280 research outputs found
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
Ubiquitous Cell-Free Massive MIMO Communications
Since the first cellular networks were trialled in the 1970s, we have
witnessed an incredible wireless revolution. From 1G to 4G, the massive traffic
growth has been managed by a combination of wider bandwidths, refined radio
interfaces, and network densification, namely increasing the number of antennas
per site. Due its cost-efficiency, the latter has contributed the most. Massive
MIMO (multiple-input multiple-output) is a key 5G technology that uses massive
antenna arrays to provide a very high beamforming gain and spatially
multiplexing of users, and hence, increases the spectral and energy efficiency.
It constitutes a centralized solution to densify a network, and its performance
is limited by the inter-cell interference inherent in its cell-centric design.
Conversely, ubiquitous cell-free Massive MIMO refers to a distributed Massive
MIMO system implementing coherent user-centric transmission to overcome the
inter-cell interference limitation in cellular networks and provide additional
macro-diversity. These features, combined with the system scalability inherent
in the Massive MIMO design, distinguishes ubiquitous cell-free Massive MIMO
from prior coordinated distributed wireless systems. In this article, we
investigate the enormous potential of this promising technology while
addressing practical deployment issues to deal with the increased
back/front-hauling overhead deriving from the signal co-processing.Comment: Published in EURASIP Journal on Wireless Communications and
Networking on August 5, 201
Spectral Efficiency Analysis of Multi-Cell Massive MIMO Systems with Ricean Fading
This paper investigates the spectral efficiency of multi-cell massive
multiple-input multiple-output systems with Ricean fading that utilize the
linear maximal-ratio combining detector. We firstly present closed-form
expressions for the effective signal-to-interference-plus-noise ratio (SINR)
with the least squares and minimum mean squared error (MMSE) estimation
methods, respectively, which apply for any number of base-station antennas
and any Ricean -factor. Also, the obtained results can be particularized in
Rayleigh fading conditions when the Ricean -factor is equal to zero. In the
following, novel exact asymptotic expressions of the effective SINR are derived
in the high and high Ricean -factor regimes. The corresponding analysis
shows that pilot contamination is removed by the MMSE estimator when we
consider both infinite and infinite Ricean -factor, while the pilot
contamination phenomenon persists for the rest of cases. All the theoretical
results are verified via Monte-Carlo simulations.Comment: 15 pages, 2 figures, the tenth International Conference on Wireless
Communications and Signal Processing (WCSP 2018), to appea
Electromagnetic Lens-focusing Antenna Enabled Massive MIMO: Performance Improvement and Cost Reduction
Massive multiple-input multiple-output (MIMO) techniques have been recently
advanced to tremendously improve the performance of wireless communication
networks. However, the use of very large antenna arrays at the base stations
(BSs) brings new issues, such as the significantly increased hardware and
signal processing costs. In order to reap the enormous gain of massive MIMO and
yet reduce its cost to an affordable level, this paper proposes a novel system
design by integrating an electromagnetic (EM) lens with the large antenna
array, termed the EM-lens enabled MIMO. The EM lens has the capability of
focusing the power of an incident wave to a small area of the antenna array,
while the location of the focal area varies with the angle of arrival (AoA) of
the wave. Therefore, in practical scenarios where the arriving signals from
geographically separated users have different AoAs, the EM-lens enabled system
provides two new benefits, namely energy focusing and spatial interference
rejection. By taking into account the effects of imperfect channel estimation
via pilot-assisted training, in this paper we analytically show that the
average received signal-to-noise ratio (SNR) in both the single-user and
multiuser uplink transmissions can be strictly improved by the EM-lens enabled
system. Furthermore, we demonstrate that the proposed design makes it possible
to considerably reduce the hardware and signal processing costs with only
slight degradations in performance. To this end, two complexity/cost reduction
schemes are proposed, which are small-MIMO processing with parallel receiver
filtering applied over subgroups of antennas to reduce the computational
complexity, and channel covariance based antenna selection to reduce the
required number of radio frequency (RF) chains. Numerical results are provided
to corroborate our analysis.Comment: 30 pages, 9 figure
Joint Pilot Design and Uplink Power Allocation in Multi-Cell Massive MIMO Systems
This paper considers pilot design to mitigate pilot contamination and provide
good service for everyone in multi-cell Massive multiple input multiple output
(MIMO) systems. Instead of modeling the pilot design as a combinatorial
assignment problem, as in prior works, we express the pilot signals using a
pilot basis and treat the associated power coefficients as continuous
optimization variables. We compute a lower bound on the uplink capacity for
Rayleigh fading channels with maximum ratio detection that applies with
arbitrary pilot signals. We further formulate the max-min fairness problem
under power budget constraints, with the pilot signals and data powers as
optimization variables. Because this optimization problem is non-deterministic
polynomial-time hard due to signomial constraints, we then propose an algorithm
to obtain a local optimum with polynomial complexity. Our framework serves as a
benchmark for pilot design in scenarios with either ideal or non-ideal
hardware. Numerical results manifest that the proposed optimization algorithms
are close to the optimal solution obtained by exhaustive search for different
pilot assignments and the new pilot structure and optimization bring large
gains over the state-of-the-art suboptimal pilot design.Comment: 16 pages, 8 figures. Accepted to publish at IEEE Transactions on
Wireless Communication
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