Multi-Layer Parallel Decoding Algorithm and VLSI Architecture for Quasi-Cyclic LDPC Codes

We propose a multi-layer parallel decoding algorithm and VLSI architecture for decoding of structured quasi-cyclic low-density parity-check codes. In the conventional layered decoding algorithm, the block-rows of the parity check matrix are processed sequentially, or layer after layer. The maximum number of rows that can be simultaneously processed by the conventional layered decoder is limited to the sub-matrix size. To remove this limitation and support layer-level parallelism, we extend the conventional layered decoding algorithm and architecture to enable simultaneously processing of multiple (K) layers of a parity check matrix, which will lead to a roughly K-fold throughput increase. As a case study, we have designed a double-layer parallel LDPC decoder for the IEEE 802.11n standard. The decoder was synthesized for a TSMC 45-nm CMOS technology. With a synthesis area of 0.81 mm2 and a maximum clock frequency of 815 MHz, the decoder achieves a maximum throughput of 3.0 Gbps at 15 iterations

Modeling and Energy Optimization of LDPC Decoder Circuits with Timing Violations

This paper proposes a "quasi-synchronous" design approach for signal processing circuits, in which timing violations are permitted, but without the need for a hardware compensation mechanism. The case of a low-density parity-check (LDPC) decoder is studied, and a method for accurately modeling the effect of timing violations at a high level of abstraction is presented. The error-correction performance of code ensembles is then evaluated using density evolution while taking into account the effect of timing faults. Following this, several quasi-synchronous LDPC decoder circuits based on the offset min-sum algorithm are optimized, providing a 23%-40% reduction in energy consumption or energy-delay product, while achieving the same performance and occupying the same area as conventional synchronous circuits.Comment: To appear in IEEE Transactions on Communication

Deriving Good LDPC Convolutional Codes from LDPC Block Codes

Low-density parity-check (LDPC) convolutional codes are capable of achieving excellent performance with low encoding and decoding complexity. In this paper we discuss several graph-cover-based methods for deriving families of time-invariant and time-varying LDPC convolutional codes from LDPC block codes and show how earlier proposed LDPC convolutional code constructions can be presented within this framework. Some of the constructed convolutional codes significantly outperform the underlying LDPC block codes. We investigate some possible reasons for this "convolutional gain," and we also discuss the --- mostly moderate --- decoder cost increase that is incurred by going from LDPC block to LDPC convolutional codes.Comment: Submitted to IEEE Transactions on Information Theory, April 2010; revised August 2010, revised November 2010 (essentially final version). (Besides many small changes, the first and second revised versions contain corrected entries in Tables I and II.

A Flexible LDPC/Turbo Decoder Architecture

Low-density parity-check (LDPC) codes and convolutional Turbo codes are two of the most powerful error correcting codes that are widely used in modern communication systems. In a multi-mode baseband receiver, both LDPC and Turbo decoders may be required. However, the different decoding approaches for LDPC and Turbo codes usually lead to different hardware architectures. In this paper we propose a unified message passing algorithm for LDPC and Turbo codes and introduce a flexible soft-input soft-output (SISO) module to handle LDPC/Turbo decoding. We employ the trellis-based maximum a posteriori (MAP) algorithm as a bridge between LDPC and Turbo codes decoding. We view the LDPC code as a concatenation of n super-codes where each super-code has a simpler trellis structure so that the MAP algorithm can be easily applied to it. We propose a flexible functional unit (FFU) for MAP processing of LDPC and Turbo codes with a low hardware overhead (about 15% area and timing overhead). Based on the FFU, we propose an area-efficient flexible SISO decoder architecture to support LDPC/Turbo codes decoding. Multiple such SISO modules can be embedded into a parallel decoder for higher decoding throughput. As a case study, a flexible LDPC/Turbo decoder has been synthesized on a TSMC 90 nm CMOS technology with a core area of 3.2 mm2. The decoder can support IEEE 802.16e LDPC codes, IEEE 802.11n LDPC codes, and 3GPP LTE Turbo codes. Running at 500 MHz clock frequency, the decoder can sustain up to 600 Mbps LDPC decoding or 450 Mbps Turbo decoding.NokiaNokia Siemens Networks (NSN)XilinxTexas InstrumentsNational Science Foundatio

Ultra-low power LDPC decoder design with high parallelism for wireless communication system

制度:新 ; 報告番号:甲3423号 ; 学位の種類:博士(工学) ; 授与年月日:2011/9/15 ; 早大学位記番号:新574

Research on energy-efficient VLSI decoder for LDPC code

制度:新 ; 報告番号:甲3742号 ; 学位の種類:博士(工学) ; 授与年月日:2012/9/15 ; 早大学位記番号:新6113Waseda Universit

Design Trade‐Offs for FPGA Implementation of LDPC Decoders

Low density parity check (LDPC) decoders represent important throughput bottlenecks, as well as major cost and power-consuming components in today\u27s digital circuits for wireless communication and storage. They present a wide range of architectural choices, with different throughput, cost, and error correction capability trade-offs. In this book chapter, we will present an overview of the main design options in the architecture and implementation of these circuits on field programmable gate array (FPGA) devices. We will present the mapping of the main units within the LDPC decoders on the specific embedded components of FPGA device. We will review architectural trade-offs for both flooded and layered scheduling strategies in their FPGA implementation