of PR (1-D MR) channels. Moreover, the weight consistency matrix (WCM) framework was introduced to systematically remove any type of absorbing sets (ASs) from the graph of an NB-LDPC code [11], [12...

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“…Based on the PEXIT algorithm and AWD, many contributions related to the design and analysis of protograph codes as well as their variants have been achieved for a variety of channel conditions [59]- [62], [66]- [80], [83], [88], [94]- [116]. Furthermore, the applications of protograph codes to other areas beyond channel coding, such as JSCC and JCPNC, have been extensively investigated [117]- [123].…”

Section: E Historical Development Of Protograph Codesmentioning

confidence: 99%

“…, 11) have been produced for PR channels based on the proposed rate-9/10 protograph code in the same paper. Inspired by the above-mentioned publications, non-binary protograph codes have already been investigated over PR channels in [116], where the infinite-length EXIT algorithm has also been extended to the non-binary domain in order to measure the convergence performance (i.e., decoding threshold) of non-binary protograph codes. Nonetheless, the authors in [116] have restricted their attention to the analysis aspect and have not provided any design results.…”

Section: Design Of Protograph Codes In Pr Channelsmentioning

confidence: 99%

A Survey on Protograph LDPC Codes and Their Applications

Fang

Guan

et al. 2015

IEEE Commun. Surv. Tutorials

149

112

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Low-density parity-check (LDPC) codes have attracted much attention in the past two decades since they can asymptotically approach the Shannon capacity in a variety of data transmission and storage scenarios. As a type of promising structured LDPC codes, the protograph LDPC codes not only inherit the advantage of conventional LDPC codes, i.e., excellent error performance, but also possess simple representations to realize fast encoding and efficient decoding. This paper provides a comprehensive survey on the state-of-the-art in protograph LDPC code design and analysis for different channel conditions, including the additive white Gaussian noise (AWGN) channels, fading channels, partial response (PR) channels, and Poisson pulse-position modulation (PPM) channels. Moreover, the applications of protograph LDPC codes to joint sourceand-channel coding (JSCC) and joint channel-and-physical-layernetwork coding (JCPNC) are reviewed and studied. In particular, we focus our attention on the encoding design and assume the decoder is implemented by the belief propagation (BP) algorithm. Hopefully, this survey may facilitate the research in this area.

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EXIT Chart Analysis of Nonbinary Protograph LDPC Codes for Partial Response Channels

Cited by 11 publications

References 10 publications

Design of an Improved M-Ary DCSK-Aided Protograph-Coded Communication System

Design of an Improved M-Ary DCSK-Aided Protograph-Coded Communication System

A Channel-Aware Combinatorial Approach to Design High Performance Spatially-Coupled Codes

A Survey on Protograph LDPC Codes and Their Applications

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