A survey of FPGA-based LDPC decoders

Low-Density Parity Check (LDPC) error correction decoders have become popular in communications systems, as a benefit of their strong error correction performance and their suitability to parallel hardware implementation. A great deal of research effort has been invested into LDPC decoder designs that exploit the flexibility, the high processing speed and the parallelism of Field-Programmable Gate Array (FPGA) devices. FPGAs are ideal for design prototyping and for the manufacturing of small-production-run devices, where their in-system programmability makes them far more cost-effective than Application-Specific Integrated Circuits (ASICs). However, the FPGA-based LDPC decoder designs published in the open literature vary greatly in terms of design choices and performance criteria, making them a challenge to compare. This paper explores the key factors involved in FPGA-based LDPC decoder design and presents an extensive review of the current literature. In-depth comparisons are drawn amongst 140 published designs (both academic and industrial) and the associated performance trade-offs are characterised, discussed and illustrated. Seven key performance characteristics are described, namely their processing throughput, latency, hardware resource requirements, error correction capability, processing energy efficiency, bandwidth efficiency and flexibility. We offer recommendations that will facilitate fairer comparisons of future designs, as well as opportunities for improving the design of FPGA-based LDPC decoder

Doing and evaluating community research - A process and outcomes approach for communities and researchers

First paragraph: This guide aims to help community partners and academics maximise the benefits of research that is coproduced between communities and academic researchers based in a university. It is divided into three parts: - Learning points - The research story - themes and lessons - How to evaluate The text is hyperlinked for easy access for those who are reading the electronic version. The page numbers in the learning points above take you to the relevant text, as does the underlined text in this section

1.5 Gbit/s FPGA implementation of a fully-parallel turbo decoder designed for mission-critical machine-type communication applications

In wireless communication schemes, turbo codes facilitate near-capacity transmission throughputs by achieving reliable forward error correction. However, owing to the serial data dependencies imposed by the underlying Logarithmic Bahl-Cocke-Jelinek-Raviv (Log- BCJR) algorithm, the limited processing throughputs of conventional turbo decoder implementations impose a severe bottleneck upon the overall throughputs of realtime wireless communication schemes. Motivated by this, we recently proposed a Fully Parallel Turbo Decoder (FPTD) algorithm, which eliminates these serial data dependencies, allowing parallel processing and hence offering a significantly higher processing throughput. In this paper, we propose a novel resource-efficient version of the FPTD algorithm, which reduces its computational resource requirement by 50%, which enhancing its suitability for Field-Programmable Gate Array (FPGA) implementations. We propose a model FPGA implementation. When using a Stratix IV FPGA, the proposed FPTD FPGA implementation achieves an average throughput of 1.53 Gbit/s and an average latency of 0.56 s, when decoding frames comprising N=720 bits. These are respectively 13.2 times and 11.1 times superior to those of the state-of-the- art FPGA implementation of the Log-BCJR Long- Term Evolution (LTE) turbo decoder, when decoding frames of the same frame length at the same error correction capability. Furthermore, our proposed FPTD FPGA implementation achieves a normalized resource usage of 0.42 kALUTs Mbit/s , which is 5.2 times superior to that of the benchmarker decoder. Furthermore, when decoding the shortest N=40-bit LTE frames, the proposed FPTD FPGA implementation achieves an average throughput of 442 Mbit/s and an average latency of 0.18 s, which are respectively 21.1 times and 10.6 times superior to those of the benchmarker decoder. In this case, the normalized resource usage of 0.08 kALUTs Mbit/s is 146.4 times superior to that of the benchmarker decoder

Tunable Semiconducting Polymer Nanoparticles with INDT-Based Conjugated Polymers for Photoacoustic Molecular Imaging.

Photoacoustic imaging combines both excellent spatial resolution with high contrast and specificity, without the need for patients to be exposed to ionizing radiation. This makes it ideal for the study of physiological changes occurring during tumorigenesis and cardiovascular disease. In order to fully exploit the potential of this technique, new exogenous contrast agents with strong absorbance in the near-infrared range, good stability and biocompatibility, are required. In this paper, we report the formulation and characterization of a novel series of endogenous contrast agents for photoacoustic imaging in vivo. These contrast agents are based on a recently reported series of indigoid π-conjugated organic semiconductors, coformulated with 1,2-dipalmitoyl-sn-glycero-3-phosphocholine, to give semiconducting polymer nanoparticles of about 150 nm diameter. These nanoparticles exhibited excellent absorption in the near-infrared region, with good photoacoustic signal generation efficiencies, high photostability, and extinction coefficients of up to three times higher than those previously reported. The absorption maximum is conveniently located in the spectral region of low absorption of chromophores within human tissue. Using the most promising semiconducting polymer nanoparticle, we have demonstrated wavelength-dependent differential contrast between vasculature and the nanoparticles, which can be used to unambiguously discriminate the presence of the contrast agent in vivo

Methyltransferases: Functions and Applications

In this review the current state of the art of S-adenosylmethionine (SAM)-dependent methyltransferases and SAM are evaluated. Their structural classification and diversity is introduced and key mechanistic aspects presented which are then detailed further. Then, catalytic SAM as a target for drugs and approaches to utilise SAM as a cofactor in synthesis is introduced with different recycling approaches evaluated. The use of SAM analogues are also described. Finally O-, N-, C- and S-MTs, their synthetic applications and potential for compound diversification is given

An Integrated Biorefinery Concept for Conversion of Sugar Beet Pulp into Value-added Chemicals and Pharmaceutical Intermediates

Over 8 million tonnes of sugar beet are grown annually in the UK. Sugar beet pulp (SBP) is the main by-product of sugar beet processing which is currently dried and sold as a low value animal feed. SBP is a rich source of carbohydrates, mainly in the form of cellulose and pectin, including D-glucose (Glu), L-arabinose (Ara) and D-galacturonic acid (GalAc). This work describes the technical feasibility of an integrated biorefinery concept for fractionation of SBP and conversion of these monosaccharides into value-added products. SBP fractionation is initially carried out by steam explosion under mild conditions to yield soluble pectin and insoluble cellulose fractions. The cellulose is readily hydrolysed by cellulases to release Glu that can then be fermented by a commercial Yeast strain to produce bioethanol with a high yield. The pectin fraction can be either fully hydrolysed, using physico-chemical methods, or selectively hydrolysed, using cloned arabinases and galacturonases, to yield Ara-rich and GalAc-rich streams. These monomers can be separated using either Centrifugal Partition Chromatography (CPC) or ultrafiltration into streams suitable for subsequent enzymatic upgrading. Building on our previous experience with transketolase (TK) and transaminase (TAm) enzymes, the conversion of Ara and GalAc into higher value products was explored. In particular the conversion of Ara into L-gluco-heptulose (GluHep), that has potential therapeutic applications in hypoglycaemia and cancer, using a mutant TK is described. Preliminary studies with TAm also suggest GluHep can be selectively aminated to the corresponding chiral aminopolyol. Current work is addressing upgrading of the remaining SBP monomer, GalAc, and modelling of the biorefinery concept to enable economic and Life Cycle Analysis (LCA)

Detecting intratumoral heterogeneity of EGFR activity by liposome-based in vivo transfection of a fluorescent biosensor

Despite decades of research in the epidermal growth factor receptor (EGFR) signalling field, and many targeted anti-cancer drugs that have been tested clinically, the success rate for these agents in the clinic is low, particularly in terms of the improvement of overall survival. Intratumoral heterogeneity is proposed as a major mechanism underlying treatment failure of these molecule-targeted agents. Here we highlight the application of fluorescence lifetime microscopy (FLIM)-based biosensing to demonstrate intratumoral heterogeneity of EGFR activity. For sensing EGFR activity in cells, we used a genetically encoded CrkII-based biosensor which undergoes conformational changes upon tyrosine-221 phosphorylation by EGFR. We transfected this biosensor into EGFR-positive tumour cells using targeted lipopolyplexes bearing EGFR-binding peptides at their surfaces. In a murine model of basal-like breast cancer, we demonstrated a significant degree of intratumoral heterogeneity in EGFR activity, as well as the pharmacodynamic effect of a radionuclide-labeled EGFR inhibitor in situ. Furthermore, a significant correlation between high EGFR activity in tumour cells and macrophage-tumour cell proximity was found to in part account for the intratumoral heterogeneity in EGFR activity observed. The same effect of macrophage infiltrate on EGFR activation was also seen in a colorectal cancer xenograft. In contrast, a non-small cell lung cancer xenograft expressing a constitutively active EGFR conformational mutant exhibited macrophage proximity-independent EGFR activity. Our study validates the use of this methodology to monitor therapeutic response in terms of EGFR activity. In addition, we found iNOS gene induction in macrophages that are cultured in tumour cell-conditioned media as well as an iNOS activity-dependent increase in EGFR activity in tumour cells. These findings point towards an immune microenvironment-mediated regulation that gives rise to the observed intratumoral heterogeneity of EGFR signalling activity in tumour cells in vivo

Design and implementation of flexible FPGA-based LDPC decoders

Since their rediscovery in the mid-1990s, Low-Density Parity Check (LDPC) error correction decoders have been the focus of a great deal of research within the communications community. They have also become popular channel coding schemes in a plethora of diverse communications standards, as a benefit of their strong error correction performance, low-complexity computations, and their suitability to parallel hardware implementation. Meanwhile, a great deal of research effort has been invested into LDPC decoder designs that exploit the high processing speed and parallelism of Field-Programmable Gate Array (FPGA) devices, which now constitute a cost-effective alternative to Application-Specific Integrated Circuit (ASIC) platforms for LDPC decoder implementations. However, the FPGA-based LDPC decoder designs published in the open literature vary greatly in terms of design choices and performance criteria, making them a challenge to compare and even more challenging to implement.In this thesis, we explore the key factors involved in FPGA-based LDPC decoder design and present an extensive review of the current literature, analysing and characterising the performance tradeoffs demonstrated across over 140 competing designs. From this survey, we conclude that high-performance FPGA-based LDPC decoder designs supporting the ability to dynamically alter their decoding parameters at run-time are under-represented within the state-of-the-art, despite their necessity in order to comply with many modern communications standards.Accordingly, this thesis therefore proposes two parameterised FPGA-based LDPC decoder architectures, which both support run-time flexibility over any arbitrary set of one or more Quasi-Cyclic (QC) LDPC codes. Our first architecture adopts a traditional fixed-point message decoding algorithm, but features a variety of design optimisations which reduce the costs of supporting multiple diverse codes. Implementation results of this decoder indicate that it is capable of achieving throughputs that are higher than previous flexible FPGA-based LDPC decoders, even whilst achieving the desired level of flexibility and satisfactorily high error correction performance

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

Comparison of fixed-point CNPUs constructed using the proposed novel Dual-tree topology vs. three alternatives, for a range of input numbers I, measuring hardware resource requirements and maximum operating frequency. The dataset is associated with the following publication: P. Hailes, L. Xu, R. G. Maunder, B. M. Al-Hashimi, and L. Hanzo, &ldquo;Hardware-Efficient Node Processing Unit Architectures for Flexible LDPC Decoder Implementations,&rdquo; IEEE Trans. Circuits Syst. II Express Briefs, 2018.</span