The Cramer-Rao Bound for Signal Parameter Estimation From Quantized Data [Lecture Notes]

Several current ultrawide band applications, such as millimeter-wave radar and communication systems [1]-[3], require high sampling rates and therefore expensive and energy-hungry analog-to-digital converters (ADCs). In applications where cost and power constraints exist, the use of high-precision ADCs is not feasible, and the designer must resort to ADCs with coarse quantization. Consequently, the interest in the topic of signal parameter estimation from quantized data has increased significantly in recent years.

Automated summary

Several ultrawide band applications require high sampling rates that necessitate expensive and energy-consuming ADCs. In cost and power-constrained applications, the use of coarse quantization ADCs becomes necessary. As a result, the interest in signal parameter estimation from quantized data has significantly increased in recent years.