431 research outputs found
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
Downlink Training in Cell-Free Massive MIMO: A Blessing in Disguise
Cell-free Massive MIMO (multiple-input multiple-output) refers to a
distributed Massive MIMO system where all the access points (APs) cooperate to
coherently serve all the user equipments (UEs), suppress inter-cell
interference and mitigate the multiuser interference. Recent works demonstrated
that, unlike co-located Massive MIMO, the \textit{channel hardening} is, in
general, less pronounced in cell-free Massive MIMO, thus there is much to
benefit from estimating the downlink channel. In this study, we investigate the
gain introduced by the downlink beamforming training, extending the previously
proposed analysis to non-orthogonal uplink and downlink pilots. Assuming
single-antenna APs, conjugate beamforming and independent Rayleigh fading
channel, we derive a closed-form expression for the per-user achievable
downlink rate that addresses channel estimation errors and pilot contamination
both at the AP and UE side. The performance evaluation includes max-min
fairness power control, greedy pilot assignment methods, and a comparison
between achievable rates obtained from different capacity-bounding techniques.
Numerical results show that downlink beamforming training, although increases
pilot overhead and introduces additional pilot contamination, improves
significantly the achievable downlink rate. Even for large number of APs, it is
not fully efficient for the UE relying on the statistical channel state
information for data decoding.Comment: Published in IEEE Transactions on Wireless Communications on August
14, 2019. {\copyright} 2019 IEEE. Personal use of this material is permitted.
Permission from IEEE must be obtained for all other use
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
Uplink Sounding Reference Signal Coordination to Combat Pilot Contamination in 5G Massive MIMO
To guarantee the success of massive multiple-input multiple-output (MIMO),
one of the main challenges to solve is the efficient management of pilot
contamination. Allocation of fully orthogonal pilot sequences across the
network would provide a solution to the problem, but the associated overhead
would make this approach infeasible in practical systems. Ongoing
fifth-generation (5G) standardisation activities are debating the amount of
resources to be dedicated to the transmission of pilot sequences, focussing on
uplink sounding reference signals (UL SRSs) design. In this paper, we
extensively evaluate the performance of various UL SRS allocation strategies in
practical deployments, shedding light on their strengths and weaknesses.
Furthermore, we introduce a novel UL SRS fractional reuse (FR) scheme, denoted
neighbour-aware FR (FR-NA). The proposed FR-NA generalizes the fixed reuse
paradigm, and entails a tradeoff between i) aggressively sharing some UL SRS
resources, and ii) protecting other UL SRS resources with the aim of relieving
neighbouring BSs from pilot contamination. Said features result in a cell
throughput improvement over both fixed reuse and state-of-the-art FR based on a
cell-centric perspective
Massive MIMO for Next Generation Wireless Systems
Multi-user Multiple-Input Multiple-Output (MIMO) offers big advantages over
conventional point-to-point MIMO: it works with cheap single-antenna terminals,
a rich scattering environment is not required, and resource allocation is
simplified because every active terminal utilizes all of the time-frequency
bins. However, multi-user MIMO, as originally envisioned with roughly equal
numbers of service-antennas and terminals and frequency division duplex
operation, is not a scalable technology. Massive MIMO (also known as
"Large-Scale Antenna Systems", "Very Large MIMO", "Hyper MIMO", "Full-Dimension
MIMO" & "ARGOS") makes a clean break with current practice through the use of a
large excess of service-antennas over active terminals and time division duplex
operation. Extra antennas help by focusing energy into ever-smaller regions of
space to bring huge improvements in throughput and radiated energy efficiency.
Other benefits of massive MIMO include the extensive use of inexpensive
low-power components, reduced latency, simplification of the media access
control (MAC) layer, and robustness to intentional jamming. The anticipated
throughput depend on the propagation environment providing asymptotically
orthogonal channels to the terminals, but so far experiments have not disclosed
any limitations in this regard. While massive MIMO renders many traditional
research problems irrelevant, it uncovers entirely new problems that urgently
need attention: the challenge of making many low-cost low-precision components
that work effectively together, acquisition and synchronization for
newly-joined terminals, the exploitation of extra degrees of freedom provided
by the excess of service-antennas, reducing internal power consumption to
achieve total energy efficiency reductions, and finding new deployment
scenarios. This paper presents an overview of the massive MIMO concept and
contemporary research.Comment: Final manuscript, to appear in IEEE Communications Magazin
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