Stochastic Computing Improves the Timing-Error Tolerance and Latency of Turbo Decoders: Design Guidelines and Tradeoffs

Perez-Andrade, Isaac; Zhong, Shida; Maunder, Robert G.; Al-Hashimi, Bashir M.; Hanzo, Lajos

doi:10.1109/access.2016.2523063

Cited by 13 publications

(6 citation statements)

References 56 publications

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“…So, a more general soft SCL decoder is required for concatenated frameworks, for example concatenated coding schemes or joint detection and decoding schemes, invoking iterative decoding. 3) Stochastic Polar Decoders: Stochastic LDPC and turbo decodes are known to provide attractive benefits in terms of fault-tolerance (to timing errors) as well as latency (or equivalently throughout) [183], [184]. However, stochastic polar decoders have not attractive much attention, except for in [185]- [190].…”

Section: Discussionmentioning

confidence: 99%

Polar Codes and Their Quantum-Domain Counterparts

Babar

Egilmez

Xiang

et al. 2020

IEEE Commun. Surv. Tutorials

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Arikan's polar codes are capable of achieving the Shannon's capacity at a low encoding and decoding complexity, while inherently supporting rate adaptation. By virtue of these attractive features, polar codes have provided fierce competition to both the turbo as well as the Low Density Parity Check (LDPC) codes, making its way into the 5G New Radio (NR). Realizing the significance of polar codes, in this paper we provide a comprehensive survey of polar codes, highlighting the major milestones achieved in the last decade. Furthermore, we also provide tutorial insights into the polar encoder, decoders as well as the code construction methods. We also extend our discussions to quantum polar codes with an emphasis on the underlying quantum-to-classical isomorphism and the syndromebased quantum polar codes.

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Section: Discussionmentioning

confidence: 99%

Polar Codes and Their Quantum-Domain Counterparts

Babar

Egilmez

Xiang

et al. 2020

IEEE Commun. Surv. Tutorials

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“…Stochastic LDPC and turbo decoder implementations have a rich literature owing to their numerous benefits, primarily owing to their fault-tolerance [83,84]. Surprisingly, their stochastic polar decoder counterparts have hitherto not attracted much attention apart from [85][86][87][88][89][90].…”

Section: Channel Codingmentioning

confidence: 99%

“…Since the discovery of Turbo code, a large variety of concatenated coding schemes have been conceived, e.g., several potent concatenated schemes, namely parallel concatenated code (PCC) [92] and serially concatenated code (SCC) [95]. Indeed, there are also powerful hybrid concatenated codes (HCCs) [83,84,96] that rely on diverse constituent codes and worth exploring in the future. The above-mentioned turbo principle relying on iterative soft information exchange may be employed for detecting any of the above schemes.…”

Section: Channel Codingmentioning

confidence: 99%

Towards 6G wireless communication networks: vision, enabling technologies, and new paradigm shifts

You

Wang

Huang

et al. 2020

Sci. China Inf. Sci.

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The fifth generation (5G) wireless communication networks are being deployed worldwide from 2020 and more capabilities are in the process of being standardized, such as mass connectivity, ultra-reliability, and guaranteed low latency. However, 5G will not meet all requirements of the future in 2030 and beyond, and sixth generation (6G) wireless communication networks are expected to provide global coverage, enhanced spectral/energy/cost efficiency, better intelligence level and security, etc. To meet these requirements, 6G networks will rely on new enabling technologies, i.e., air interface and transmission technologies and novel network architecture, such as waveform design, multiple access, channel coding schemes, multi-antenna technologies, network slicing, cell-free architecture, and cloud/fog/edge computing. Our vision on 6G is that it will have four new paradigm shifts. First, to satisfy the requirement of global coverage, 6G will not be limited to terrestrial communication networks, which will need to be complemented with non-terrestrial networks such as satellite and unmanned aerial vehicle (UAV) communication networks, thus achieving a space-air-ground-sea integrated communication network. Second, all spectra will be fully explored to further increase data rates and connection density, including the sub-6 GHz, millimeter wave (mmWave), terahertz (THz), and optical frequency bands. Third, facing the big datasets generated by the use of extremely heterogeneous networks, diverse communication scenarios, large numbers of antennas, wide bandwidths, and new service requirements, 6G networks will enable a new range of smart applications with the aid of artificial intelligence (AI) and big data technologies. Fourth, network security will have to be strengthened when developing 6G networks. This article provides a comprehensive survey of recent advances and future trends in these four aspects. Clearly, 6G with additional technical requirements beyond those of 5G will enable faster and further communications to the extent that the boundary between physical and cyber worlds disappears.

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“…Here, providing any input with a 0-valued LLR will nullify any effect it may have on the proceeding calculations. However, a null value does not always exist, as is the case for the NPUs of stochastic LDPC decoders [6], [15], in which the messages exchanged between nodes are represented by bit-serial Bernoulli sequences [6]. Furthermore, the use of null values results in inefficient energy usage, since this implies that every subnode is activated during every NPU activation, regardless of whether it makes any contribution towards the decoding process.…”

Section: Flexible Npu Architecturesmentioning

confidence: 99%

Hardware-Efficient Node Processing Unit Architectures for Flexible LDPC Decoder Implementations

Hailes

Maunder

et al. 2018

IEEE Trans. Circuits Syst. II

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In LDPC decoder implementations, the architecture of the Node Processing Units (NPUs) has a significant impact both on the hardware resource requirements and on the processing throughput. Additionally, some NPU architectures impose limitations on the decoder's support for intra-or inter-standard LDPC code flexibility at run-time. In this paper, we present a generalised algorithmic method of constructing NPUs that support run-time flexibility whilst maintaining a low hardware resource requirement and high maximum operating frequency. FPGA-based synthesis results demonstrate that the proposed architecture offers a significantly improved hardware efficiency, when compared to two commonly-employed alternatives.

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Stochastic Computing Improves the Timing-Error Tolerance and Latency of Turbo Decoders: Design Guidelines and Tradeoffs

Cited by 13 publications

References 56 publications

Polar Codes and Their Quantum-Domain Counterparts

Polar Codes and Their Quantum-Domain Counterparts

Towards 6G wireless communication networks: vision, enabling technologies, and new paradigm shifts

Hardware-Efficient Node Processing Unit Architectures for Flexible LDPC Decoder Implementations

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