A Parallelized Layered QC-LDPC Decoder for IEEE 802.11ad

We present a doubly parallelized layered quasi-cyclic low density parity-check decoder for the emerging IEEE 802.11ad multigigabit wireless standard. The decoding algorithm is equivalent to a nonparallelized layered decoder and, thus, retains its favorable convergence characteristics, which are known to be superior to those of flooding schedule based decoders. The proposed architecture was synthesized using a TSMC 40 nm CMOS technology, resulting in a cell area of 0.18 mm2 and a clock frequency of 850 MHz. At this clock frequency, the decoder achieves a coded throughput of 3.12 Gbps, thus meeting the throughput requirements when using both the mandatory BPSK modulation and the optional QPSK modulation

Comparison of Polar Decoders with Existing Low-Density Parity-Check and Turbo Decoders

Polar codes are a recently proposed family of provably capacity-achieving error-correction codes that received a lot of attention. While their theoretical properties render them interesting, their practicality compared to other types of codes has not been thoroughly studied. Towards this end, in this paper, we perform a comparison of polar decoders against LDPC and Turbo decoders that are used in existing communications standards. More specifically, we compare both the error-correction performance and the hardware efficiency of the corresponding hardware implementations. This comparison enables us to identify applications where polar codes are superior to existing error-correction coding solutions as well as to determine the most promising research direction in terms of the hardware implementation of polar decoders.Comment: Fixes small mistakes from the paper to appear in the proceedings of IEEE WCNC 2017. Results were presented in the "Polar Coding in Wireless Communications: Theory and Implementation" Worksho

Multiple Parallel Concatenated Gallager Codes: High Throughput Architecture Design and Implementation

The design of advanced wireless communication systems has been one of the most important research areas in recent years. High performance error correction schemes and high speed data services are at the heart of these systems. Due to the excellent performance of Low-Density Parity-Check (LDPC) codes, they are good candidates for many new wireless communication standards. However, complexity, latency scalability and flexibility remain a challenge. This thesis is concerned with investigating a new approach to coding and decoding LDPC codes based on Parallel Concatenated Gallager Code (PCGCs) using multiple constituent codes. These are a class of concatenated codes built from the direct parallel concatenation of LDPC codes without interleavers. They are characterized by a competitive BER performance while still maintaining the low complexity and flexibility attributes. New methods for encoding and decoding are presented together with BER simulation results showing the performance of these codes. Analysis in terms of the number of constituent codes is also carried out. Complexity analysis is performed and preliminary implementation results are also given based on a proposed high throughput architecture

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