5,510 research outputs found
Pilot Decontamination in CMT-based Massive MIMO Networks
Pilot contamination problem in massive MIMO networks operating in
time-division duplex (TDD) mode can limit their expected capacity to a great
extent. This paper addresses this problem in cosine modulated multitone (CMT)
based massive MIMO networks; taking advantage of their so-called blind
equalization property. We extend and apply the blind equalization technique
from single antenna case to multi-cellular massive MIMO systems and show that
it can remove the channel estimation errors (due to pilot contamination effect)
without any need for cooperation between different cells or transmission of
additional training information. Our numerical results advocate the efficacy of
the proposed blind technique in improving the channel estimation accuracy and
removal of the residual channel estimation errors caused by the users of the
other cells.Comment: Accepted in ISWCS 201
Group-blind detection with very large antenna arrays in the presence of pilot contamination
Massive MIMO is, in general, severely affected by pilot contamination. As
opposed to traditional detectors, we propose a group-blind detector that takes
into account the presence of pilot contamination. While sticking to the
traditional structure of the training phase, where orthogonal pilot sequences
are reused, we use the excess antennas at each base station to partially remove
interference during the uplink data transmission phase. We analytically derive
the asymptotic SINR achievable with group-blind detection, and confirm our
findings by simulations. We show, in particular, that in an
interference-limited scenario with one dominant interfering cell, the SINR can
be doubled compared to non-group-blind detection.Comment: 5 pages, 4 figure
Pilot Decontamination Through Pilot Sequence Hopping in Massive MIMO Systems
This work concerns wireless cellular networks applying massive multiple-input
multiple-output (MIMO) technology. In such a system, the base station in a
given cell is equipped with a very large number (hundreds or even thousands) of
antennas and serves multiple users. Estimation of the channel from the base
station to each user is performed at the base station using an uplink pilot
sequence. Such a channel estimation procedure suffers from pilot contamination.
Orthogonal pilot sequences are used in a given cell but, due to the shortage of
orthogonal sequences, the same pilot sequences must be reused in neighboring
cells, causing pilot contamination. The solution presented in this paper
suppresses pilot contamination, without the need for coordination among cells.
Pilot sequence hopping is performed at each transmission slot, which provides a
randomization of the pilot contamination. Using a modified Kalman filter, it is
shown that such randomized contamination can be significantly suppressed.
Comparisons with conventional estimation methods show that the mean squared
error can be lowered as much as an order of magnitude at low mobility
Robust Pilot Decontamination Based on Joint Angle and Power Domain Discrimination
We address the problem of noise and interference corrupted channel estimation
in massive MIMO systems. Interference, which originates from pilot reuse (or
contamination), can in principle be discriminated on the basis of the
distributions of path angles and amplitudes. In this paper we propose novel
robust channel estimation algorithms exploiting path diversity in both angle
and power domains, relying on a suitable combination of the spatial filtering
and amplitude based projection. The proposed approaches are able to cope with a
wide range of system and topology scenarios, including those where, unlike in
previous works, interference channel may overlap with desired channels in terms
of multipath angles of arrival or exceed them in terms of received power. In
particular we establish analytically the conditions under which the proposed
channel estimator is fully decontaminated. Simulation results confirm the
overall system gains when using the new methods.Comment: 14 pages, 5 figures, accepted for publication in IEEE Transactions on
Signal Processin
Downlink Performance of Superimposed Pilots in Massive MIMO systems
In this paper, we investigate the downlink throughput performance of a
massive multiple-input multiple-output (MIMO) system that employs superimposed
pilots for channel estimation. The component of downlink (DL) interference that
results from transmitting data alongside pilots in the uplink (UL) is shown to
decrease at a rate proportional to the square root of the number of antennas at
the BS. The normalized mean-squared error (NMSE) of the channel estimate is
compared with the Bayesian Cram\'{e}r-Rao lower bound that is derived for the
system, and the former is also shown to diminish with increasing number of
antennas at the base station (BS). Furthermore, we show that staggered pilots
are a particular case of superimposed pilots and offer the downlink throughput
of superimposed pilots while retaining the UL spectral and energy efficiency of
regular pilots. We also extend the framework for designing a hybrid system,
consisting of users that transmit either regular or superimposed pilots, to
minimize both the UL and DL interference. The improved NMSE and DL rates of the
channel estimator based on superimposed pilots are demonstrated by means of
simulations.Comment: 28 single-column pages, 6 figures, 1 table, Submitted to IEEE Trans.
Wireless Commun. in Aug 2017. Revised Submission in Feb. 201
Dealing with Interference in Distributed Large-scale MIMO Systems: A Statistical Approach
This paper considers the problem of interference control through the use of
second-order statistics in massive MIMO multi-cell networks. We consider both
the cases of co-located massive arrays and large-scale distributed antenna
settings. We are interested in characterizing the low-rankness of users'
channel covariance matrices, as such a property can be exploited towards
improved channel estimation (so-called pilot decontamination) as well as
interference rejection via spatial filtering. In previous work, it was shown
that massive MIMO channel covariance matrices exhibit a useful finite rank
property that can be modeled via the angular spread of multipath at a MIMO
uniform linear array. This paper extends this result to more general settings
including certain non-uniform arrays, and more surprisingly, to two dimensional
distributed large scale arrays. In particular our model exhibits the dependence
of the signal subspace's richness on the scattering radius around the user
terminal, through a closed form expression. The applications of the
low-rankness covariance property to channel estimation's denoising and
low-complexity interference filtering are highlighted.Comment: 12 pages, 11 figures, to appear in IEEE Journal of Selected Topics in
Signal Processin
Effective responder communication improves efficiency and psychological outcomes in a mass decontamination field experiment: implications for public behaviour in the event of a chemical incident
The risk of incidents involving mass decontamination in response to a chemical, biological, radiological, or nuclear release has increased in recent years, due to technological advances, and the willingness of terrorists to use unconventional weapons. Planning for such incidents has focused on the technical issues involved, rather than on psychosocial concerns. This paper presents a novel experimental study, examining the effect of three different responder communication strategies on public experiences and behaviour during a mass decontamination field experiment. Specifically, the research examined the impact of social identity processes on the relationship between effective responder communication, and relevant outcome variables (e.g. public compliance, public anxiety, and co-operative public behaviour). All participants (N = 111) were asked to visualise that they had been involved in an incident involving mass decontamination, before undergoing the decontamination process, and receiving one of three different communication strategies: 1) Health-focused explanations about decontamination, and sufficient practical information; 2) No health-focused explanations about decontamination, sufficient practical information; 3) No health-focused explanations about decontamination, insufficient practical information. Four types of data were collected: timings of the decontamination process; observational data; and quantitative and qualitative self-report data. The communication strategy which resulted in the most efficient progression of participants through the decontamination process, as well as the fewest observations of non-compliance and confusion, was that which included both health-focused explanations about decontamination and sufficient practical information. Further, this strategy resulted in increased perceptions of responder legitimacy and increased identification with responders, which in turn resulted in higher levels of expected compliance during a real incident, and increased willingness to help other members of the public. This study shows that an understanding of the social identity approach facilitates the development of effective responder communication strategies for incidents involving mass decontamination
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