Soft-Output Successive Cancellation Stack Polar Decoder

Xiang, Luping; Liu, Yusha; Maunder, Robert G.; Hanzo, Lajos

doi:10.1109/tvt.2021.3077757

Cited by 7 publications

(3 citation statements)

References 30 publications

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“…In this case, the eavesdropper is unable to infer the specific polarization pattern and coding structures since the specific detection method is unattainable. Following the increasing detection order, the soft estimate [39] of the t-th data stream is formulated as:…”

Section: Mmse Detection Ordermentioning

confidence: 99%

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Multi-Domain Polarization for Enhancing the Physical Layer Security of MIMO Systems

Xiang,

Zeng,

et al. 2024

IEEE Trans. Commun.

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A novel Physical Layer Security (PLS) framework is conceived for enhancing the security of the wireless communication systems by exploiting multi-domain polarization in Multiple-Input Multiple-Output (MIMO) systems. We design a sophisticated key generation scheme based on multi-domain polarization, and the corresponding receivers. An in-depth analysis of the system's secrecy rate is provided, demonstrating the confidentiality of our approach in the presence of eavesdroppers having strong computational capabilities. More explicitly, our simulation results and theoretical analysis corroborate the advantages of the proposed scheme in terms of its bit error rate (BER), block error rate (BLER), and maximum achievable secrecy rate. Our findings indicate that the innovative PLS framework effectively enhances the security and reliability of wireless communication systems. For instance, in a 4 × 4 MIMO setup, the proposed PLS strategy exhibits an improvement of 2dB compared to conventional MIMO, systems at a BLER of 2 • 10 −5 while the eavesdropper's BLER reaches 1.

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Section: Mmse Detection Ordermentioning

confidence: 99%

“…The LLRs are derived based on equation ( 13) and subsequently they are input into the successive cancellation (SC) based stack polar decoder [39] for making hard decisions, as depicted in Fig 6.…”

Section: A Legitimate Receivermentioning

confidence: 99%

Multi-Domain Polarization for Enhancing the Physical Layer Security of MIMO Systems

Xiang,

Zeng,

et al. 2024

IEEE Trans. Commun.

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“…To address this issue, some studies concentrated on low-latency SC decoding techniques [ 4 , 5 ], which combine the stability of recognition-based techniques with the dynamism of check-based techniques. In addition, some studies have been presented to improve error correction performance [ 6 , 7 , 8 , 9 , 10 , 11 , 12 ]. While all of these are serial techniques, which suffer from random node errors, some parallel decoding techniques, including the BP algorithm [ 13 , 14 ], have been proposed to address this issue.…”

Section: Introductionmentioning

confidence: 99%

DIR-Net: Deep Residual Polar Decoding Network Based on Information Refinement

Song

Feng

Wang

2022

Entropy

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Polar codes are closer to the Shannon limit with lower complexity in coding and decoding. As traditional decoding techniques suffer from high latency and low throughput, with the development of deep learning technology, some deep learning-based decoding methods have been proposed to solve these problems. Usually, the deep neural network is treated as a black box and learns to map the polar codes with noise to the original information code directly. In fact, it is difficult for the network to distinguish between valid and interfering information, which leads to limited BER performance. In this paper, a deep residual network based on information refinement (DIR-NET) is proposed for decoding polar-coded short packets. The proposed method works to fully distinguish the effective and interference information in the codewords, thus obtaining a lower bit error rate. To achieve this goal, we design a two-stage decoding network, including a denoising subnetwork and decoding subnetwork. This structure can further improve the accuracy of the decoding method. Furthermore, we construct the whole network solely on the basis of the attention mechanism. It has a stronger information extraction ability than the traditional neural network structure. Benefiting from cascaded attention modules, information can be filtered and refined step-by-step, thus obtaining a low bit error rate. The simulation results show that DIR-Net outperforms existing decoding methods in terms of BER performance under both AWGN channels and flat fading channels.

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Polar Decoder-Based Full Adders: Implementation and Comparative Analysis Using 180 nm and 90 nm Technologies in Cadence

Vijayalakshmi

Selvakumar

2023

Lecture Notes in Electrical Engineering

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Soft-Output Successive Cancellation Stack Polar Decoder

Cited by 7 publications

References 30 publications

Multi-Domain Polarization for Enhancing the Physical Layer Security of MIMO Systems

Multi-Domain Polarization for Enhancing the Physical Layer Security of MIMO Systems

DIR-Net: Deep Residual Polar Decoding Network Based on Information Refinement

Polar Decoder-Based Full Adders: Implementation and Comparative Analysis Using 180 nm and 90 nm Technologies in Cadence

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