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

Hailes, Peter; Xu, Lei; Maunder, Robert G.; Al-Hashimi, Bashir M.; Hanzo, Lajos

doi:10.1109/tcsii.2018.2807362

Cited by 11 publications

(5 citation statements)

References 15 publications

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“…The proposed FC requires M number of LDPC decoders and hence our future work will consider hardware efficient implementation of this. Among the state-of-the-art techniques for channel coding, LDPC decoding is widely considered to be the most hardware-efficient [40], [41]. In the proposed WSN scheme, all sensors transmit messages comprising the same number T of bits, which presents an opportunity for parallel LDPC decoding to be used.…”

Section: Discussionmentioning

confidence: 99%

Tree-Search Techniques for Joint Iterative Compressive Sensing and LDPC Decoding in Wireless Sensor Networks

Chen

Wang

et al. 2023

IEEE Sensors J.

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Novel techniques are conceived for joint Compressive Sensing (CS) and Low-Density Parity Check (LDPC) coding in Wireless Sensor Networks (WSNs), namely a Soft-Input Soft-Output (SISO) tree search Sphere Decoding (SD) technique, and a SISO Hamming Distance (HD) based solution. Factor graphs are utilized to describe the connectivity between the signals and sensors, as well as with the LDPC codes. In the Fusion Center (FC), the factor graphs may be used for iterative joint LDPC-CS decoding, in order to recover the signals observed. However, the CS decoder of the FC suffers from high complexity, if the exhaustive Maximum A posteriori (e-MAP) technique is employed, which considers all possible combinations of source signals detected by each of the associated sensors. Hence, in the proposed SD and HD schemes only the more likely combinations of source signals are tested for reducing the CS decoding complexity. More specifically, a tree search technique is used in the first step to find the most likely combination of source signal values.Then, in the second step, the proposed SD continues the tree search to find a set of alternative hypotheses. This facilitates the generation of high quality extrinsic information, which may be iteratively exchanged with the LDPC decoder. By contrast, in the HD approach, the second step obtains the alternative hypotheses within a certain HD of the most likely source signal combination. Both our BLock Error Rate (BLER) results and Extrinsic Information Transfer (EXIT) charts show that the proposed SD and HD techniques approach the performance of the full-search e-MAP approach at a significantly reduced complexity. In particular, we show the e-MAP solution is about 56 times more complex than the SD approach and around 210 times more complex than the HD approach. Compared to a Separate Source-Channel Coding (SSCC) hard information benchmarker, the proposed SISO schemes improve the decoding performance by about 1.7 dB. Furthermore, the SISO schemes allow the iterations inside the CS decoding to eliminate the error floors and obtain a further 2.45 dB gain.

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Section: Discussionmentioning

confidence: 99%

Tree-Search Techniques for Joint Iterative Compressive Sensing and LDPC Decoding in Wireless Sensor Networks

Chen

Wang

et al. 2023

IEEE Sensors J.

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“…The research on JSCC systems has become more popular [49]- [54], but the feasibility of implementing a JSCC system at the circuit level is rarely mentioned. As a sub-class of LDPC codes [44], [55]- [58], QC-LDPC, where the parity check matrix is composed of permutation matrices (CPMs), can contribute to effective partial-parallel processing, due to the regularity of their parity check matrices H H H. For telecommunication, there have been comprehensive studies [59]- [61] on improving the complexity and accuracy of the LDPC decoders. They applied appropriate calculations [62]- [64] and various structures of LDPC codes [65]- [68].…”

Section: Joint Source Channel Coding and Its Prototypementioning

confidence: 99%

Joint Source-Channel Coding System for 6G Communication: Design, Prototype and Future Directions

Zhong,

Sham,

et al. 2024

IEEE Access

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The emergence of the AI era signifies a shift in the future landscape of global communication networks, wherein robots are expected to play a more prominent role compared to humans. The establishment of a novel paradigm for the development of next-generation 6G communication is of utmost importance for semantics task-oriented empowered communications. The goal of semantic communication lies in the integration of collaborative efforts between the intelligence of the transmission source and the joint design of source coding and channel coding. This characteristic represents a significant benefit of joint source-channel coding (JSCC), as it enables the generation of source alphabets with diverse lengths and achieves a code rate of unity. Therefore, we leverage not only quasi-cyclic (QC) characteristics to facilitate the utilization of flexible structural hardware design but also Unequal Error Protection (UEP) to ensure the recovery of semantic importance. In this study, the feasibility of using a semantic encoder/decoder that is aware of UEP can be explored based on the existing JSCC system. This approach is aimed at protecting the significance of semantic task-oriented information. Additionally, the deployment of a JSCC system can be facilitated by employing QC-Low-Density Parity-Check (LDPC) codes on a reconfigurable device. The QC-LDPC layered decoding technique, which has been specifically optimized for hardware parallelism and tailored for channel decoding applications, can be suitably adapted to accommodate the JSCC system. The performance of the proposed system is evaluated by conducting BER measurements using both floating-point and 6-bit quantization. This is done to assess the extent of performance deterioration in a fair manner. The fixedpoint system is synthesized and subsequently used as a semantic feature transmission and reception system across a noisy channel, with the aim of presenting a prototype for semantic communications. This study concludes with some insights and potential research avenues for the JSCC prototype in the context of future communication.

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“…This method also aids in shortening the time required to evaluate and test the variable node and check node designs. Besides [50], a generalized algorithmic method of constructing node processing units (NPUs) supports flexibility in run-time while keeping small hardware alternative demands and a large operating frequency and support for flexibility in inter or intra-standard LDPC at operating time.…”

Section: Related Workmentioning

confidence: 99%

A Review of Modern and Recent Studies on the Low-Density Parity-Check Technology Approach

2023

IJCCCE

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Data theory coding is an excellent and well-known branch of study that has produced various crucial solutions to the insoluble challenges of safe data transfers. Last improvements in detecting error techniques have resulted in a significant increase in the use of low-density parity-check (LDPC) code to address critical concerns connected to secure data transfer. Until now, decent efforts have been performed on LDPC codes that target low complexity, high performance, and low bit error rate goals. The final aim of this review is to provide a recent literature understanding of modern improvements previously mentioned and in LDPC encoding and decoding (applicative and theoretical) techniques. A comparative scan of many remarkable LDPC decoding algorithms, 5G standard requirements, popular power management methods, and low-energy LDPC design studies is also shown. Lastly, conclusions are presented by outlining key study results, current concerns, and general thoughts on new research directions possibilities. Index Terms— low-density parity-check encoder/decoder (LDPC), error correction codes (ECC), forward error correction codes (FEC), parity check matrix(PCM).

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

Cited by 11 publications

References 15 publications

Tree-Search Techniques for Joint Iterative Compressive Sensing and LDPC Decoding in Wireless Sensor Networks

Tree-Search Techniques for Joint Iterative Compressive Sensing and LDPC Decoding in Wireless Sensor Networks

Joint Source-Channel Coding System for 6G Communication: Design, Prototype and Future Directions

A Review of Modern and Recent Studies on the Low-Density Parity-Check Technology Approach

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