120 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
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
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
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
Uncoordinated pilot decontamination in massive MIMO systems
Abstract This work concerns wireless cellular networks applying time division duplexing (TDD) massive multiple-input multiple-output (MIMO) technology. Such systems suffer from pilot contamination during channel estimation, due to the shortage of orthogonal pilot sequences. This paper presents a solution based on pilot sequence hopping, which provides a randomization of the pilot contamination. It is shown that such randomized contamination can be significantly suppressed through appropriate filtering. The resulting channel estimation scheme requires no inter-cell coordination, which is a strong advantage for practical implementations. Comparisons with conventional estimation methods show that the MSE can be lowered as much as an order of magnitude at low mobility. Achievable uplink and downlink rates are increased by 42 and 46%, respectively, in a system with 128 antennas at the base station
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