Parameters estimation from 1-bit dithered quantized data with dependent noise
SIP '07 Proceedings of the Ninth IASTED International Conference on Signal and Image Processing
Statistical results for system identification based on quantized observations
Automatica (Journal of IFAC)
Performance limit for distributed estimation systems with identical one-bit quantizers
IEEE Transactions on Signal Processing
Achievable diversity limits in a quantized MIMO-OFDM linear pre-coded system
ISWPC'10 Proceedings of the 5th IEEE international conference on Wireless pervasive computing
Nonparametric one-bit quantizers for distributed estimation
IEEE Transactions on Signal Processing
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The effects of sampling and quantization on frequency estimation for a single sinusoid are investigated. The Cramer-Rao bound for 1-bit quantization is derived and compared with the limit of infinite quantization. It is found that 1-bit quantization gives a slightly worse performance, however, with a dramatic increase of variance at certain frequencies. This can be avoided by using four times oversampling. The effect of sampling when using nonideal antialiasing lowpass filters is therefore investigated through derivation of the Cramer-Rao lower bounds. Finally, fast estimators for 1-bit quantization, in particular, correlation-based estimators, are derived, and their performance is investigated. The paper is concluded with simulation results for four times oversampled 1-bit quantization