Improving SNR for DSM Linear Systems Using Probabilistic Error Correction and State Restoration: A Comparative Study

Smaller feature sizes and lower supply voltages make DSM devices more susceptible to soft errors generated by alpha particles and neutrons as well as other sources of environmental noise. In this scenario, soft-error/noise tolerant techniques are necessary for maintaining the SNR of critical DSP applications. This paper studies linear DSP circuits and discusses two low cost techniques for improving the SNR of DSP filters. Both techniques use a single checksum variable for error detection. This gives a distance two code that is traditionally good for error detection but not correction. In this paper, such a code is used to improve SNR rather than perfectly remove the error. The first technique, ´checksum-based probabilistic error correction´, uses the value indicated by the checksum variable to probabilistically correct the error and achieves up to 5 dB improvement in the SNR value. The second technique, ´state restoration´, works well when the length of burst errors is small and the error magnitude is large. A general error statistics has been defined as a random process and the distribution of SNR is compared for the two proposed techniques