Simultaneous localization and mapping in millimeter wave networks with angle measurements

In this paper we propose a belief propagation (BP) based simultaneous localization and mapping (SLAM) approach suitable for millimeter wave (mm-Wave) networks. This approach leverages angle of arrival (AoA) and angle of departure (AoD) information with respect to multiple scatterers. Considering measurements from multiple base stations (BSs) and scatterers, seen as multiple sources, we solve out the data association problem from a centralized BP perspective, while jointly estimating the positions of both the mobile and scatterers. Simulations show that the proposed approach outperforms conventional distributed BS-wise BP methods in terms of estimation accuracy

Joint Localization and Mapping through Millimeter Wave MIMO in 5G Systems

Millimeter wave signals with multiple transmit and receive antennas are considered as enabling technology for enhanced mobile broadband services in 5G systems. While this combination is mainly associated with achieving high data rates, it also offers huge potential for radio-based positioning. Recent studies showed that millimeter wave signals with multiple transmit and receive antennas are capable of jointly estimating the position and orientation of a mobile terminal while mapping the radio environment simultaneously. To this end, we present a message passing-based estimator which jointly estimates the position and orientation of the mobile terminal, as well as the location of reflectors or scatterers in the absence of the line-of-sight path. We provide numerical examples showing that our estimator can provide considerably higher estimation accuracy compared to a state-of-the-art estimator. Our examples demonstrate that our message passing-based estimator neither requires the presence of a line-of-sight path nor prior knowledge regarding any of the parameters to be estimated

Joint Localization and Mapping through Millimeter Wave MIMO in 5G Systems - Extended Version

Millimeter wave signals with multiple transmit and receive antennas are considered as enabling technology for enhanced mobile broadband services in 5G systems. While this combination is mainly associated with achieving high data rates, it also offers huge potential for radio-based positioning. Recent studies showed that millimeter wave systems with multiple transmit and receive antennas are capable of jointly estimating the position and orientation of a mobile terminal while mapping the radio environment simultaneously. To this end, we present a message passing-based estimator which jointly estimates the position and orientation of the mobile terminal, as well as the location of reflectors or scatterers. We provide numerical examples showing that this estimator can provide considerably higher estimation accuracy compared to a state-of-the-art estimator. Our examples demonstrate that our message passing-based estimator neither requires the presence of a line-of-sight path nor prior knowledge regarding any of the parameters to be estimated

Multipath Assisted Positioning in Vehicular Applications

Precise localization and tracking in intelligent transportation systems has aroused great interest since it is required in a large variety of applications. The positioning accuracy of global navigation satellite systems is unreliable and insufficient enough for many use cases. In urban canyons or tunnels, the positioning performance degrades due to a low received signal power, multipath propagation, or signal blocking. Instead we exploit the ubiquitous access to cellular mobile radio networks. Cellular networks are designed to cover the access to the network in an area by a single link to reduce the risk of interference from neighboring base stations. The idea of Channel-SLAM is to exploit the numerous multipath components (MPCs) of a radio signal arriving at the receiver for positioning. Each MPC can be regarded as being sent from a virtual transmitter in a pure line-of-sight condition. Within this paper, we show how to apply multipath assisted positioning in an urban scenario. Therefore, we analyze how a road user equipped with a circular antenna array is tracked in an urban scenario in the presence of only one physical transmitter. We further jointly estimate the positions of the physical and the virtual transmitters to enrich maps