An Algorithm for High Precision Delta-Sigma Digital-to-Analog Converters

Software-defined radio accomplishes both modulation and demodulation processes using software. While this has a number of advantages, which includes flexibility, interoperability, sustainability, and adaptability, the requirement for sampling the signal for digital processes toward adequate recovery often involves the use of a fast but expensive analogue-todigital converter (ADC). This, in a way translates to higher cost and requirement for bigger storage. This paper presents a method of switched signal recovery at uniform sampling rates that are less than the frequently over-estimated Nyquist rate employed. In particular, an algorithm for achieving this was implemented for an AM wave, under-sampled at varied uniform rates up-to twice the carrier rate, and then demodulated using the Market Paradigm. Furthermore,the slope detectorwas also implemented by including a differentiator after the sampling stage of the algorithm. The simulated results showed that the algorithm was able to recover the message signal at sampling rates far less than twice the carrier rate without the need for any additional hardware. Specifically, the best value of the Spurious Free Dynamic Range (SFDR) obtained for the recovered message signal was 20dB at a sampling rate of less than 20% of the Nyquist rate for the carrier signal.

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An Algorithm for High Precision Delta-Sigma Digital-to-Analog Converters

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