  In this article, we address the timely topic of cellular bistatic
simultaneous localization and mapping (SLAM) with specific focus on end-to-end
processing solutions, from raw I/Q samples, via channel parameter estimation to
user equipment (UE) and landmark location information in millimeter-wave
(mmWave) networks, with minimal prior knowledge. Firstly, we propose a new
multipath channel parameter estimation solution that operates directly with
beam reference signal received power (BRSRP) measurements, alleviating the need
to know the true antenna beam-patterns or the underlying beamforming weights.
Additionally, the method has built-in robustness against unavoidable antenna
sidelobes. Secondly, we propose new snapshot SLAM algorithms that have
increased robustness and identifiability compared to prior art, in practical
built environments with complex clutter and multi-bounce propagation scenarios,
and do not rely on any a priori motion model. The performance of the proposed
methods is assessed at the 60 GHz mmWave band, via both realistic ray-tracing
evaluations as well as true experimental measurements, in an indoor
environment. A wide set of offered results demonstrate the improved
performance, compared to the relevant prior art, in terms of the channel
parameter estimation as well as the end-to-end SLAM performance. Finally, the
article provides the measured 60 GHz data openly available for the research
community, facilitating results reproducibility as well as further algorithm
development.
