4,781 research outputs found
Massive MIMO performance evaluation based on measured propagation data
Massive MIMO, also known as very-large MIMO or large-scale antenna systems,
is a new technique that potentially can offer large network capacities in
multi-user scenarios. With a massive MIMO system, we consider the case where a
base station equipped with a large number of antenna elements simultaneously
serves multiple single-antenna users in the same time-frequency resource. So
far, investigations are mostly based on theoretical channels with independent
and identically distributed (i.i.d.) complex Gaussian coefficients, i.e.,
i.i.d. Rayleigh channels. Here, we investigate how massive MIMO performs in
channels measured in real propagation environments. Channel measurements were
performed at 2.6 GHz using a virtual uniform linear array (ULA) which has a
physically large aperture, and a practical uniform cylindrical array (UCA)
which is more compact in size, both having 128 antenna ports. Based on
measurement data, we illustrate channel behavior of massive MIMO in three
representative propagation conditions, and evaluate the corresponding
performance. The investigation shows that the measured channels, for both array
types, allow us to achieve performance close to that in i.i.d. Rayleigh
channels. It is concluded that in real propagation environments we have
characteristics that can allow for efficient use of massive MIMO, i.e., the
theoretical advantages of this new technology can also be harvested in real
channels.Comment: IEEE Transactions on Wireless Communications, 201
Doctoral Thesis: Massive MIMO in Real Propagation Environments
Mobile communications are now evolving towards the fifth generation (5G). In the near future, we expect an explosive increase in the number of connected devices, such as phones, tablets, sensors, connected vehicles and so on. Much higher data rates than in today's 4G systems are required. In the 5G visions, better coverage in remote regions is also included, aiming for bringing the current "4 billion unconnected" population into the online world. There is also a great interest in "green communications", for less energy consumption in the ICT (information and communication technology) industry. Massive MIMO is a potential technology to fulfill the requirements and visions. By equipping a base station with a large number, say tens to hundreds, of antennas, many terminals can be served in the same time-frequency resource without severe inter-user interference. Through "aggressive" spatial multiplexing, higher data rates can be achieved without increasing the required spectrum. Processing efforts can be made at the base station side, allowing terminals to have simple and cheap hardware. By exploiting the many spatial degrees of freedom, linear precoding/detection schemes can be used to achieve near-optimal performance. The large number of antennas also brings the advantage of large array gain, resulting in an increase in received signal strength. Better coverage is thus achieved. On the other hand, transmit power from base stations and terminals can be scaled down to pursue energy efficiency. In the last five years, a lot of theoretical studies have been done, showing the extraordinary advantages of massive MIMO. However, the investigations are mainly based on theoretical channels with independent and identically distributed (i.i.d.) Gaussian coefficients, and sometimes assuming unlimited number of antennas. When bringing this new technology from theory to practice, it is important to understand massive MIMO behavior in real propagation channels using practical antenna arrays. Not much has been known about real massive MIMO channels, and whether the claims about massive MIMO still hold there, until the studies in this thesis were done. The thesis study connects the "ideal" world of theory to the "non-ideal" reality. Channel measurements for massive MIMO in the 2.6 GHz band were performed, in different propagation environments and using different types of antenna arrays. Based on obtained real-life channel data, the studies include • channel characterization to identify important massive MIMO properties, • evaluation of propagation conditions in real channels and corresponding massive MIMO performance, • channel modeling for massive MIMO to capture the identified channel properties, and • reduction of massive MIMO hardware complexity through antenna selection. The investigations in the thesis conclude that massive MIMO works efficiently in real propagation environments. The theoretical advantages, as observed in i.i.d. Rayleigh channels, can also be harvested in real channels. Important propagation effects are identified for massive MIMO scenarios, including channel variations over large arrays, multipath-component (MPC) lifetime, and 3D propagation. These propagation properties are modeled and included into the COST 2100 MIMO channel model as an extension for massive MIMO. The study on antenna selection shows that characteristics in real channels allow for significant reductions of massive MIMO complexity without significant performance loss. As one of the world's first research work on massive MIMO behavior in real propagation channels, the studies in this thesis promote massive MIMO as a practical technology for future communication systems
Millimeter-Wave Massive MIMO Testbed with Hybrid Beamforming
Massive multiple-input multiple-out (MIMO) technology is vital in
millimeter-wave (mmWave) bands to obtain large array gains. However, there are
practical challenges, such as high hardware cost and power consumption in such
systems. A promising solution to these problems is to adopt a hybrid
beamforming architecture. This architecture has a much lower number of
transceiver (TRx) chains than the total antenna number, resulting in cost- and
energy-efficient systems. In this paper, we present a real-time mmWave (28 GHz)
massive MIMO testbed with hybrid beamforming. This testbed has a
64-antenna/16-TRx unit for beam-selection, which can be expanded to larger
array sizes in a modular way. For testing everything from baseband processing
algorithms to scheduling and beam-selection in real propagation environments,
we extend the capability of an existing 100-antenna/100-TRx massive MIMO
testbed (below 6 GHz), built upon software-defined radio technology, to a
flexible mmWave massive MIMO system.Comment: 54th Asilomar Conference on Signals, Systems, and Computers, Nov.
202
Massive MIMO in Real Propagation Environments: Do All Antennas Contribute Equally?
Massive MIMO can greatly increase both spectral and transmit-energy
efficiency. This is achieved by allowing the number of antennas and RF chains
to grow very large. However, the challenges include high system complexity and
hardware energy consumption. Here we investigate the possibilities to reduce
the required number of RF chains, by performing antenna selection. While this
approach is not a very effective strategy for theoretical independent Rayleigh
fading channels, a substantial reduction in the number of RF chains can be
achieved for real massive MIMO channels, without significant performance loss.
We evaluate antenna selection performance on measured channels at 2.6 GHz,
using a linear and a cylindrical array, both having 128 elements. Sum-rate
maximization is used as the criterion for antenna selection. A selection scheme
based on convex optimization is nearly optimal and used as a benchmark. The
achieved sum-rate is compared with that of a very simple scheme that selects
the antennas with the highest received power. The power-based scheme gives
performance close to the convex optimization scheme, for the measured channels.
This observation indicates a potential for significant reductions of massive
MIMO implementation complexity, by reducing the number of RF chains and
performing antenna selection using simple algorithms.Comment: Submitted to IEEE Transactions on Communication
Indoor wireless communications and applications
Chapter 3 addresses challenges in radio link and system design in indoor scenarios. Given the fact that most human activities take place in indoor environments, the need for supporting ubiquitous indoor data connectivity and location/tracking service becomes even more important than in the previous decades. Specific technical challenges addressed in this section are(i), modelling complex indoor radio channels for effective antenna deployment, (ii), potential of millimeter-wave (mm-wave) radios for supporting higher data rates, and (iii), feasible indoor localisation and tracking techniques, which are summarised in three dedicated sections of this chapter
Massive MIMO-based Localization and Mapping Exploiting Phase Information of Multipath Components
In this paper, we present a robust multipath-based localization and mapping
framework that exploits the phases of specular multipath components (MPCs)
using a massive multiple-input multiple-output (MIMO) array at the base
station. Utilizing the phase information related to the propagation distances
of the MPCs enables the possibility of localization with extraordinary accuracy
even with limited bandwidth. The specular MPC parameters along with the
parameters of the noise and the dense multipath component (DMC) are tracked
using an extended Kalman filter (EKF), which enables to preserve the
distance-related phase changes of the MPC complex amplitudes. The DMC comprises
all non-resolvable MPCs, which occur due to finite measurement aperture. The
estimation of the DMC parameters enhances the estimation quality of the
specular MPCs and therefore also the quality of localization and mapping. The
estimated MPC propagation distances are subsequently used as input to a
distance-based localization and mapping algorithm. This algorithm does not need
prior knowledge about the surrounding environment and base station position.
The performance is demonstrated with real radio-channel measurements using an
antenna array with 128 ports at the base station side and a standard cellular
signal bandwidth of 40 MHz. The results show that high accuracy localization is
possible even with such a low bandwidth.Comment: 14 pages (two columns), 13 figures. This work has been submitted to
the IEEE Transaction on Wireless Communications for possible publication.
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