Study of single event upsets (SEUS) a survey and analysis

Over the last few years evolution in electronics technology has led to the shrinkage of electronic circuits. While this has led to the emergence of more powerful computing systems it has also caused a dramatic increase in the occurrence of soft errors and a steady climb in failure in time (FIT) rates. This problem is most prevalent in FPGA based systems which are highly susceptible to radiation induced errors. Depending upon the severity of the problem a number of methods exist to counter these effects including Triple Modular Redundancy (TMR), Error Control Coding (ECC), scrubbing systems etc. The following project presents a simulation of an FPGA based system that employs one of the popular error control code techniques called the Hamming Code. A resulting analysis shows that Hamming Code is able to mitigate the effects of single event upsets (SEUs) but suffers due to a number of limitations.

Study of single event upsets (SEUS) a survey and analysis

Over the last few years evolution in electronics technology has led to the shrinkage of electronic circuits. While this has led to the emergence of more powerful computing systems it has also caused a dramatic increase in the occurrence of soft errors and a steady climb in failure in time (FIT) rates. This problem is most prevalent in FPGA based systems which are highly susceptible to radiation induced errors. Depending upon the severity of the problem a number of methods exist to counter these effects including Triple Modular Redundancy (TMR), Error Control Coding (ECC), scrubbing systems etc. The following project presents a simulation of an FPGA based system that employs one of the popular error control code techniques called the Hamming Code. A resulting analysis shows that Hamming Code is able to mitigate the effects of single event upsets (SEUs) but suffers due to a number of limitations.

Communications using Sparse Signals

Inspired by compressive sensing principles, we propose novel error control coding techniques for communication systems. The information bits are encoded in the support and the non-zero entries of a sparse signal. By selecting a dictionary matrix with suitable dimensions, the codeword for transmission is obtained by multiplying the dictionary matrix with the sparse signal. Specifically, the codewords are obtained from the sparse linear combinations of the columns of the dictionary matrix. At the decoder, we employ variations of greedy sparse signal recovery algorithms. Using Gold code sequences and mutually unbiased bases from quantum information theory as dictionary matrices, we study the block error rate (BLER) performance of the proposed scheme in the AWGN channel. Our results show that the proposed scheme has a comparable and competitive performance with respect to the several widely used linear codes, for very small to moderate block lengths. In addition, our coding scheme extends straightforwardly to multi-user scenarios such as multiple access channel, broadcast channel, and interference channel. In these multi-user channels, if the users are grouped such that they have similar channel gains and noise levels, the overall BLER performance of our proposed scheme will coincide with an equivalent single-user scenario.

Communications using Sparse Signals

Inspired by compressive sensing principles, we propose novel error control coding techniques for communication systems. The information bits are encoded in the support and the non-zero entries of a sparse signal. By selecting a dictionary matrix with suitable dimensions, the codeword for transmission is obtained by multiplying the dictionary matrix with the sparse signal. Specifically, the codewords are obtained from the sparse linear combinations of the columns of the dictionary matrix. At the decoder, we employ variations of greedy sparse signal recovery algorithms. Using Gold code sequences and mutually unbiased bases from quantum information theory as dictionary matrices, we study the block error rate (BLER) performance of the proposed scheme in the AWGN channel. Our results show that the proposed scheme has a comparable and competitive performance with respect to the several widely used linear codes, for very small to moderate block lengths. In addition, our coding scheme extends straightforwardly to multi-user scenarios such as multiple access channel, broadcast channel, and interference channel. In these multi-user channels, if the users are grouped such that they have similar channel gains and noise levels, the overall BLER performance of our proposed scheme will coincide with an equivalent single-user scenario.