1,652 research outputs found
Robust Phase-Based Positioning Using Massive MIMO with Limited Bandwidth
This paper presents a robust phase-based positioningframework using a massive multiple-input multiple-output(MIMO) system. The phase-based distance estimates of MPCstogether with other parameters are tracked with an ExtendedKalman Filter (EKF), the state dimension of which varies withthe birth-death processes of paths. The iterative maximumlikelihoodestimation algorithm (RIMAX) and the modeling ofdense multipath component (DMC) in the framework furtherenhance the quality of parameter tracking by providing anaccurate initial state and the underlying noise covariance.The tracked MPCs are fed into a time-of-arrival (TOA) selfcalibrationpositioning algorithm for simultaneous trajectoryand environment estimation. Throughout the positioning process,no prior knowledge of the surrounding environment andbase station position is needed. The performance is evaluatedwith the measurement of a 2D complex movement, which wasperformed in a sports hall with an antenna array with 128 portsas base station using a standard cellular bandwidth of 40 MHz.The positioning result shows that the mean deviation of theestimated user equipment trajectory from the ground truth is13 cm. In summary, the proposed framework is a promisinghigh-resolution radio-based positioning solution for current andnext generation cellular systems
Massive MIMO-based Localization and Mapping Exploiting Phase Information of Multipath Components
In this paper, we present a robust multipath-based localization and mapping
framework that exploits the phases of specular multipath components (MPCs)
using a massive multiple-input multiple-output (MIMO) array at the base
station. Utilizing the phase information related to the propagation distances
of the MPCs enables the possibility of localization with extraordinary accuracy
even with limited bandwidth. The specular MPC parameters along with the
parameters of the noise and the dense multipath component (DMC) are tracked
using an extended Kalman filter (EKF), which enables to preserve the
distance-related phase changes of the MPC complex amplitudes. The DMC comprises
all non-resolvable MPCs, which occur due to finite measurement aperture. The
estimation of the DMC parameters enhances the estimation quality of the
specular MPCs and therefore also the quality of localization and mapping. The
estimated MPC propagation distances are subsequently used as input to a
distance-based localization and mapping algorithm. This algorithm does not need
prior knowledge about the surrounding environment and base station position.
The performance is demonstrated with real radio-channel measurements using an
antenna array with 128 ports at the base station side and a standard cellular
signal bandwidth of 40 MHz. The results show that high accuracy localization is
possible even with such a low bandwidth.Comment: 14 pages (two columns), 13 figures. This work has been submitted to
the IEEE Transaction on Wireless Communications for possible publication.
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Massive MIMO is a Reality -- What is Next? Five Promising Research Directions for Antenna Arrays
Massive MIMO (multiple-input multiple-output) is no longer a "wild" or
"promising" concept for future cellular networks - in 2018 it became a reality.
Base stations (BSs) with 64 fully digital transceiver chains were commercially
deployed in several countries, the key ingredients of Massive MIMO have made it
into the 5G standard, the signal processing methods required to achieve
unprecedented spectral efficiency have been developed, and the limitation due
to pilot contamination has been resolved. Even the development of fully digital
Massive MIMO arrays for mmWave frequencies - once viewed prohibitively
complicated and costly - is well underway. In a few years, Massive MIMO with
fully digital transceivers will be a mainstream feature at both sub-6 GHz and
mmWave frequencies. In this paper, we explain how the first chapter of the
Massive MIMO research saga has come to an end, while the story has just begun.
The coming wide-scale deployment of BSs with massive antenna arrays opens the
door to a brand new world where spatial processing capabilities are
omnipresent. In addition to mobile broadband services, the antennas can be used
for other communication applications, such as low-power machine-type or
ultra-reliable communications, as well as non-communication applications such
as radar, sensing and positioning. We outline five new Massive MIMO related
research directions: Extremely large aperture arrays, Holographic Massive MIMO,
Six-dimensional positioning, Large-scale MIMO radar, and Intelligent Massive
MIMO.Comment: 20 pages, 9 figures, submitted to Digital Signal Processin
Indoor wireless communications and applications
Chapter 3 addresses challenges in radio link and system design in indoor scenarios. Given the fact that most human activities take place in indoor environments, the need for supporting ubiquitous indoor data connectivity and location/tracking service becomes even more important than in the previous decades. Specific technical challenges addressed in this section are(i), modelling complex indoor radio channels for effective antenna deployment, (ii), potential of millimeter-wave (mm-wave) radios for supporting higher data rates, and (iii), feasible indoor localisation and tracking techniques, which are summarised in three dedicated sections of this chapter
Massive MIMO for Next Generation Wireless Systems
Multi-user Multiple-Input Multiple-Output (MIMO) offers big advantages over
conventional point-to-point MIMO: it works with cheap single-antenna terminals,
a rich scattering environment is not required, and resource allocation is
simplified because every active terminal utilizes all of the time-frequency
bins. However, multi-user MIMO, as originally envisioned with roughly equal
numbers of service-antennas and terminals and frequency division duplex
operation, is not a scalable technology. Massive MIMO (also known as
"Large-Scale Antenna Systems", "Very Large MIMO", "Hyper MIMO", "Full-Dimension
MIMO" & "ARGOS") makes a clean break with current practice through the use of a
large excess of service-antennas over active terminals and time division duplex
operation. Extra antennas help by focusing energy into ever-smaller regions of
space to bring huge improvements in throughput and radiated energy efficiency.
Other benefits of massive MIMO include the extensive use of inexpensive
low-power components, reduced latency, simplification of the media access
control (MAC) layer, and robustness to intentional jamming. The anticipated
throughput depend on the propagation environment providing asymptotically
orthogonal channels to the terminals, but so far experiments have not disclosed
any limitations in this regard. While massive MIMO renders many traditional
research problems irrelevant, it uncovers entirely new problems that urgently
need attention: the challenge of making many low-cost low-precision components
that work effectively together, acquisition and synchronization for
newly-joined terminals, the exploitation of extra degrees of freedom provided
by the excess of service-antennas, reducing internal power consumption to
achieve total energy efficiency reductions, and finding new deployment
scenarios. This paper presents an overview of the massive MIMO concept and
contemporary research.Comment: Final manuscript, to appear in IEEE Communications Magazin
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
A Survey of Air-to-Ground Propagation Channel Modeling for Unmanned Aerial Vehicles
In recent years, there has been a dramatic increase in the use of unmanned
aerial vehicles (UAVs), particularly for small UAVs, due to their affordable
prices, ease of availability, and ease of operability. Existing and future
applications of UAVs include remote surveillance and monitoring, relief
operations, package delivery, and communication backhaul infrastructure.
Additionally, UAVs are envisioned as an important component of 5G wireless
technology and beyond. The unique application scenarios for UAVs necessitate
accurate air-to-ground (AG) propagation channel models for designing and
evaluating UAV communication links for control/non-payload as well as payload
data transmissions. These AG propagation models have not been investigated in
detail when compared to terrestrial propagation models. In this paper, a
comprehensive survey is provided on available AG channel measurement campaigns,
large and small scale fading channel models, their limitations, and future
research directions for UAV communication scenarios
Ubiquitous Indoor Fine-Grained Positioning and Tracking: A Channel Response Perspective
The future of location-aided applications is shaped by the ubiquity of
Internet-of-Things devices. As an increasing amount of commercial off-the-shelf
radio devices support channel response collection, it is possible to achieve
fine-grained position estimation at a relatively low cost. In this paper, we
focus on the channel response-based positioning and tracking for various
applications. We first give an overview of the state of the art (SOTA) of
channel response-enabled localization, which is further classified into two
categories, i.e., device-based and contact-free schemes. A taxonomy for these
complementary approaches is provided concerning the involved techniques. Then,
we present a micro-benchmark of channel response-based direct positioning and
tracking for both device-based and contact-free schemes. Finally, some
practical issues for real-world applications and future research opportunities
are pointed out.Comment: 13th International Conference on Indoor Positioning and Indoor
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