Recent Results on the Implementation of a Burst Error and Burst Erasure Channel Emulator Using an FPGA Architecture

The behaviour of a transmission channel may be simulated using the performance abilities of current generation multiprocessing hardware, namely, a multicore Central Processing Unit (CPU), a general purpose Graphics Processing Unit (GPU), or a Field Programmable Gate Array (FPGA). These were investigated by Cullinan et al. in a recent paper (published in 2012) where these three devices capabilities were compared to determine which device would be best suited towards which specific task. In particular, it was shown that, for the application which is objective of our work (i.e., for a transmission channel simulation), the FPGA is 26.67 times faster than the GPU and 10.76 times faster than the CPU. Motivated by these results, in this paper we propose and present a direct hardware emulation. In particular, a Cyclone II FPGA architecture is implemented to simulate a burst error channel behaviour, in which errors are clustered together, and a burst erasure channel behaviour, in which the erasures are clustered together. The results presented in the paper are valid for any FPGA architecture that may be considered for this scope

Improve the Usability of Polar Codes: Code Construction, Performance Enhancement and Configurable Hardware

Error-correcting codes (ECC) have been widely used for forward error correction (FEC) in modern communication systems to dramatically reduce the signal-to-noise ratio (SNR) needed to achieve a given bit error rate (BER). Newly invented polar codes have attracted much interest because of their capacity-achieving potential, efficient encoder and decoder implementation, and flexible architecture design space.This dissertation is aimed at improving the usability of polar codes by providing a practical code design method, new approaches to improve the performance of polar code, and a configurable hardware design that adapts to various specifications. State-of-the-art polar codes are used to achieve extremely low error rates. In this work, high-performance FPGA is used in prototyping polar decoders to catch rare-case errors for error-correcting performance verification and error analysis. To discover the polarization characteristics and error patterns of polar codes, an FPGA emulation platform for belief-propagation (BP) decoding is built by a semi-automated construction flow. The FPGA-based emulation achieves significant speedup in large-scale experiments involving trillions of data frames. The platform is a key enabler of this work. The frozen set selection of polar codes, known as bit selection, is critical to the error-correcting performance of polar codes. A simulation-based in-order bit selection method is developed to evaluate the error rate of each bit using Monte Carlo simulations. The frozen set is selected based on the bit reliability ranking. The resulting code construction exhibits up to 1 dB coding gain with respect to the conventional bit selection. To further improve the coding gain of BP decoder for low-error-rate applications, the decoding error mechanisms are studied and analyzed, and the errors are classified based on their distinct signatures. Error detection is enabled by low-cost CRC concatenation, and post-processing algorithms targeting at each type of the error is designed to mitigate the vast majority of the decoding errors. The post-processor incurs only a small implementation overhead, but it provides more than an order of magnitude improvement of the error-correcting performance. The regularity of the BP decoder structure offers many hardware architecture choices. Silicon area, power consumption, throughput and latency can be traded to reach the optimal design points for practical use cases. A comprehensive design space exploration reveals several practical architectures at different design points. The scalability of each architecture is also evaluated based on the implementation candidates. For dynamic communication channels, such as wireless channels in the upcoming 5G applications, multiple codes of different lengths and code rates are needed to t varying channel conditions. To minimize implementation cost, a universal decoder architecture is proposed to support multiple codes through hardware reuse. A 40nm length- and rate-configurable polar decoder ASIC is demonstrated to fit various communication environments and service requirements.PHDElectrical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/140817/1/shuangsh_1.pd

Low-Density Parity-Check Code Decoder Design and Error Characterization on an FPGA Based Framework

Low-Density Parity-Check (LDPC) codes have gained popularity in communication systems and standards due to their capacity approaching error correction performance. Among all the hard-decision based LDPC decoders, Gallager B (GaB), due to simplicity of its operations, poses as the most hardware friendly algorithm and an attractive solution for meeting the high-throughput demand in communication systems. However, GaB sufferers from poor error correction performance. In this work, we first propose a resource efficient GaB hardware architecture that delivers the best throughput while using fewest Field Programmable Gate Array (FPGA) resources with respect to the state of the art comparable LDPC decoding algorithms. We then introduce a Probabilistic GaB (PGaB) algorithm that disturbs the decisions made during the decoding iterations randomly with a probability value determined based on experimental studies. We achieve up to four orders of magnitude better error correction performance than the GaB with a 3.4% improvement in normalized throughput performance. PGaB requires around 40% less energy than GaB as the probabilistic execution results with reducing the average iteration count by up to 62% compared to the GaB. We also show that our PGaB consistently results with an improvement in maximum operational clock rate compared to the state of the art implementations. In this dissertation, we also present a high throughput FPGA based framework to accelerate error characterization of the LDPC codes. Our flexible framework allows the end user adjust the simulation parameters and rapidly study various LDPC codes and decoders. We first show that the connection intensive bipartite graph based LDPC decoder hardware architecture creates routing stress for longer codewords that are utilized in today's communications systems and standards. We address this problem by partitioning each processing element (PE) in the bipartite graph in such a way that the inputs of a PE are evenly distributed over its partitions. This allows depopulating the Loo Up Table (LUT) resources utilized for the decoder architecture by spreading the logic across the FPGA. We show that even though LUT usage increases, critical path delay reduces with the depopulation. More importantly, with the depopulation technique an unroutable design becomes routable, which allows longer codewords to be mapped on the FPGA. We then conduct two experiments on error correction performance analysis for the GaB and PGaB algorithms, demonstrate our framework's ability to reach a resolution level that is not attainable with general purpose processor (GPP) based simulations, which reduces the time scale of simulations to 24 hours from an estimated 199 years. We finally conduct the first study on identifying all possible codewords that are not correctable by the GaB for the case where a codeword has four errors. We reduce the time scale of this simulation that requires processing 117 billion codewords to 4 hours and 38 minutes with our framework from an estimated 7800 days on a single GPP

Survey of FPGA applications in the period 2000 – 2015 (Technical Report)

Romoth J, Porrmann M, Rückert U. Survey of FPGA applications in the period 2000 – 2015 (Technical Report).; 2017.Since their introduction, FPGAs can be seen in more and more different fields of applications. The key advantage is the combination of software-like flexibility with the performance otherwise common to hardware. Nevertheless, every application field introduces special requirements to the used computational architecture. This paper provides an overview of the different topics FPGAs have been used for in the last 15 years of research and why they have been chosen over other processing units like e.g. CPUs

Dependable Embedded Systems

This Open Access book introduces readers to many new techniques for enhancing and optimizing reliability in embedded systems, which have emerged particularly within the last five years. This book introduces the most prominent reliability concerns from today’s points of view and roughly recapitulates the progress in the community so far. Unlike other books that focus on a single abstraction level such circuit level or system level alone, the focus of this book is to deal with the different reliability challenges across different levels starting from the physical level all the way to the system level (cross-layer approaches). The book aims at demonstrating how new hardware/software co-design solution can be proposed to ef-fectively mitigate reliability degradation such as transistor aging, processor variation, temperature effects, soft errors, etc. Provides readers with latest insights into novel, cross-layer methods and models with respect to dependability of embedded systems; Describes cross-layer approaches that can leverage reliability through techniques that are pro-actively designed with respect to techniques at other layers; Explains run-time adaptation and concepts/means of self-organization, in order to achieve error resiliency in complex, future many core systems