Design of hardware accelerators for demanding applications.

This paper focuses on mastering the architecture development of hardware accelerators. It presents the results of our analysis of the main issues that have to be addressed when designing accelerators for modern demanding applications, when using as an example the accelerator design for LDPC decoding for the newest demanding communication system standards. Based on the results of our analysis, we formulate the main requirements that have to be satisfied by an adequate accelerator design methodology, and propose a design approach which satisfies these requirements

Energy-efficient design and implementation of turbo codes for wireless sensor network

The objective of this thesis is to apply near Shannon limit Error-Correcting Codes (ECCs), particularly the turbo-like codes, to energy-constrained wireless devices, for the purpose of extending their lifetime. Conventionally, sophisticated ECCs are applied to applications, such as mobile telephone networks or satellite television networks, to facilitate long range and high throughput wireless communication. For low power applications, such as Wireless Sensor Networks (WSNs), these ECCs were considered due to their high decoder complexities. In particular, the energy efficiency of the sensor nodes in WSNs is one of the most important factors in their design. The processing energy consumption required by high complexity ECCs decoders is a significant drawback, which impacts upon the overall energy consumption of the system. However, as Integrated Circuit (IC) processing technology is scaled down, the processing energy consumed by hardware resources reduces exponentially. As a result, near Shannon limit ECCs have recently begun to be considered for use in WSNs to reduce the transmission energy consumption [1,2]. However, to ensure that the transmission energy consumption reduction granted by the employed ECC makes a positive improvement on the overall energy efficiency of the system, the processing energy consumption must still be carefully considered.The main subject of this thesis is to optimise the design of turbo codes at both an algorithmic and a hardware implementation level for WSN scenarios. The communication requirements of the target WSN applications, such as communication distance, channel throughput, network scale, transmission frequency, network topology, etc, are investigated. Those requirements are important factors for designing a channel coding system. Especially when energy resources are limited, the trade-off between the requirements placed on different parameters must be carefully considered, in order to minimise the overall energy consumption. Moreover, based on this investigation, the advantages of employing near Shannon limit ECCs in WSNs are discussed. Low complexity and energy-efficient hardware implementations of the ECC decoders are essential for the target applications

Hardware implementation aspects of polar decoders and ultra high-speed LDPC decoders

The goal of channel coding is to detect and correct errors that appear during the transmission of information. In the past few decades, channel coding has become an integral part of most communications standards as it improves the energy-efficiency of transceivers manyfold while only requiring a modest investment in terms of the required digital signal processing capabilities. The most commonly used channel codes in modern standards are low-density parity-check (LDPC) codes and Turbo codes, which were the first two types of codes to approach the capacity of several channels while still being practically implementable in hardware. The decoding algorithms for LDPC codes, in particular, are highly parallelizable and suitable for high-throughput applications. A new class of channel codes, called polar codes, was introduced recently. Polar codes have an explicit construction and low-complexity encoding and successive cancellation (SC) decoding algorithms. Moreover, polar codes are provably capacity achieving over a wide range of channels, making them very attractive from a theoretical perspective. Unfortunately, polar codes under standard SC decoding cannot compete with the LDPC and Turbo codes that are used in current standards in terms of their error-correcting performance. For this reason, several improved SC-based decoding algorithms have been introduced. The most prominent SC-based decoding algorithm is the successive cancellation list (SCL) decoding algorithm, which is powerful enough to approach the error-correcting performance of LDPC codes. The original SCL decoding algorithm was described in an arithmetic domain that is not well-suited for hardware implementations and is not clear how an efficient SCL decoder architecture can be implemented. To this end, in this thesis, we re-formulate the SCL decoding algorithm in two distinct arithmetic domains, we describe efficient hardware architectures to implement the resulting SCL decoders, and we compare the decoders with existing LDPC and Turbo decoders in terms of their error-correcting performance and their implementation efficiency. Due to the ongoing technology scaling, the feature sizes of integrated circuits keep shrinking at a remarkable pace. As transistors and memory cells keep shrinking, it becomes increasingly difficult and costly (in terms of both area and power) to ensure that the implemented digital circuits always operate correctly. Thus, manufactured digital signal processing circuits, including channel decoder circuits, may not always operate correctly. Instead of discarding these faulty dies or using costly circuit-level fault mitigation mechanisms, an alternative approach is to try to live with certain malfunctions, provided that the algorithm implemented by the circuit is sufficiently fault-tolerant. In this spirit, in this thesis we examine decoding of polar codes and LDPC codes under the assumption that the memories that are used within the decoders are not fully reliable. We show that, in both cases, there is inherent fault-tolerance and we also propose some methods to reduce the effect of memory faults on the error-correcting performance of the considered decoders

Conflict resolution for pipelined layered LDPC decoders

International audienceMany of the current LDPC implementations of DVB-S2, T2 or WiMAX standard use the so-called layered architecture combined with pipeline. However, the pipeline process may introduce memory access conflicts. The resolution of these conflicts requires careful scheduling combined with dedicated hardware and/or idle cycle insertion. In this paper, based on the DVB-T2 example, we explain explicitly how the scheduling can solve most of the pipeline conflicts. The two contributions of the paper are 1) how to split the matrix to relax the pipeline conflicts at a cost of a reduced maximum available parallelism 2) how to project the problem of the research of an efficient scheduling to the well-known "Travelling Salesman Problem" and use a genetic algorithm to solve it