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5G millimeter wave (mmWave) signals can enable accurate positioning in vehicular networks when the base station (BS) and vehicles are equipped with large antenna arrays. However, radiobased positioning suffers from multipath signals generated by different types of objects in the physical environment. Multipath can be turned into a benefit, by building up a radio map (comprising the number of objects, object type, and object state) and using this map to exploit all available signal paths for positioning. Building such a map is challenging, due to the inherent data association uncertainty, missed detection, and clutter. We propose a new method for cooperative vehicle positioning and mapping of the radio environment in order to address these challenges. The proposed method comprises a multimodel probability hypothesis density (PHD) filter and a map fusion routine, which is able to consider different types of objects and different fields of views (FoVs). Simulation results demonstrate that the proposed method handles the aforementioned challenges, and improves the vehicle positioning and mapping performance.

5G communication systems operating above 24 GHz have promising properties for user localization and environment mapping. Existing studies have either relied on simplified abstract models of the signal propagation and the measurements, or are based on direct positioning approaches, which directly map the received waveform to a position. In this study, we consider an intermediate approach, which consists of four phases—downlink data transmission, multi-dimensional channel estimation, channel parameter clustering, and simultaneous localization and mapping (SLAM) based on a novel likelihood function. This approach can decompose the problem into simpler steps, thus leading to lower complexity. At the same time, by considering an end-to-end processing chain, we are accounting for a wide variety of practical impairments. Simulation results demonstrate the efficacy of the proposed approach.

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BackgroundAmbroxol (ABX) has been suggested as an augmentative pharmacological agent for neuronopathic Gaucher disease (nGD). This study assessed the long-term safety and efficacy of combined therapy with high-dose ABX and enzyme replacement therapy (ERT) in nGD.MethodsABX+ERT therapy was administered for 4.5 years in four patients with nGD. ABX was initiated at a dose of 1.5 mg/kg/day, and the dose was escalated up to 27 mg/kg/day. The target plasma level was 10 µmol/L or less. The changes in glucocerebrosidase activity, biochemical, safety and neurocognitive findings were assessed.ResultsEnhanced residual GCcase activity was observed in all patients, as evidenced in both in vitro and in vivo studies. During the first 2 years of study with ABX (up to 21 mg/kg/day), mean seizure frequencies and neurocognitive function worsened. After ABX dosage was increased up to 27 mg/kg/day of ABX, its trough plasma concentration was 3.2–8.8 µmol/L. Drug-to-drug interaction, especially with antiepileptic drug significantly affected the pharmacokinetic parameters of ABX. Importantly, at 27 mg/kg/day of ABX, the seizure frequencies markedly decreased from the baseline, and the neurocognitive function was improved. In addition, Lyso-Gb1, a biomarker for the severity and progression of GD, was normalised in all patients. High-dose ABX was well-tolerated with no severe adverse events.ConclusionsLong-term treatment with high-dose ABX+ERT was safe and might help to arrest the progression of the neurological manifestations in GD.

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