60 research outputs found
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
A Coordinated Approach to Channel Estimation in Large-scale Multiple-antenna Systems
This paper addresses the problem of channel estimation in multi-cell
interference-limited cellular networks. We consider systems employing multiple
antennas and are interested in both the finite and large-scale antenna number
regimes (so-called "massive MIMO"). Such systems deal with the multi-cell
interference by way of per-cell beamforming applied at each base station.
Channel estimation in such networks, which is known to be hampered by the pilot
contamination effect, constitute a major bottleneck for overall performance. We
present a novel approach which tackles this problem by enabling a low-rate
coordination between cells during the channel estimation phase itself. The
coordination makes use of the additional second-order statistical information
about the user channels, which are shown to offer a powerful way of
discriminating across interfering users with even strongly correlated pilot
sequences. Importantly, we demonstrate analytically that in the
large-number-of-antennas regime, the pilot contamination effect is made to
vanish completely under certain conditions on the channel covariance. Gains
over the conventional channel estimation framework are confirmed by our
simulations for even small antenna array sizes.Comment: 10 pages, 6 figures, to appear in IEEE Journal on Selected Areas in
Communication
A review of codebooks for CSI feedback in 5G new radio and beyond
Codebooks have been indispensable for wireless communication standard since
the first release of the Long-Term Evolution in 2009. They offer an efficient
way to acquire the channel state information (CSI) for multiple antenna
systems. Nowadays, a codebook is not limited to a set of pre-defined precoders,
it refers to a CSI feedback framework, which is more and more sophisticated. In
this paper, we review the codebooks in 5G New Radio (NR) standards. The
codebook timeline and the evolution trend are shown. Each codebook is
elaborated with its motivation, the corresponding feedback mechanism, and the
format of the precoding matrix indicator. Some insights are given to help grasp
the underlying reasons and intuitions of these codebooks. Finally, we point out
some unresolved challenges of the codebooks for future evolution of the
standards. In general, this paper provides a comprehensive review of the
codebooks in 5G NR and aims to help researchers understand the CSI feedback
schemes from a standard and industrial perspective.Comment: 11pages, 7 figures, 1 table, magzine revie
Superdirectivity-enhanced wireless communications: A multi-user perspective
Superdirective array may achieve an array gain proportional to the square of
the number of antennas . In the early studies of superdirectivity, little
research has been done from wireless communication point of view. To leverage
superdirectivity for enhancing the spectral efficiency, this paper investigates
multi-user communication systems with superdirective arrays. We first propose a
field-coupling-aware (FCA) multi-user channel estimation method, which takes
into account the antenna coupling effects. Aiming to maximize the power gain of
the target user, we propose multi-user multipath superdirective precoding (SP)
as an extension of our prior work on coupling-based superdirective beamforming.
Furthermore, to reduce the inter-user interference, we propose
interference-nulling superdirective precoding (INSP) as the optimal solution to
maximize user power gains while eliminating interference. Then, by taking the
ohmic loss into consideration, we further propose a regularized
interference-nulling superdirective precoding (RINSP) method. Finally, we
discuss the well-known narrow directivity bandwidth issue, and find that it is
not a fundamental problem of superdirective arrays in multi-carrier
communication systems. Simulation results show our proposed methods outperform
the state-of-the-art methods significantly. Interestingly, in the multi-user
scenario, an 18-antenna superdirective array can achieve up to a 9-fold
increase of spectral efficiency compared to traditional multiple-input
multiple-output (MIMO), while simultaneously reducing the array aperture by
half.Comment: 11 pages, 8 figure
Eigenvector prediction-based precoding for massive MIMO with mobility
Eigenvector decomposition (EVD) is an inevitable operation to obtain the
precoders in practical massive multiple-input multiple-output (MIMO) systems.
Due to the large antenna size and at finite computation resources at the base
station (BS), the overwhelming computation complexity of EVD is one of the key
limiting factors of the system performance. To address this problem, we propose
an eigenvector prediction (EGVP) method by interpolating the precoding matrix
with predicted eigenvectors. The basic idea is to exploit a few historical
precoders to interpolate the rest of them without EVD of the channel state
information (CSI). We transform the nonlinear EVD into a linear prediction
problem and prove that the prediction of the eigenvectors can be achieved with
a complex exponential model. Furthermore, a channel prediction method called
fast matrix pencil prediction (FMPP) is proposed to cope with the CSI delay
when applying the EGVP method in mobility environments. The asymptotic analysis
demonstrates how many samples are needed to achieve asymptotically error-free
eigenvector predictions and channel predictions. Finally, the simulation
results demonstrate the spectral efficiency improvement of our scheme over the
benchmarks and the robustness to different mobility scenarios.Comment: 13pages, 7 figures, 1 table, journa
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
A Superdirective Beamforming Approach with Impedance Coupling and Field Coupling for Compact Antenna Arrays
In most multiple-input multiple-output (MIMO) communication systems, the
antenna spacing is generally no less than half a wavelength. It helps to reduce
the mutual coupling and therefore facilitate the system design. The maximum
array gain equals the number of antennas in this settings. However, when the
antenna spacing is made very small, the array gain of a compact array can be
proportional to the square of the number of antennas - a value much larger than
the traditional array. To achieve this so-called ``superdirectivity" however,
the calculation of the excitation coefficients (beamforming vector) is known to
be a challenging problem. In this paper, we address this problem with a novel
double coupling-based superdirective beamforming method. In particular, we
categorize the antenna coupling effects to impedance coupling and field
coupling. By characterizing these two coupling in model, we derive the
beamforming vector for superdirective arrays. In order to obtain the field
coupling matrix, we propose a spherical wave expansion approach, which is
effective in both simulations and realistic scenarios. Moreover, a prototype of
the independently controlled superdirective antenna array is developed.
Full-wave electromagnetic simulations and real-world experiments validate the
effectiveness of our proposed approaches, and superdirectivity is achieved in
reality by a compact array with 4 and 5 dipole antennas.Comment: arXiv admin note: text overlap with arXiv:2204.1154
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