Generalized Spatially Coupled Parallel Concatenated Convolutional Codes With Partial Repetition

Qiu, Min; Wu, Xiaowei; Yuan, Jinhong; Amat, Alexandre Graell i

doi:10.1109/isit45174.2021.9517979

Cited by 7 publications

(4 citation statements)

References 22 publications

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“…Unlike the aforementioned works that applied adapted scaling factor for BCH codes, our study applies this adapted parameter to decode GPCB-RS codes. We can compare our work with several recent works using turbo decoding for convolutional codes or block codes using experimental weighting parameters namely [11][12] [13] and [14], our result gave good performance at the level of the gold decoding gain close to the Shannon limits [15]. The remainder of this paper is structured as follows : Section II presents the encoder structure of the generalized parallel concatenated block codes.…”

Section: Introductionmentioning

confidence: 69%

Turbo decoding of concatenated codes based on RS codes using adapted scaling factors

Azougaghe¹,

Farchane²,

Safi³

et al. 2022

Infocommunications journal

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Iteratively decoded block turbo codes are product codes that exhibit excellent performance with reasonable complexity. In this paper, a generalization of parallel concatenated block codes (GPCBs) based on RS codes is presented. We propose an efficient decoding algorithm with modifications of the Chase-Pyndiah algorithm is written by using Weighting factor α and Reliability factor β. In this work, we studied the effect of diverse parametres such as the effect of various component codes, interleaver size (number of sub-blocks) and number of iterations. The simulation results shows the relevance of the adapted parameters to decode generalized parallel concatenated block codes based on RS codes. The proposed algorithm (MCP) using the adapted parameters performs better than the one using with empirical parameters (CP).

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Section: Introductionmentioning

confidence: 69%

Turbo decoding of concatenated codes based on RS codes using adapted scaling factors

Azougaghe¹,

Farchane²,

Safi³

et al. 2022

Infocommunications journal

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show abstract

“…To improve the decoding threshold, [152], [170] generalized SC-PCCCs by allowing a fraction of information bits to be repeated q times before performing coupling and component code encoding. The resultant codes are called generalized SC-PCCCs (GSC-PCCCs).…”

Section: ) Generalized Sc-pcccs (Gsc-pcccs) and Capacity-achievingmentioning

confidence: 99%

Channel Coding Toward 6G: Technical Overview and Outlook

Rowshan,

Qiu,

Xie

et al. 2024

IEEE Open J. Commun. Soc.

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Channel coding plays a pivotal role in ensuring reliable communication over wireless channels. With the growing need for ultra-reliable communication in emerging wireless use cases, the significance of channel coding has amplified. Furthermore, minimizing decoding latency is crucial for critical-mission applications, while optimizing energy efficiency is paramount for mobile and the Internet of Things (IoT) communications. As the fifth generation (5G) of mobile communications is currently in operation and 5G-advanced is on the horizon, the objective of this paper is to assess prominent channel coding schemes in the context of recent advancements and the anticipated requirements for the sixth generation (6G). In this paper, after considering the potential impact of channel coding on key performance indicators (KPIs) of wireless networks, we review the evolution of mobile communication standards and the organizations involved in the standardization, from the first generation (1G) to the current 5G, highlighting the technologies integral to achieving targeted KPIs such as reliability, data rate, latency, energy efficiency, spectral efficiency, connection density, and traffic capacity. Following this, we delve into the anticipated requirements for potential use cases in 6G. The subsequent sections of the paper focus on a comprehensive review of three primary coding schemes utilized in past generations and their recent advancements: lowdensity parity-check (LDPC) codes, turbo codes (including convolutional codes), and polar codes (alongside Reed-Muller codes). Additionally, we examine alternative coding schemes like Fountain codes (also known as rate-less codes), sparse regression codes, among others. Our evaluation includes a comparative analysis of error correction performance and the performance of hardware implementation for these coding schemes, providing insights into their potential and suitability for the upcoming 6G era. Lastly, we will briefly explore considerations such as higher-order modulations and waveform design, examining their contributions to enhancing key performance indicators in conjunction with channel coding schemes.

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“…where R 0 = K ′ N ′ is the code rate of the mother PCC. When L → ∞, the code rate of the GSC-PCC approaches R uc in (1).…”

Section: B Encodingmentioning

confidence: 99%

“…4a]), the difference is that in our case the information node u is represented by two nodes, u r and u o . 1 Since the information sequence u r is repeated q times before being encoded by the PCC encoder, node u r connects the upper and lower factor nodes f U and f L via q edges, respectively.…”

Section: A Graph Representationmentioning

confidence: 99%

Generalized Spatially-Coupled Parallel Concatenated Codes With Partial Repetition

Qiu

Yuan

et al. 2022

IEEE Trans. Commun.

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A new class of spatially-coupled turbo-like codes (SC-TCs), dubbed generalized spatially coupled parallel concatenated codes (GSC-PCCs), is introduced. These codes are constructed by applying spatial coupling on parallel concatenated codes (PCCs) with a fraction of information bits repeated q times. GSC-PCCs can be seen as a generalization of the original spatially-coupled parallel concatenated codes proposed by Moloudi et al. [2]. To characterize the asymptotic performance of GSC-PCCs, we derive the corresponding density evolution equations and compute their decoding thresholds. The threshold saturation effect is observed and proven. Most importantly, we rigorously prove that the rate-R GSC-PCC ensemble with 2state convolutional component codes achieves at least a fraction 1 − R R+q of the capacity of the binary erasure channel (BEC) for repetition factor q ≥ 2 and this multiplicative gap vanishes as q tends to infinity. To the best of our knowledge, this is the first class of SC-TCs that are proven to be capacity-achieving. Further, the connection between the strength of the component codes, the decoding thresholds of GSC-PCCs, and the repetition factor is established. The superiority of the proposed codes with finite blocklength is exemplified by comparing their error performance with that of existing SC-TCs via computer simulations.

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Generalized Spatially Coupled Parallel Concatenated Convolutional Codes With Partial Repetition

Cited by 7 publications

References 22 publications

Turbo decoding of concatenated codes based on RS codes using adapted scaling factors

Turbo decoding of concatenated codes based on RS codes using adapted scaling factors

Channel Coding Toward 6G: Technical Overview and Outlook

Generalized Spatially-Coupled Parallel Concatenated Codes With Partial Repetition

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