1,627 research outputs found
Sectoring in Multi-cell Massive MIMO Systems
In this paper, the downlink of a typical massive MIMO system is studied when
each base station is composed of three antenna arrays with directional antenna
elements serving 120 degrees of the two-dimensional space. A lower bound for
the achievable rate is provided. Furthermore, a power optimization problem is
formulated and as a result, centralized and decentralized power allocation
schemes are proposed. The simulation results reveal that using directional
antennas at base stations along with sectoring can lead to a notable increase
in the achievable rates by increasing the received signal power and decreasing
'pilot contamination' interference in multicell massive MIMO systems. Moreover,
it is shown that using optimized power allocation can increase 0.95-likely rate
in the system significantly
A Generalized Framework on Beamformer Design and CSI Acquisition for Single-Carrier Massive MIMO Systems in Millimeter Wave Channels
In this paper, we establish a general framework on the reduced dimensional
channel state information (CSI) estimation and pre-beamformer design for
frequency-selective massive multiple-input multiple-output MIMO systems
employing single-carrier (SC) modulation in time division duplex (TDD) mode by
exploiting the joint angle-delay domain channel sparsity in millimeter (mm)
wave frequencies. First, based on a generic subspace projection taking the
joint angle-delay power profile and user-grouping into account, the reduced
rank minimum mean square error (RR-MMSE) instantaneous CSI estimator is derived
for spatially correlated wideband MIMO channels. Second, the statistical
pre-beamformer design is considered for frequency-selective SC massive MIMO
channels. We examine the dimension reduction problem and subspace (beamspace)
construction on which the RR-MMSE estimation can be realized as accurately as
possible. Finally, a spatio-temporal domain correlator type reduced rank
channel estimator, as an approximation of the RR-MMSE estimate, is obtained by
carrying out least square (LS) estimation in a proper reduced dimensional
beamspace. It is observed that the proposed techniques show remarkable
robustness to the pilot interference (or contamination) with a significant
reduction in pilot overhead
Active Attack on User Load Achieving Pilot Design in Massive MIMO Networks
In this paper, we propose an active attacking strategy on a massive
multiple-input multiple-output (MIMO) network, where the pilot sequences are
obtained using the user load-achieving pilot sequence design. The user
load-achieving design ensures that the signal-to-interference-plus-noise ratio
(SINR) requirements of all the users in the massive MIMO networks are
guaranteed even in the presence of pilot contamination. However, this design
has some vulnerabilities, such as one known pilot sequence and the correlation
among the pilot sequences, that may be exploited by active attackers. In this
work, we first identify the potential vulnerabilities in the user
load-achieving pilot sequence design and then, accordingly, develop an active
attacking strategy on the network. In the proposed attacking strategy, the
active attackers transmit known pilot sequences in the uplink training and
artificial noise in the downlink data transmission. Our examination
demonstrates that the per-cell user load region is significantly reduced by the
proposed attacking strategy. As a result of the reduced per-cell user load
region, the SINR requirements of all the users are no longer guaranteed in the
presence of the active attackers. Specifically, for the worst affected users
the SINR requirements may not be ensured even with infinite antennas at the
base station.Comment: Accepted in IEEE GlobeCOM 201
Soft Pilot Reuse and Multi-Cell Block Diagonalization Precoding for Massive MIMO Systems
The users at cell edge of a massive multiple-input multiple-output (MIMO)
system suffer from severe pilot contamination, which leads to poor quality of
service (QoS). In order to enhance the QoS for these edge users, soft pilot
reuse (SPR) combined with multi-cell block diagonalization (MBD) precoding are
proposed. Specifically, the users are divided into two groups according to
their large-scale fading coefficients, referred to as the center users, who
only suffer from modest pilot contamination and the edge users, who suffer from
severe pilot contamination. Based on this distinction, the SPR scheme is
proposed for improving the QoS for the edge users, whereby a cell-center pilot
group is reused for all cell-center users in all cells, while a cell-edge pilot
group is applied for the edge users in the adjacent cells. By extending the
classical block diagonalization precoding to a multi-cell scenario, the MBD
precoding scheme projects the downlink transmit signal onto the null space of
the subspace spanned by the inter-cell channels of the edge users in adjacent
cells. Thus, the inter-cell interference contaminating the edge users' signals
in the adjacent cells can be efficiently mitigated and hence the QoS of these
edge users can be further enhanced. Our theoretical analysis and simulation
results demonstrate that both the uplink and downlink rates of the edge users
are significantly improved, albeit at the cost of the slightly decreased rate
of center users.Comment: 13 pages, 12 figures, accepted for publication in IEEE Transactions
on Vehicular Technology, 201
Achieving "Massive MIMO" Spectral Efficiency with a Not-so-Large Number of Antennas
The main focus and contribution of this paper is a novel network-MIMO TDD
architecture that achieves spectral efficiencies comparable with "Massive
MIMO", with one order of magnitude fewer antennas per active user per cell. The
proposed architecture is based on a family of network-MIMO schemes defined by
small clusters of cooperating base stations, zero-forcing multiuser MIMO
precoding with suitable inter-cluster interference constraints, uplink pilot
signals reuse across cells, and frequency reuse. The key idea consists of
partitioning the users population into geographically determined "bins", such
that all users in the same bin are statistically equivalent, and use the
optimal network-MIMO architecture in the family for each bin. A scheduler takes
care of serving the different bins on the time-frequency slots, in order to
maximize a desired network utility function that captures some desired notion
of fairness. This results in a mixed-mode network-MIMO architecture, where
different schemes, each of which is optimized for the served user bin, are
multiplexed in time-frequency. In order to carry out the performance analysis
and the optimization of the proposed architecture in a clean and
computationally efficient way, we consider the large-system regime where the
number of users, the number of antennas, and the channel coherence block length
go to infinity with fixed ratios. The performance predicted by the large-system
asymptotic analysis matches very well the finite-dimensional simulations.
Overall, the system spectral efficiency obtained by the proposed architecture
is similar to that achieved by "Massive MIMO", with a 10-fold reduction in the
number of antennas at the base stations (roughly, from 500 to 50 antennas).Comment: Full version with appendice (proofs of theorems). A shortened version
without appendice was submitted to IEEE Trans. on Wireless Commun. Appendix B
was revised after submissio
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