Polar Code decoder exploration framework

Kestel, Claus; Weithoffer, Stefan; Wehn, Norbert

doi:10.5194/ars-16-43-2018

Cited by 8 publications

(5 citation statements)

References 16 publications

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“…A modular framework for generating and evaluating highthroughput Polar code decoders is presented in [243], where soft cancellation algorithms are explored. Achieving a Tbpsthroughput with Polar codes is also addressed in [244], where low-latency majority logic and low-complexity successive cancellation are combined for decoding, alongside an adaptive quantization scheme for log-likelihood-ratios (LLRs).…”

Section: B Channel Codingmentioning

confidence: 99%

An Overview of Signal Processing Techniques for Terahertz Communications

2021

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Terahertz (THz)-band communications are a key enabler for future-generation wireless communication systems that promise to integrate a wide range of data-demanding applications. Recent advancements in photonic, electronic, and plasmonic technologies are closing the gap in THz transceiver design. Consequently, prospect THz signal generation, modulation, and radiation methods are converging, and the corresponding channel model, noise, and hardware-impairment notions are emerging. Such progress paves the way for well-grounded research into THz-specific signal processing techniques for wireless communications. This tutorial overviews these techniques with an emphasis on ultra-massive multiple-input multiple-output (UM-MIMO) systems and reconfigurable intelligent surfaces, which are vital to overcoming the distance problem at very high frequencies. We focus on the classical problems of waveform design and modulation, beamforming and precoding, index modulation, channel estimation, channel coding, and data detection. We also motivate signal processing techniques for THz sensing and localization.

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Section: B Channel Codingmentioning

confidence: 99%

An Overview of Signal Processing Techniques for Terahertz Communications

2021

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“…This scheme involves transforming a set of independent and identically distributed (iid) bit channels into channels with varying error rates, leveraging their polarizing properties. Due to their highperformance capabilities, these codes are increasingly recognized as promising candidates for data transmission in emerging 6G networks [24], [25].…”

Section: Polar Codesmentioning

confidence: 99%

Advanced hybrid algorithms for precise multipath channel estimation in next-generation wireless networks

Rekkal,

Bassou

2024

IJECE

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Multipath channels continue to present challenges in wireless communication for both 5G and 6G networks. A multipath channel is a phenomenon in wireless communications where signals traverse from the sender to the receiver along various paths. This end occurs due to the reflection, diffraction, and refraction of signals of various objects and structures in the environment. Such pathways can cause symbol interference in the transmitted signal, leading to communication issues. To this end, our paper proposes the integration of three algorithms: teaching-learning-based optimization (TLBO), particle swarm optimization (PSO), and artificial neural networks (ANN). This combination effectively analyzes and stabilizes the transmission channel, minimizing symbol interference. We have developed, simulated, and evaluated this hybrid approach for multipath fading channels. We apply it to various coding schemes, including tail-biting convolutional code, turbo codes, low-density parity-check, and polar code. Additionally, we have explored various decoding methods such as Viterbi, maximum logarithmic maximum a posteriori, minimum sum, and cyclic redundancy check soft cancellation list. Our study encompasses new channel equalization schemes and coding gains derived from simulations and mathematical analysis. Our proposed method significantly enhances channel equalization, reducing interference and improving error correction in wireless communication systems.

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“…However, the modified-SCAN decoder can process the SCL decoder's output, which allows them to work together to deliver the best of both worlds, as mentioned in Section I. Similar to other polar decoders [23], the proposed G-SCAN polar decoder core can be operated on the basis of the same factor graph that is used in the polar encoder core, which is exemplified in Figure 3a for the case of N = 8. In general, a factor graph comprises N n 2 unit factor graphs and N n nodes where N = 2 n , with each unit factor graph being connected to four nodes.…”

Section: A Proposed G-scan Polar Decoder Algorithmmentioning

confidence: 99%

“…Similarly, the modified-SCAN decoder used in the second step of the G-SCAN algorithm adopts the same schedule as the conventional SCAN algorithm, which is also based on the SC algorithm. More specifically, the SC algorithm can be represented as detailed in [23], where a binary tree having n layers and N = 2 n leaf nodes, there are 2(2N − 2) node-visits. This schedule of visiting the nodes is exemplified on a factor graph in Figure 3b, where the steps of the modified-SCAN algorithm are indicated by the step indices in brackets for the case of N = 8.…”

Section: A Proposed G-scan Polar Decoder Algorithmmentioning

confidence: 99%

A Soft-Input Soft-Output Polar Decoding Algorithm for Turbo-Detection in MIMO-Aided 5G New Radio

Kaykac

Xiang

Maunder

et al. 2022

IEEE Trans. Veh. Technol.

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Soft-Input Soft-Output (SISO) polar decoding algorithms, such as Belief Propagation (BP) and Soft Cancellation (SCAN) polar decoding, offer iteration capability for facilitating turbo-style detection. However, at lower Signal-to-Noise Ratios (SNRs), the performance of the BP and SCAN decoders is about 1.5 dB and 0.5 dB worse than that of the state-of-the-art harddecision Successive Cancellation List (SCL) decoding algorithm, respectively, despite iteratively exchanging information with a Multiple Input Multiple Output (MIMO) detector. Motivated by this gap, we conceive a novel G-SCAN polar decoder, which generates both soft-decision and hard-decision outputs. This is achieved by intrinsically amalgamating a list decoder with a novel SISO decoder. These soft-decision outputs may be used for turbo-detection, but they also support the hard-decision outputs of the SCL algorithm for achieving superior block error rate (BLER) performance. As a result of these benefits, the proposed G-SCAN algorithm using a list size of L = 2 offers around 1dB BLER gain compared to the conventional hard-decision SCL decoder relying on L = 32. Furthermore, we have carried out its Extrinsic Information Transfer (EXIT) chart analysis, and characterized the performance vs. the complexity of the proposed G-SCAN algorithm, and compared it to various softand hard-decision output benchmarks for a wide variety of different rate-matching modes and block lengths. Furthermore, in order to reduce the complexity of the proposed algorithm, a novel Cyclic Redundancy Check (CRC)-aided G-SCAN algorithm is also proposed, which facilitates early termination and improves the BLER performance.

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Polar Code decoder exploration framework

Cited by 8 publications

References 16 publications

An Overview of Signal Processing Techniques for Terahertz Communications

An Overview of Signal Processing Techniques for Terahertz Communications

Advanced hybrid algorithms for precise multipath channel estimation in next-generation wireless networks

A Soft-Input Soft-Output Polar Decoding Algorithm for Turbo-Detection in MIMO-Aided 5G New Radio

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