2,168 research outputs found
Wireless Power Transfer in Massive MIMO Aided HetNets with User Association
This paper explores the potential of wireless power transfer (WPT) in massive
multiple input multiple output (MIMO) aided heterogeneous networks (HetNets),
where massive MIMO is applied in the macrocells, and users aim to harvest as
much energy as possible and reduce the uplink path loss for enhancing their
information transfer. By addressing the impact of massive MIMO on the user
association, we compare and analyze two user association schemes. We adopt the
linear maximal ratio transmission beam-forming for massive MIMO power transfer
to recharge users. By deriving new statistical properties, we obtain the exact
and asymptotic expressions for the average harvested energy. Then we derive the
average uplink achievable rate under the harvested energy constraint.Comment: 36 pages, 11 figures, to appear in IEEE Transactions on
Communication
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
Uplink Analysis of Large MU-MIMO Systems With Space-Constrained Arrays in Ricean Fading
Closed-form approximations to the expected per-terminal
signal-to-interference-plus-noise-ratio (SINR) and ergodic sum spectral
efficiency of a large multiuser multiple-input multiple-output system are
presented. Our analysis assumes correlated Ricean fading with maximum ratio
combining on the uplink, where the base station (BS) is equipped with a uniform
linear array (ULA) with physical size restrictions. Unlike previous studies,
our model caters for the presence of unequal correlation matrices and unequal
Rice factors for each terminal. As the number of BS antennas grows without
bound, with a finite number of terminals, we derive the limiting expected
per-terminal SINR and ergodic sum spectral efficiency of the system. Our
findings suggest that with restrictions on the size of the ULA, the expected
SINR saturates with increasing operating signal-to-noise-ratio (SNR) and BS
antennas. Whilst unequal correlation matrices result in higher performance, the
presence of strong line-of-sight (LoS) has an opposite effect. Our analysis
accommodates changes in system dimensions, SNR, LoS levels, spatial correlation
levels and variations in fixed physical spacings of the BS array.Comment: 7 pages, 3 figures, accepted for publication in the proceedings of
IEEE ICC, to be held in Paris, France, May 201
Massive MIMO is a Reality -- What is Next? Five Promising Research Directions for Antenna Arrays
Massive MIMO (multiple-input multiple-output) is no longer a "wild" or
"promising" concept for future cellular networks - in 2018 it became a reality.
Base stations (BSs) with 64 fully digital transceiver chains were commercially
deployed in several countries, the key ingredients of Massive MIMO have made it
into the 5G standard, the signal processing methods required to achieve
unprecedented spectral efficiency have been developed, and the limitation due
to pilot contamination has been resolved. Even the development of fully digital
Massive MIMO arrays for mmWave frequencies - once viewed prohibitively
complicated and costly - is well underway. In a few years, Massive MIMO with
fully digital transceivers will be a mainstream feature at both sub-6 GHz and
mmWave frequencies. In this paper, we explain how the first chapter of the
Massive MIMO research saga has come to an end, while the story has just begun.
The coming wide-scale deployment of BSs with massive antenna arrays opens the
door to a brand new world where spatial processing capabilities are
omnipresent. In addition to mobile broadband services, the antennas can be used
for other communication applications, such as low-power machine-type or
ultra-reliable communications, as well as non-communication applications such
as radar, sensing and positioning. We outline five new Massive MIMO related
research directions: Extremely large aperture arrays, Holographic Massive MIMO,
Six-dimensional positioning, Large-scale MIMO radar, and Intelligent Massive
MIMO.Comment: 20 pages, 9 figures, submitted to Digital Signal Processin
- …