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

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

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

VLSI Decoder Architecture for High Throughput, Variable Block-size and Multi-rate LDPC Codes

A low-density parity-check (LDPC) decoder architecture that supports variable block sizes and multiple code rates is presented. The proposed architecture is based on the structured quasi-cyclic (QC-LDPC) codes whose performance compares favorably with that of randomly constructed LDPC codes for short to moderate block sizes. The main contribution of this work is to address the variable block-size and multirate decoder hardware complexity that stems from the irregular LDPC codes. The overall decoder, which was synthesized, placed and routed on TSMC 0.13-micron CMOS technology with a core area of 4.5 square millimeters, supports variable code lengths from 360 to 4200 bits and multiple code rates between 1/4 and 9/10. The average throughput can achieve 1 Gbps at 2.2 dB SNR.NokiaNational Science Foundatio

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

Concatenated Turbo/LDPC codes for deep space communications: performance and implementation

Deep space communications require error correction codes able to reach extremely low bit-error-rates, possibly with a steep waterfall region and without error floor. Several schemes have been proposed in the literature to achieve these goals. Most of them rely on the concatenation of different codes that leads to high hardware implementation complexity and poor resource sharing. This work proposes a scheme based on the concatenation of non-custom LDPC and turbo codes that achieves excellent error correction performance. Moreover, since both LDPC and turbo codes can be decoded with the BCJR algorithm, our preliminary results show that an efficient hardware architecture with high resource reuse can be designe