Design and implementation of log domain decoder

Low-Density-Parity-Check (LDPC) code has become famous in communications systems for error correction, as an advantage of the robust performance in correcting errors and the ability to meet all the requirements of the 5G system. However, the mot challenge faced researchers is the hardware implementation, because of higher complexity and long run-time. In this paper, an efficient and optimum design for log domain decoder has been implemented using Xilinx system generator with FPGA device Kintex 7 (XC7K325T-2FFG900C). Results confirm that the proposed decoder gives a Bit Error Rate (BER) very closed to theory calculations which illustrate that this decoder is suitable for next generation demand which needs high data rate with very low BER

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

Low-Power 400-Gbps Soft-Decision LDPC FEC for Optical Transport Networks

We present forward error correction systems based on soft-decision low-density parity check (LDPC) codes for applications in 100–400-Gbps optical transport networks. These systems are based on the low-complexity “adaptive degeneration” decoding algorithm, which we introduce in this paper, along with randomly-structured LDPC codes with block lengths from 30 000 to 60 000 bits and overhead (OH) from 6.7% to 33%. We also construct a 3600-bit prototype LDPC code with 20% overhead, and experimentally show that it has no error floor above a bit error rate (BER) of 10−15 using a field-programmable gate array (FPGA)-based hardware emulator. The projected net coding gain at a BER of 10−15 ranges from 9.6 dB at 6.7% OH to 11.2 dB at 33% OH. We also present application-specific integrated circuit synthesis results for these decoders in 28 nm fully depleted silicon on insulator technology, which show that they are capable of 400-Gbps operation with energy consumption of under 3 pJ per information bit

Hardware Implementations of CCSDS Deep Space LDPC Codes for a Satellite Transponder

Error-correction coding is a technique that adds mathematical structure to a message, allowing corruptions to be detected and corrected when the message is received. This is especially important for deep space satellite communications, since the long distances and low signal power levels often cause message corruption. A very strong type of error-correction coding known as LDPC codes was recently standardized for use with space communications. This project implements the encoding and decoding algorithms required for a small satellite radio to be able to use these LDPC codes. Several decoder architectures are implemented and compared by their performance, speed, and complexity. Using these LDPC decoders requires knowledge of the received signal and noise levels, so an appropriate algorithm for estimating these parameters is developed and implemented. The LDPC encoder is implemented using a flexible architecture that allows the entire standardized family of ten LDPC codes to be encoded using the same hardware

GF(q) LDPC encoder and decoder FPGA implementation using group shuffled belief propagation algorithm

This paper presents field programmable gate array (FPGA) exercises of the GF(q) low-density parity-check (LDPC) encoder and interpreter utilizing the group shuffled belief propagation (GSBP) algorithm are presented in this study. For small blocks, non-dual LDPC codes have been shown to have a greater error correction rate than dual codes. The reduction behavior of non-binary LDPC codes over GF (16) (also known as GF(q)-LDPC codes) over the additive white Gaussian noise (AWGN) channel has been demonstrated to be close to the Shannon limit and employs a short block length (N=600 bits). At the same time, it also provides a non-binary LDPC (NB-LDPC) code set program. Furthermore, the simplified bubble check treasure event count is implemented through the use of first in first out (FIFO), which is based on an elegant design. The structure of the interpreter and the creation of the residential area he built were planned in very high speed integrated circuit (VHSIC) hardware description language (VHDL) and simulated in MODELSIM 6.5. The combined output of the Cyclone II FPGA is combined with the simulation output

A survey of FPGA-based LDPC decoders

Low-Density Parity Check (LDPC) error correction decoders have become popular in communications systems, as a benefit of their strong error correction performance and their suitability to parallel hardware implementation. A great deal of research effort has been invested into LDPC decoder designs that exploit the flexibility, the high processing speed and the parallelism of Field-Programmable Gate Array (FPGA) devices. FPGAs are ideal for design prototyping and for the manufacturing of small-production-run devices, where their in-system programmability makes them far more cost-effective than Application-Specific Integrated Circuits (ASICs). However, the FPGA-based LDPC decoder designs published in the open literature vary greatly in terms of design choices and performance criteria, making them a challenge to compare. This paper explores the key factors involved in FPGA-based LDPC decoder design and presents an extensive review of the current literature. In-depth comparisons are drawn amongst 140 published designs (both academic and industrial) and the associated performance trade-offs are characterised, discussed and illustrated. Seven key performance characteristics are described, namely their processing throughput, latency, hardware resource requirements, error correction capability, processing energy efficiency, bandwidth efficiency and flexibility. We offer recommendations that will facilitate fairer comparisons of future designs, as well as opportunities for improving the design of FPGA-based LDPC decoder

A software-defined receiver for laser communications using a GPU

This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2018Cataloged from PDF version of thesis.Includes bibliographical references (pages 43-46).Laser commiunication systems provide a high data rate, power efficient communication solution for small satellites and deep space missions. One challenge that limits the widespread use of laser communication systems is the lack of accessible, low-complexity receiver electronics and software implementations. Graphics Processing Units (GPUs) can reduce the complexity in receiver design since GPUs require less specialized knowledge and can enable faster development times than Field Programmnable Cate Array (FPGA) implementations, while still retaining comparable data throughputs via parallelization. This thesis explores the use of a Graphics Processing Unit (GPU) as the sole computational unit for the signal processing algorithms involved in laser conmnunications.by Joseph Matthew Kusters.M. Eng.M.Eng. Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Scienc