Asymptotic Performance Analysis for 1-bit Bayesian Smoothing
arXiv:1511.05318
Abstract
Energy-efficient signal processing systems require estimation methods operating on data collected with low-complexity devices. Using analog-to-digital converters (ADC) with -bit amplitude resolution has been identified as a possible option in order to obtain low power consumption. The -bit performance loss, in comparison to an ideal receiver with -bit ADC, is well-established and moderate for low SNR applications ( or dB). Recently it has been shown that for parameter estimation with state-space models the -bit performance loss with Bayesian filtering can be significantly smaller ( or dB). Here we extend the analysis to Bayesian smoothing where additional measurements are used to reconstruct the current state of the system parameter. Our results show that a -bit receiver performing smoothing is able to outperform an ideal -bit system carrying out filtering by the cost of an additional processing delay .