874 research outputs found
Beamspace Aware Adaptive Channel Estimation for Single-Carrier Time-varying Massive MIMO Channels
In this paper, the problem of sequential beam construction and adaptive
channel estimation based on reduced rank (RR) Kalman filtering for
frequency-selective massive multiple-input multiple-output (MIMO) systems
employing single-carrier (SC) in time division duplex (TDD) mode are
considered. In two-stage beamforming, a new algorithm for statistical
pre-beamformer design is proposed for spatially correlated time-varying
wideband MIMO channels under the assumption that the channel is a stationary
Gauss-Markov random process. The proposed algorithm yields a nearly optimal
pre-beamformer whose beam pattern is designed sequentially with low complexity
by taking the user-grouping into account, and exploiting the properties of
Kalman filtering and associated prediction error covariance matrices. The
resulting design, based on the second order statistical properties of the
channel, generates beamspace on which the RR Kalman estimator can be realized
as accurately as possible. It is observed that the adaptive channel estimation
technique together with the proposed sequential beamspace construction shows
remarkable robustness to the pilot interference. This comes with significant
reduction in both pilot overhead and dimension of the pre-beamformer lowering
both hardware complexity and power consumption.Comment: 7 pages, 3 figures, accepted by IEEE ICC 2017 Wireless Communications
Symposiu
Receiver Algorithm based on Differential Signaling for SIMO Phase Noise Channels with Common and Separate Oscillator Configurations
In this paper, a receiver algorithm consisting of differential transmission
and a two-stage detection for a single-input multiple-output (SIMO) phase-noise
channels is studied. Specifically, the phases of the QAM modulated data symbols
are manipulated before transmission in order to make them more immune to the
random rotational effects of phase noise. At the receiver, a two-stage detector
is implemented, which first detects the amplitude of the transmitted symbols
from a nonlinear combination of the received signal amplitudes. Then in the
second stage, the detector performs phase detection. The studied signaling
method does not require transmission of any known symbols that act as pilots.
Furthermore, no phase noise estimator (or a tracker) is needed at the receiver
to compensate the effect of phase noise. This considerably reduces the
complexity of the receiver structure. Moreover, it is observed that the studied
algorithm can be used for the setups where a common local oscillator or
separate independent oscillators drive the radio-frequency circuitries
connected to each antenna. Due to the differential encoding/decoding of the
phase, weighted averaging can be employed at a multi-antenna receiver, allowing
for phase noise suppression to leverage the large number of antennas. Hence, we
observe that the performance improves by increasing the number of antennas,
especially in the separate oscillator case. Further increasing the number of
receive antennas results in a performance error floor, which is a function of
the quality of the oscillator at the transmitter.Comment: IEEE GLOBECOM 201
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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