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Accurate and ubiquitous localization is crucial for a variety of applicationssuch as logistics, navigation, intelligent transport, monitoring, control, andalso for the benefit of communications. Exploiting millimeter-wave (mmWave)signals in 5G and Beyond 5G systems can provide accurate localization withlimited infrastructure. We consider the single base station (BS) localizationproblem and extend it to 3D position and 3D orientation estimation of anunsynchronized multi-antenna user equipment (UE), using downlink multiple-inputmultiple-output orthogonal frequency-division multiplexing (MIMO-OFDM) signals.Through a Fisher information analysis, we show that the problem is oftenidentifiable, provided that there is at least one multipath component inaddition to the line-of-sight (LoS), even if the position of correspondingincidence point (IP) is a priori unknown. Subsequently, we pose a maximumlikelihood (ML) estimation problem, to jointly estimate the 3D position and 3Dorientation of the UE as well as several nuisance parameters (the UE clockoffset and the positions of IPs corresponding to the multipath). The ML problemis a high-dimensional non-convex optimization problem over a product ofEuclidean and non-Euclidean manifolds. To avoid complex exhaustive searchprocedures, we propose a geometric initial estimate of all parameters, whichreduces the problem to a 1-dimensional search over a finite interval. Numericalresults show the efficiency of the proposed ad-hoc estimation, whose gap to theCram\'er-Rao bound (CRB) is tightened using the ML estimation.

MmWave 6D Radio Localization with a Snapshot Observation from a Single BS