  Precise localization is one key element of the Internet of Things (IoT).
Especially concepts for position estimation when Global Navigation Satellite
Systems (GNSS) are unavailable have moved into the focus. One crucial component
for localization systems in general and precise runtime-based positioning, in
particular, is the necessity of ultra-precise clock synchronization between the
receiving base stations. Our work presents a software-based approach for the
wireless synchronization of spatially separated base stations using a low-cost
off-the-shelf frontend architecture. The proposed system estimates the time
synchronization, sampling clock offset, and carrier frequency offset using
broadcast signals as Signals of Opportunity. In this paper, we derive the
theoretical lower bound for the estimation variance according to the Modified
Cramer-Rao Bound. We show that a theoretical time synchronization accuracy in
the range of ps and a frequency synchronization precision in the range of
milli-Hertz is achievable. An algorithm is presented that estimates the desired
parameter based on evaluating the Cross-Correlation Function between base
stations. Initial measurements are conducted in a real-world environment. It is
shown that the presented estimator nearly reaches the theoretical bound within
a time and frequency synchronization accuracy of down to 200 ps and 6 mHz,
respectively.
