247 research outputs found
Performance of location and orientation estimation in 5G mmWave systems: Uplink vs downlink
The fifth generation of mobile communications (5G) is expected to exploit the concept of location-aware communication systems. Therefore, there is a need to understand the localization limits in these networks, particularly, using millimeter-wave technology (mmWave). Contributing to this understanding, we consider single-anchor localization limits in terms of 3D position and orientation error bounds for mmWave multipath channels, for both the uplink and downlink. It is found that uplink localization is sensitive to the orientation angle of the user equipment (UE), whereas downlink is not. Moreover, in the considered outdoor scenarios, reflected and scattered paths generally improve localization. Finally, using detailed numerical simulations, we show that mmWave systems are in theory capable of localizing a UE with sub-meter position error, and sub-degree orientation error
Error Bounds for Uplink and Downlink 3D Localization in 5G mmWave Systems
Location-aware communication systems are expected to play a pivotal part in
the next generation of mobile communication networks. Therefore, there is a
need to understand the localization limits in these networks, particularly,
using millimeter-wave technology (mmWave). Towards that, we address the uplink
and downlink localization limits in terms of 3D position and orientation error
bounds for mmWave multipath channels. We also carry out a detailed analysis of
the dependence of the bounds of different systems parameters. Our key findings
indicate that the uplink and downlink behave differently in two distinct ways.
First of all, the error bounds have different scaling factors with respect to
the number of antennas in the uplink and downlink. Secondly, uplink
localization is sensitive to the orientation angle of the user equipment (UE),
whereas downlink is not. Moreover, in the considered outdoor scenarios, the
non-line-of-sight paths generally improve localization when a line-of-sight
path exists. Finally, our numerical results show that mmWave systems are
capable of localizing a UE with sub-meter position error, and sub-degree
orientation error.Comment: This manuscripts is updated following two rounds of reviews at IEEE
Transactions on Wireless Communications. More discussion is included in
different parts of the paper. Results are unchanged, and are still vali
Towards the Next Generation of Location-Aware Communications
This thesis is motivated by the expected implementation of the
next generation mobile networks (5G) from 2020, which is being
designed with a radical paradigm shift towards millimeter-wave
technology (mmWave). Operating in 30--300 GHz frequency band
(1--10 mm wavelengths), massive antenna arrays that provide a
high angular resolution, while being packed on a small area will
be used. Moreover, since the abundant mmWave spectrum is barely
occupied, large bandwidth allocation is possible and will enable
low-error time estimation. With this high spatiotemporal
resolution, mmWave technology readily lends itself to extremely
accurate localization that can be harnessed in the network design
and optimization, as well as utilized in many modern
applications. Localization in 5G is still in early stages, and
very little is known about its performance and feasibility.
In this thesis, we contribute to the understanding of 5G mmWave
localization by focusing on challenges pertaining to this
emerging technology. Towards that, we start by considering a
conventional cellular system and propose a positioning method
under outdoor LOS/NLOS conditions that, although approaches the
Cram\'er-Rao lower bound (CRLB), provides accuracy in the order
of meters. This shows that conventional systems have limited
range of location-aware applications. Next, we focus on mmWave
localization in three stages. Firstly, we tackle the initial
access (IA) problem, whereby user equipment (UE) attempts to
establish a link with a base station (BS). The challenge in this
problem stems from the high directivity of mmWave. We investigate
two beamforming schemes: directional and random. Subsequently, we
address 3D localization beyond IA phase. Devices nowadays have
higher computational capabilities and may perform localization in
the downlink. However, beamforming on the UE side is sensitive to
the device orientation. Thus, we study localization in both the
uplink and downlink under multipath propagation and derive the
position (PEB) and orientation error bounds (OEB). We also
investigate the impact of the number of antennas and the number
of beams on these bounds. Finally, the above components assume
that the system is synchronized. However, synchronization in
communication systems is not usually tight enough for
localization. Therefore, we study two-way localization as a means
to alleviate the synchronization requirement and investigate two
protocols: distributed (DLP) and centralized (CLP).
Our results show that random-phase beamforming is more
appropriate IA approach in the studied scenarios. We also observe
that the uplink and downlink are not equivalent, in that the
error bounds scale differently with the number of antennas, and
that uplink localization is sensitive to the UE orientation,
while downlink is not. Furthermore, we find that NLOS paths
generally boost localization. The investigation of the two-way
protocols shows that CLP outperforms DLP by a significant margin.
We also observe that mmWave localization is mainly limited by
angular rather than temporal estimation.
In conclusion, we show that mmWave systems are capable of
localizing a UE with sub-meter position error, and sub-degree
orientation error, which asserts that mmWave will play a central
role in communication network optimization and unlock
opportunities that were not available in the previous generation
Single-anchor two-way localization bounds for 5G mmWave systems
Recently, millimeter-wave (mmWave) 5G localization has been shown to be to provide centimeter-level accuracy, lending itself to many location-aware applications, e.g., connected autonomous vehicles (CAVs). One assumption usually made in the investigation of localization methods is that the user equipment (UE), i.e., a CAV, and the base station (BS) are time synchronized. In this paper, we remove this assumption and investigate two two-way localization protocols: (i) a round-trip localization protocol (RLP), whereby the BS and UE exchange signals in two rounds of transmission and then localization is achieved using the signal received in the second round; (ii) a collaborative localization protocol (CLP), whereby localization is achieved using the signals received in the two rounds. We derive the position and orientation error bounds applying beamforming at both ends and compare them to the traditional one-way localization. Our results show that mmWave localization is mainly limited by the angular rather than the temporal estimation and that CLP significantly outperforms RLP. Our simulations also show that it is more beneficial to have more antennas at the BS than at the UE
Single-Anchor Two-Way Localization Bounds for 5G mmWave Systems
Recently, millimeter-wave (mmWave) 5G localization has been shown to be to
provide centimeter-level accuracy, lending itself to many location-aware
applications, e.g., connected autonomous vehicles (CAVs). One assumption
usually made in the investigation of localization methods is that the user
equipment (UE), i.e., a CAV, and the base station (BS) are {time} synchronized.
In this paper, we remove this assumption and investigate two two-way
localization protocols: (i) a round-trip localization protocol (RLP), whereby
the BS and UE exchange signals in two rounds of transmission and then
localization is achieved using the signal received in the second round; (ii) a
collaborative localization protocol (CLP), whereby localization is achieved
using the signals received in the two rounds. We derive the position and
orientation error bounds applying beamforming at both ends and compare them to
the traditional one-way localization. Our results show that mmWave localization
is mainly limited by the angular rather than the temporal estimation and that
CLP significantly outperforms RLP. Our simulations also show that it is more
beneficial to have more antennas at the BS than at the UE.Comment: This version is accepted for publication as a paper in the IEEE
Transactions on Vehicular Technolog
Low-Complexity Accurate Mmwave Positioning for Single-Antenna Users Based on Angle-of-Departure and Adaptive Beamforming
The problem of position estimation of a mobile user equipped with a single antenna receiver using downlink transmissions is addressed. The advantages of this setup compared to the classical MIMO and uplink scenarios are analyzed in terms of achievable theoretical performance (Cram\ue9r-Rao bounds) considering a realistic power budget. Based on this analysis, a low-complexity two-step algorithm with improved localization performance is proposed, which first performs a (coarse) angle of departure estimation and then precodes the down-link signal to introduce beamforming towards the user direction. Results demonstrate that position estimation in downlink can be potentially much more accurate than in uplink, even in presence of multiple users in the system
Localization Error Bounds for 5G mmWave Systems under I/Q Imbalance
Location awareness is expected to play a significant role in 5G millimeter-wave (mmWave) communication systems. One of the basic elements of these systems is quadrature amplitude modulation (QAM), which has in-phase and quadrature (I/Q) modulators. It is not uncommon for transceiver hardware to exhibit an imbalance in the I/Q components, causing degradation in data rate and signal quality. Under an amplitude and phase imbalance model at both the transmitter and receiver, 2D positioning performance in 5G mmWave systems is considered. Towards that, we derive the position and orientation error bounds and study the effects of the I/Q imbalance parameters on the derived bounds. The numerical results reveal that I/Q imbalance impacts the performance similarly, whether it occurs at the transmitter or the receiver, and can cause a degradation up to 12% in position and orientation estimation accuracy
3D Orientation Estimation with Multiple 5G mmWave Base Stations
We consider the problem of estimating the 3D orientation of a user, using the
downlink mmWave signals received from multiple base stations. We show that the
received signals from several base stations, having known positions, can be
used to estimate the unknown orientation of the user. We formulate the
estimation problem as a maximum likelihood estimation problem in the the
manifold of rotation matrices. In order to provide an initial estimate to solve
the non-linear non-convex optimization problem, we resort to a least squares
estimation problem that exploits the underlying geometry. Our numerical results
show that the problem of orientation estimation can be solved when the signals
from at least two base stations are received. We also provide the orientation
lower error bound, showing a narrow gap between the performance of the proposed
estimators and the bound
5G multi-BS positioning with a single-antenna receiver
Cellular localization generally relies on timedifference-of-arrival (TDOA) measurements. In this paper, we investigate a novel scenario where the mobile user estimates its own position by jointly exploiting TDOA and angle of departure (AOD) measurements, which are estimated from downlink transmissions in a millimeter-wave (mmWave) multiple-input singleoutput (MISO) setup. We first perform a Fisher information analysis to derive the lower bounds on the estimation accuracy, and then propose a novel localization algorithm, which is able to provide improved performance also with few transmit antennas and limited bandwidth
Millimeter-Wave Downlink Positioning with a Single-Antenna Receiver
The paper addresses the problem of determining the unknown position of a mobile station for a mmWave MISO system. This setup is motivated by the fact that massive arrays will be initially implemented only on 5G base stations, likely leaving mobile stations with one antenna. The maximum likelihood solution to this problem is devised based on the time of flight and angle of departure of received downlink signals. While positioning in the uplink would rely on angle of arrival, it presents scalability limitations that are avoided in the downlink. To circumvent the multidimensional optimization of the optimal joint estimator, we propose two novel approaches amenable to practical implementation thanks to their reduced complexity. A thorough analysis, which includes the derivation of relevant Cram\ue9r-Rao lower bounds, shows that it is possible to achieve quasi-optimal performance even in presence of few transmissions, low SNRs, and multipath propagation effects
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