471 research outputs found
Position and Orientation Estimation through Millimeter Wave MIMO in 5G Systems
Millimeter wave signals and large antenna arrays are considered enabling
technologies for future 5G networks. While their benefits for achieving
high-data rate communications are well-known, their potential advantages for
accurate positioning are largely undiscovered. We derive the Cram\'{e}r-Rao
bound (CRB) on position and rotation angle estimation uncertainty from
millimeter wave signals from a single transmitter, in the presence of
scatterers. We also present a novel two-stage algorithm for position and
rotation angle estimation that attains the CRB for average to high
signal-to-noise ratio. The algorithm is based on multiple measurement vectors
matching pursuit for coarse estimation, followed by a refinement stage based on
the space-alternating generalized expectation maximization algorithm. We find
that accurate position and rotation angle estimation is possible using signals
from a single transmitter, in either line-of- sight, non-line-of-sight, or
obstructed-line-of-sight conditions.Comment: The manuscript has been revised, and increased from 27 to 31 pages.
Also, Fig.2, Fig. 10 and Table I are adde
5G Positioning and Mapping with Diffuse Multipath
5G mmWave communication is useful for positioning due to the geometric
connection between the propagation channel and the propagation environment.
Channel estimation methods can exploit the resulting sparsity to estimate
parameters(delay and angles) of each propagation path, which in turn can be
exploited for positioning and mapping. When paths exhibit significant spread in
either angle or delay, these methods breakdown or lead to significant biases.
We present a novel tensor-based method for channel estimation that allows
estimation of mmWave channel parameters in a non-parametric form. The method is
able to accurately estimate the channel, even in the absence of a specular
component. This in turn enables positioning and mapping using only diffuse
multipath. Simulation results are provided to demonstrate the efficacy of the
proposed approach
Channel Dynamics and SNR Tracking in Millimeter Wave Cellular Systems
The millimeter wave (mmWave) frequencies are likely to play a significant
role in fifth-generation (5G) cellular systems. A key challenge in developing
systems in these bands is the potential for rapid channel dynamics: since
mmWave signals are blocked by many materials, small changes in the position or
orientation of the handset relative to objects in the environment can cause
large swings in the channel quality. This paper addresses the issue of tracking
the signal to noise ratio (SNR), which is an essential procedure for rate
prediction, handover and radio link failure detection. A simple method for
estimating the SNR from periodic synchronization signals is considered. The
method is then evaluated using real experiments in common blockage scenarios
combined with outdoor statistical models
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
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