Comprehensive approach to optimization of adaptive cyclic A/D converters for arbitrary number of conversion cycles

Abstract

Abstract An integrated analytical approach to improve the performance of adaptive sub-ranging analog-to-digital converters (ADCs) in both pre-threshold phase and post-threshold phase of their operation is presented and discussed. The differentia specifica of the adaptive ADCs, discriminating them from conventional sub-ranging ADCs, is the method of forming output codes of converted samples. The adaptive ADCs employ simple internal digital processing units (DPUs) to compute the output codes, which creates the conditions for optimization of the conversion algorithm and improvement of their effective number of bits (ENOB) beyond ENOB of their conventional counterparts. Previous researches led to development of two main groups of conversion algorithms used in adaptive ADCs, however none fully satisfactory. A new, hybrid conversion algorithm for the adaptive ADCs that combines the most desired features of each of the two groups of algorithms is proposed and investigated in this paper. It provides the greatest possible rate of increase of ENOB per cycle of conversion in the first, pre-threshold phase of conversion, and enables further increase of ENOB in the following, post-threshold phase.