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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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194 records · Page 11
All sourcesNASA NTRSDOE OSTI
NASA NTRS1990

VLSI Architecture For Viterbi Decoder

"Pipeline" architecture developed for very-large-scale integrated (VLSI) Viterbi decoding circuits for binary convolutional codes of large constraint lengths. In scheme, single sequential processor computes path metrics in trellis diagram (diagram in which paths and nodes represent possible sequences of code states and in which metrics indicate relative likelihoods of sequences). Systolic-array method used to store path information as well as to choose path with best metric. VLSI Viterbi-decoder architecture is compromise between speed and complexity. Size of decoding circuit increases approximately linearly with constraint length of code, and additional circuit chips added with moderate numbers of interconnections.

Hsu, In-Shek↗
NASA NTRS1989

Systolic array processing of the Viterbi algorithm

Results on efficient forms of decoding convolutional codes based on the Viterbi algorithm by using systolic arrays are presented. Various properties of convolutional codes are discussed. A technique called strongly connected trellis decoding is introduced to increase the efficient utilization of all the systolic array processors. Issues dealing with the composite branch metric generation, survivor updating, overall system architecture, throughput rate, and computational overhead ratio also investigated. The scheme is applicable to both hard and soft decoding of any rate b/n convolutional code. It is shown that as the length of the code becomes large, the systolic Viterbi decoder maintains a regular and general interconnection structure as well as moderate throughput rate gain over the sequential Viterbi decoder.

Chang, Chi-Yung↗
NASA NTRS1989

Advances in image compression and automatic target recognition; Proceedings of the Meeting, Orlando, FL, Mar. 30, 31, 1989

Various papers on image compression and automatic target recognition are presented. Individual topics addressed include: target cluster detection in cluttered SAR imagery, model-based target recognition using laser radar imagery, Smart Sensor front-end processor for feature extraction of images, object attitude estimation and tracking from a single video sensor, symmetry detection in human vision, analysis of high resolution aerial images for object detection, obscured object recognition for an ATR application, neural networks for adaptive shape tracking, statistical mechanics and pattern recognition, detection of cylinders in aerial range images, moving object tracking using local windows, new transform method for image data compression, quad-tree product vector quantization of images, predictive trellis encoding of imagery, reduced generalized chain code for contour description, compact architecture for a real-time vision system, use of human visibility functions in segmentation coding, color texture analysis and synthesis using Gibbs random fields.

Tescher, Andrew G.↗
NASA NTRS1995

Turbo Codes for PCS Applications

A number of the claims for turbo codes as a great advance in coding theory are confirmed, and a complete description is presented of an encoder/decoder pair that could be suitable for PCS applications. A new simple method for trellis termination is described, the effect of interleaver choice on the weight distribution of the code is analyzed, and unequal rate components (which yield better performance) are introduced.

coding turbo codes personal communication systems ↗
NASA NTRS1996

Architecture and implementation considerations of a high-speed Viterbi decoder for a Reed-Muller subcode

The (64, 40, 8) subcode of the third-order Reed-Muller (RM) code for high-speed satellite communications is proposed. The RM subcode can be used either alone or as an inner code of a concatenated coding system with the NASA standard (255, 233, 33) Reed-Solomon (RS) code as the outer code to achieve high performance (or low bit-error rate) with reduced decoding complexity. It can also be used as a component code in a multilevel bandwidth efficient coded modulation system to achieve reliable bandwidth efficient data transmission. The progress made toward achieving the goal of implementing a decoder system based upon this code is summarized. The development of the integrated circuit prototype sub-trellis IC, particularly focusing on the design methodology, is addressed.

Lin, Shu↗
NASA NTRS1996

An Iterative Soft-Decision Decoding Algorithm

This paper presents a new minimum-weight trellis-based soft-decision iterative decoding algorithm for binary linear block codes. Simulation results for the RM(64,22), EBCH(64,24), RM(64,42) and EBCH(64,45) codes show that the proposed decoding algorithm achieves practically (or near) optimal error performance with significant reduction in decoding computational complexity. The average number of search iterations is also small even for low signal-to-noise ratio.

Lin, Shu↗
NASA NTRS2014

Protograph-Based Raptor-Like Codes

Theoretical analysis has long indicated that feedback improves the error exponent but not the capacity of pointto- point memoryless channels. The analytic and empirical results indicate that at short blocklength regime, practical rate-compatible punctured convolutional (RCPC) codes achieve low latency with the use of noiseless feedback. In 3GPP, standard rate-compatible turbo codes (RCPT) did not outperform the convolutional codes in the short blocklength regime. The reason is the convolutional codes for low number of states can be decoded optimally using Viterbi decoder. Despite excellent performance of convolutional codes at very short blocklengths, the strength of convolutional codes does not scale with the blocklength for a fixed number of states in its trellis.

Divsalar, Dariush↗
NASA NTRS1996

Bit Error Probability for Maximum Likelihood Decoding of Linear Block Codes

In this paper, the bit error probability P(sub b) for maximum likelihood decoding of binary linear codes is investigated. The contribution of each information bit to P(sub b) is considered. For randomly generated codes, it is shown that the conventional approximation at high SNR P(sub b) is approximately equal to (d(sub H)/N)P(sub s), where P(sub s) represents the block error probability, holds for systematic encoding only. Also systematic encoding provides the minimum P(sub b) when the inverse mapping corresponding to the generator matrix of the code is used to retrieve the information sequence. The bit error performances corresponding to other generator matrix forms are also evaluated. Although derived for codes with a generator matrix randomly generated, these results are shown to provide good approximations for codes used in practice. Finally, for decoding methods which require a generator matrix with a particular structure such as trellis decoding or algebraic-based soft decision decoding, equivalent schemes that reduce the bit error probability are discussed.

Lin, Shu↗
NASA NTRS1988

Method for Veterbi decoding of large constraint length convolutional codes

A new method of Viterbi decoding of convolutional codes lends itself to a pipline VLSI architecture using a single sequential processor to compute the path metrics in the Viterbi trellis. An array method is used to store the path information for NK intervals where N is a number, and K is constraint length. The selected path at the end of each NK interval is then selected from the last entry in the array. A trace-back method is used for returning to the beginning of the selected path back, i.e., to the first time unit of the interval NK to read out the stored branch metrics of the selected path which correspond to the message bits. The decoding decision made in this way is no longer maximum likelihood, but can be almost as good, provided that constraint length K in not too small. The advantage is that for a long message, it is not necessary to provide a large memory to store the trellis derived information until the end of the message to select the path that is to be decoded; the selection is made at the end of every NK time unit, thus decoding a long message in successive blocks.

Hsu, In-Shek↗
NASA NTRS1990

Cross-over component code construction for multi-level block modulation codes

This paper investigates the multilevel technique for combining block coding and modulation. Several specific methods for constructing multilevel block modulation codes with interdependency among component codes are presented. Given a multilevel block modulation code C with no interdependency among the binary component codes, the proposed methods give a multilevel block modulation code C-prime which has the same rate as C, a minimum squared Euclidean distance not less than that of C, a trellis diagram with the same number of states as that of C, and a smaller number of nearest neighbor codewords than that of C.

Kasami, Tadao↗
NASA NTRS1994

An efficient system for reliably transmitting image and video data over low bit rate noisy channels

This research project is intended to develop an efficient system for reliably transmitting image and video data over low bit rate noisy channels. The basic ideas behind the proposed approach are the following: employ statistical-based image modeling to facilitate pre- and post-processing and error detection, use spare redundancy that the source compression did not remove to add robustness, and implement coded modulation to improve bandwidth efficiency and noise rejection. Over the last six months, progress has been made on various aspects of the project. Through our studies of the integrated system, a list-based iterative Trellis decoder has been developed. The decoder accepts feedback from a post-processor which can detect channel errors in the reconstructed image. The error detection is based on the Huber Markov random field image model for the compressed image. The compression scheme used here is that of JPEG (Joint Photographic Experts Group). Experiments were performed and the results are quite encouraging. The principal ideas here are extendable to other compression techniques. In addition, research was also performed on unequal error protection channel coding, subband vector quantization as a means of source coding, and post processing for reducing coding artifacts. Our studies on unequal error protection (UEP) coding for image transmission focused on examining the properties of the UEP capabilities of convolutional codes. The investigation of subband vector quantization employed a wavelet transform with special emphasis on exploiting interband redundancy. The outcome of this investigation included the development of three algorithms for subband vector quantization. The reduction of transform coding artifacts was studied with the aid of a non-Gaussian Markov random field model. This results in improved image decompression. These studies are summarized and the technical papers included in the appendices.

Costello, Daniel J., Jr.↗
NASA NTRS1991

On multilevel block modulation codes

The multilevel (ML) technique for combining block coding and modulation is investigated. A general formulation is presented for ML modulation codes in terms of component codes with appropriate distance measures. A specific method for constructing ML block modulation codes (MLBMCs) with interdependency among component codes is proposed. Given an MLBMC C with no interdependency among the binary component codes, the proposed method gives an MLBC C-prime that has the same rate as C, a minimum squared Euclidean distance not less than that of C, a trellis diagram with the same number of states as that of C, and a smaller number of nearest-neighbor codewords than that of C. Finally, a technique is presented for analyzing the error performance of MLBMCs for an additive white Gaussian noise channel based on soft-decision maximum-likelihood decoding.

Kasami, Tadao↗
NASA NTRS2007

Optimizations of a Hardware Decoder for Deep-Space Optical Communications

The National Aeronautics and Space Administration has developed a capacity approaching modulation and coding scheme that comprises a serial concatenation of an inner accumulate pulse-position modulation (PPM) and an outer convolutional code [or serially concatenated PPM (SCPPM)] for deep-space optical communications. Decoding of this code uses the turbo principle. However, due to the nonbinary property of SCPPM, a straightforward application of classical turbo decoding is very inefficient. Here, we present various optimizations applicable in hardware implementation of the SCPPM decoder. More specifically, we feature a Super Gamma computation to efficiently handle parallel trellis edges, a pipeline-friendly 'maxstar top-2' circuit that reduces the max-only approximation penalty, a low-latency cyclic redundancy check circuit for window-based decoders, and a high-speed algorithmic polynomial interleaver that leads to memory savings. Using the featured optimizations, we implement a 6.72 megabits-per-second (Mbps) SCPPM decoder on a single field-programmable gate array (FPGA). Compared to the current data rate of 256 kilobits per second from Mars, the SCPPM coded scheme represents a throughput increase of more than twenty-six fold. Extension to a 50-Mbps decoder on a board with multiple FPGAs follows naturally. We show through hardware simulations that the SCPPM coded system can operate within 1 dB of the Shannon capacity at nominal operating conditions.

quadratic polynomial interleaver↗
NASA NTRS1986

Simplified Decoding of Convolutional Codes

Some complicated intermediate steps shortened or eliminated. Decoding of convolutional error-correcting digital codes simplified by new errortrellis syndrome technique. In new technique, syndrome vector not computed. Instead, advantage taken of newly-derived mathematical identities simplify decision tree, folding it back on itself into form called "error trellis." This trellis graph of all path solutions of syndrome equations. Each path through trellis corresponds to specific set of decisions as to received digits. Existing decoding algorithms combined with new mathematical identities reduce number of combinations of errors considered and enable computation of correction vector directly from data and check bits as received.

Truong, T. K.↗