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The design plan of a VLSI single chip (255, 223) Reed-Solomon decoder

The very large-scale integration (VLSI) architecture of a single chip (255, 223) Reed-Solomon decoder for decoding both errors and erasures is described. A decoding failure detection capability is also included in this system so that the decoder will recognize a failure to decode instead of introducing additional errors. This could happen whenever the received word contains too many errors and erasures for the code to correct. The number of transistors needed to implement this decoder is estimated at about 75,000 if the delay for received message is not included. This is in contrast to the older transform decoding algorithm which needs about 100,000 transistors. However, the transform decoder is simpler in architecture than the time decoder. It is therefore possible to implement a single chip (255, 223) Reed-Solomon decoder with today's VLSI technology. An implementation strategy for the decoder system is presented. This represents the first step in a plan to take advantage of advanced coding techniques to realize a 2.0 dB coding gain for future space missions.

Hsu, I. S.

VLSI design of turbo decoder for integrated communication system on a chip applications

A high-throughput low-power turbo decoder core has been developed for integrated communication system applications such as satellite communications, wireless LAN, digital TV, cable modem, Digital Video Broadcast (DVB), and xDSL systems. The turbo decoder is based on convolutional constituent codes, which outperform all other Forward Error Correction techniques. This turbo decoder core is parameterizable and can be modified easily to fit any size for advanced communication system-on-chip products. The turbo decoder core provides Forward Error Correction of up to 15 Mbits/sec on a 0.13-micron CMOS FPGA prototyping chip at a power of 0.1 watts.

turbo decoder

Robust Bioinformatics Recognition with VLSI Biochip Microsystem

A microsystem architecture for real-time, on-site, robust bioinformatic patterns recognition and analysis has been proposed. This system is compatible with on-chip DNA analysis means such as polymerase chain reaction (PCR)amplification. A corresponding novel artificial neural network (ANN) learning algorithm using new sigmoid-logarithmic transfer function based on error backpropagation (EBP) algorithm is invented. Our results show the trained new ANN can recognize low fluorescence patterns better than the conventional sigmoidal ANN does. A differential logarithmic imaging chip is designed for calculating logarithm of relative intensities of fluorescence signals. The single-rail logarithmic circuit and a prototype ANN chip are designed, fabricated and characterized.

bioinformatics

Optimizing costs of VLSI circuits

Report analyzes costs of developing and producing low-production-volume, customized VLSI (very large-scale, integrated) circuits. Relationship is developed between IC cost and electronic system cost using IC cost models based on design/fabrication approach. Emphasis is on development of understanding between cost and volume for custom circuits to be used by NASA. Reliability is major cost component in models. Report is divided into five sections and includes four appendices with useful reference literature.

Cook, K. B., Jr.