Quantization-loss reduction for signal parameter estimation

Using coarse resolution analog-to-digital conversion (ADC) offers the possibility to reduce the complexity of digital receive systems but introduces a loss in effective signal-to-noise ratio (SNR) when comparing to ideal receivers with infinite resolution ADC. Therefore, here the problem of signal parameter estimation from a coarsely quantized receive signal is considered. In order to increase the system performance, we propose to adjust the analog radio front-end to the quantization device in order to reduce the quantizationloss. By optimizing the bandwidth of the analog filter with respect to a weighted form of the Cramér-Rao lower bound (CRLB), we show that for low SNR and a 1-bit hard-limiting device it is possible to significantly reduce the quantizationloss of initially -1.96 dB. As application, joint carrier-phase and time-delay estimation for satellite-based positioning and synchronization is discussed. Simulations of the maximum-likelihood estimator (MLE) show that the optimum estimator achieves the same quantization-loss reduction as predicted by the performance bound of the optimized system.