2,612 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
Positioning of High-speed Trains using 5G New Radio Synchronization Signals
We study positioning of high-speed trains in 5G new radio (NR) networks by
utilizing specific NR synchronization signals. The studies are based on
simulations with 3GPP-specified radio channel models including path loss,
shadowing and fast fading effects. The considered positioning approach exploits
measurement of Time-Of-Arrival (TOA) and Angle-Of-Departure (AOD), which are
estimated from beamformed NR synchronization signals. Based on the given
measurements and the assumed train movement model, the train position is
tracked by using an Extended Kalman Filter (EKF), which is able to handle the
non-linear relationship between the TOA and AOD measurements, and the estimated
train position parameters. It is shown that in the considered scenario the TOA
measurements are able to achieve better accuracy compared to the AOD
measurements. However, as shown by the results, the best tracking performance
is achieved, when both of the measurements are considered. In this case, a very
high, sub-meter, tracking accuracy can be achieved for most (>75%) of the
tracking time, thus achieving the positioning accuracy requirements envisioned
for the 5G NR. The pursued high-accuracy and high-availability positioning
technology is considered to be in a key role in several envisioned HST use
cases, such as mission-critical autonomous train systems.Comment: 6 pages, 5 figures, IEEE WCNC 2018 (Wireless Communications and
Networking Conference
Context-Awareness Enhances 5G Multi-Access Edge Computing Reliability
The fifth generation (5G) mobile telecommunication network is expected to
support Multi- Access Edge Computing (MEC), which intends to distribute
computation tasks and services from the central cloud to the edge clouds.
Towards ultra-responsive, ultra-reliable and ultra-low-latency MEC services,
the current mobile network security architecture should enable a more
decentralized approach for authentication and authorization processes. This
paper proposes a novel decentralized authentication architecture that supports
flexible and low-cost local authentication with the awareness of context
information of network elements such as user equipment and virtual network
functions. Based on a Markov model for backhaul link quality, as well as a
random walk mobility model with mixed mobility classes and traffic scenarios,
numerical simulations have demonstrated that the proposed approach is able to
achieve a flexible balance between the network operating cost and the MEC
reliability.Comment: Accepted by IEEE Access on Feb. 02, 201
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