  Analog-to-digtial (A/D) conversion plays a crucial role when it comes to the
design of energy-efficient and fast signal processing systems. As its
complexity grows exponentially with the number of output bits, significant
savings are possible when resorting to a minimum resolution of a single bit.
However, then the nonlinear effect which is introduced by the A/D converter
results in a pronounced performance loss, in particular for the case when the
receiver is operated outside the low signal-to-noise ratio (SNR) regime. By
trading the A/D resolution for a moderately faster sampling rate, we show that
for time-of-arrival (TOA) estimation under any SNR level it is possible to
obtain a low-complexity $1$-bit receive system which features a smaller
performance degradation then the classical low SNR hard-limiting loss of
$2/\pi$ ($-1.96$ dB). Key to this result is the employment of a lower bound for
the Fisher information matrix which enables us to approximate the estimation
performance for coarsely quantized receivers with correlated noise models in a
pessimistic way.
