805 research outputs found
A Complexity-Efficient High Resolution Propagation Parameter Estimation Algorithm for Ultra-Wideband Large-Scale Uniform Circular Array
Millimeter wave (mm-wave) communication with large-scale antenna array
configuration is seen as the key enabler of the next generation communication
systems. Accurate knowledge of the mm-wave propagation channels is fundamental
and essential. In this contribution, a novel complexity-efficient high
resolution parameter estimation (HRPE) algorithm is proposed for the mm-wave
channel with large-scale uniform circular array (UCA) applied. The proposed
algorithm is able to obtain the high-resolution estimation results of the
spherical channel propagation parameters. The prior channel information in the
delay domain, i.e., the delay trajectories of individual propagation paths
observed across the array elements, is exploited, by combining the
high-resolution estimation principle and the phase mode excitation technique.
Fast initializations, effective interference cancellations and reduced
searching spaces achieved by the proposed schemes significantly decrease the
algorithm complexity. Furthermore, the channel spatial non-stationarity in path
gain across the array elements is considered for the first time in the
literature for propagation parameter estimation, which is beneficial to obtain
more realistic results as well as to decrease the complexity. A mm-wave
measurement campaign at the frequency band of 28-30 GHz using a large-scale UCA
is exploited to demonstrate and validate the proposed HRPE algorithm.Comment: Single column, 28 pages. In review process with IEEE Transactions on
Communication
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
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-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.
Copyright may be transferred without notice, after which this version may no
longer be accessibl
A Novel SAGE Algorithm for Estimating Parameters of Wideband Spatial Nonstationary Wireless Channels with Antenna Polarization
In this article, a novel space-alternating generalized expectation-maximization (SAGE) algorithm is proposed for parameter estimations of wideband spatial nonstationary wireless channels with antenna polarization (SAGE-WSNSAP). Compared with the traditional SAGE algorithm, the proposed SAGE-WSNSAP algorithm adds spatial nonstationarity by introducing birth-death coefficients at both transmitter (Tx) and receiver (Rx) sides into the parametric model. To reduce the complexity of the SAGE-WSNSAP algorithm, a coarse-to-fine search method is adopted in the initialization step. In addition, multiple-input multiple-output (MIMO) channel measurements are conducted to validate the proposed algorithm. The measurement results of the angle-delay power spectral density (PSD) and average delay PSD are compared with those estimated by the far-field SAGE algorithm, the near-field SAGE algorithm, and the proposed algorithm. It is found that the estimation results using the proposed SAGE-WSNSAP algorithm show higher similarity to measurement results than using the other two SAGE algorithms. In comparison to the far-field and near-field SAGE algorithms, the SAGE-WSNSAP algorithm can extract more effective multipath components (MPCs) and improve the power extraction ratios.</p
A Framework for Developing and Evaluating Algorithms for Estimating Multipath Propagation Parameters from Channel Sounder Measurements
A framework is proposed for developing and evaluating algorithms for
extracting multipath propagation components (MPCs) from measurements collected
by channel sounders at millimeter-wave frequencies. Sounders equipped with an
omnidirectional transmitter and a receiver with a uniform planar array (UPA)
are considered. An accurate mathematical model is developed for the spatial
frequency response of the sounder that incorporates the non-ideal cross-polar
beampatterns for the UPA elements. Due to the limited Field-of-View (FoV) of
each element, the model is extended to accommodate multi-FoV measurements in
distinct azimuth directions. A beamspace representation of the spatial
frequency response is leveraged to develop three progressively complex
algorithms aimed at solving the singlesnapshot maximum likelihood estimation
problem: greedy matching pursuit (CLEAN), space-alternative generalized
expectationmaximization (SAGE), and RiMAX. The first two are based on purely
specular MPCs whereas RiMAX also accommodates diffuse MPCs. Two approaches for
performance evaluation are proposed, one with knowledge of ground truth
parameters, and one based on reconstruction mean-squared error. The three
algorithms are compared through a demanding channel model with hundreds of MPCs
and through real measurements. The results demonstrate that CLEAN gives quite
reasonable estimates which are improved by SAGE and RiMAX. Lessons learned and
directions for future research are discussed.Comment: 17 page
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