296 research outputs found
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
Recommended from our members
Analysis of millimeter wave and massive MIMO cellular networks
Millimeter wave (mmWave) communication and massive multiple-input multiple-output (MIMO) are promising techniques to increase system capacity in 5G cellular networks. The prior frameworks for conventional cellular systems do not directly apply to analyze mmWave or massive MIMO networks, as (i) mmWave cellular networks differ in the different propagation conditions and hardware constraints; and (ii) with a order of magnitude more antennas than conventional multi-user MIMO systems, massive MIMO systems will be operated in time-division duplex (TDD) mode, which renders pilot contamination a primary limiting factor. In this dissertation, I develop stochastic geometry frameworks to analyze the system-level performance of mmWave, sub-6 GHz massive MIMO, and mmWave massive MIMO cellular networks. The proposed models capture the key features of each technique, and allow for tractable signal-to-interference-plus-noise ratio (SINR) and rate analyses. In the first contribution, I develop an mmWave cellular network model that incorporates the blockage effect and directional beamforming, and analyze the SINR and rate distributions as functions of the base station density, blockage parameters, and antenna geometry. The analytical results demonstrate that with a sufficiently dense base station deployment, mmWave cellular networks are capable to achieve comparable SINR coverage and much higher rates than conventional networks. In my second contribution, I analyze the uplink SINR and rate in sub-6 GHz massive MIMO networks with the incorporation of pilot contamination and fractional power control. Based on the analysis, I show scaling laws between the number of antennas and scheduled users per cell that maintain the uplink signal-to-interference ratio (SIR) distributions are different for maximum ratio combining (MRC) and zero-forcing (ZF) receivers. In my third contribution, I extend the sub-6 GHz massive MIMO model to mmWave frequencies, by incorporating key mmWave features. I leverage the proposed model to investigate the asymptotic SINR performance, when the number of antennas goes to infinity. Numerical results show that mmWave massive MIMO outperforms its sub-6 GHz counterpart in cell throughput with a dense base station deployment, while the reverse can be true with a low base station density.Electrical and Computer Engineerin
Asymptotic Analysis of Multicell Massive MIMO over Rician Fading Channels
This work considers the downlink of a multicell massive MIMO system in which
base stations (BSs) of antennas each communicate with
single-antenna user equipments randomly positioned in the coverage area. Within
this setting, we are interested in evaluating the sum rate of the system when
MRT and RZF are employed under the assumption that each intracell link forms a
MIMO Rician fading channel. The analysis is conducted assuming that and
grow large with a non-trivial ratio under the assumption that the data
transmission in each cell is affected by channel estimation errors, pilot
contamination, and an arbitrary large scale attenuation. Numerical results are
used to validate the asymptotic analysis in the finite system regime and to
evaluate the network performance under different settings. The asymptotic
results are also instrumental to get insights into the interplay among system
parameters.Comment: 7 pages, 2 figures, submitted to GLOBECOM16, Washington, DC USA.
arXiv admin note: text overlap with arXiv:1601.0702
Asymptotic analysis of downlink MIMO systems over Rician fading channels
In this work, we focus on the ergodic sum rate in the downlink of a
single-cell large-scale multi-user MIMO system in which the base station
employs N antennas to communicate with single-antenna user equipments. A
regularized zero-forcing (RZF) scheme is used for precoding under the
assumption that each link forms a spatially correlated MIMO Rician fading
channel. The analysis is conducted assuming and grow large with a non
trivial ratio and perfect channel state information is available at the base
station. Recent results from random matrix theory and large system analysis are
used to compute an asymptotic expression of the signal-to-interference-
plus-noise ratio as a function of the system parameters, the spatial
correlation matrix and the Rician factor. Numerical results are used to
evaluate the performance gap in the finite system regime under different
operating conditions.Comment: 5 pages, 2 figures. Published at the 41st IEEE International
Conference on Acoustics, Speech and Signal Processing (ICASSP 2016),
Shanghai, 20-25 March 201
- …