GA-based Optimization of Sigma-delta Modulators for Wireless Transceivers

Over-sampling sigma-delta analog-todigital converters (ADCs) are one of the key building blocks of state of the art wireless transceivers. In sigma-delta modulator design, the scaling coefficients determine the peak signal-to-noise ratio. Therefore, selecting the optimum value of the coefficient is very important. To this end, this paper addresses the design of a fourth-order multi-bit sigma-delta modulator suitable for Wireless Local Area Networks (WLAN) receivers with feed forward path and the optimum coefficients were selected using genetic algorithm (GA)based search method. In particular, the proposed converter makes use of low-distortion swing suppression SDM architecture which is highly suitable for low oversampling ratios to attain high linearity over a wide bandwidth. A second-order traditional topology has been chosen as the second design example to validate our proposed method. The aim of this paper is the identification of the best coefficients suitable for the proposed topology in order to achieve the desired signal-to-noise ratio. GA-based search engine is a stochastic search method which can find the optimum solution within the given constraints.