2,028 research outputs found
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
Downlink Spectral Efficiency of Cell-Free Massive MIMO with Full-Pilot Zero-Forcing
Cell-free Massive multiple-input multiple-output (MIMO) ensures ubiquitous
communication at high spectral efficiency (SE) thanks to increased
macro-diversity as compared cellular communications. However, system
scalability and performance are limited by fronthauling traffic and
interference. Unlike conventional precoding schemes that only suppress
intra-cell interference, full-pilot zero-forcing (fpZF), introduced in [1],
actively suppresses also inter-cell interference, without sharing channel state
information (CSI) among the access points (APs). In this study, we derive a new
closed-form expression for the downlink (DL) SE of a cell-free Massive MIMO
system with multi-antenna APs and fpZF precoding, under imperfect CSI and pilot
contamination. The analysis also includes max-min fairness DL power
optimization. Numerical results show that fpZF significantly outperforms
maximum ratio transmission scheme, without increasing the fronthauling
overhead, as long as the system is sufficiently distributed.Comment: Paper published in 2018 IEEE Global Conference on Signal and
Information Processing (GlobalSIP). {\copyright} 2019 IEEE. Personal use of
this material is permitted. Permission from IEEE must be obtained for all
other use
Adversarial Attacks and Defenses in 6G Network-Assisted IoT Systems
The Internet of Things (IoT) and massive IoT systems are key to
sixth-generation (6G) networks due to dense connectivity, ultra-reliability,
low latency, and high throughput. Artificial intelligence, including deep
learning and machine learning, offers solutions for optimizing and deploying
cutting-edge technologies for future radio communications. However, these
techniques are vulnerable to adversarial attacks, leading to degraded
performance and erroneous predictions, outcomes unacceptable for ubiquitous
networks. This survey extensively addresses adversarial attacks and defense
methods in 6G network-assisted IoT systems. The theoretical background and
up-to-date research on adversarial attacks and defenses are discussed.
Furthermore, we provide Monte Carlo simulations to validate the effectiveness
of adversarial attacks compared to jamming attacks. Additionally, we examine
the vulnerability of 6G IoT systems by demonstrating attack strategies
applicable to key technologies, including reconfigurable intelligent surfaces,
massive multiple-input multiple-output (MIMO)/cell-free massive MIMO,
satellites, the metaverse, and semantic communications. Finally, we outline the
challenges and future developments associated with adversarial attacks and
defenses in 6G IoT systems.Comment: 17 pages, 5 figures, and 4 tables. Submitted for publication
The Road to 6G: Ten Physical Layer Challenges for Communications Engineers
While the deployment of 5G cellular systems will continue well in to the next
decade, much interest is already being generated towards technologies that will
underlie its successor, 6G. Undeniably, 5G will have transformative impact on
the way we live and communicate, yet, it is still far away from supporting the
Internet-of-Everything (IoE), where upwards of a million devices per
(both terrestrial and aerial) will require ubiquitous,
reliable, low-latency connectivity. This article looks at some of the
fundamental problems that pertain to key physical layer enablers for 6G. This
includes highlighting challenges related to intelligent reflecting surfaces,
cell-free massive MIMO and THz communications. Our analysis covers theoretical
modeling challenges, hardware implementation issues and scalability among
others. The article concludes by delineating the critical role of signal
processing in the new era for wireless communications.Comment: IEEE Communications Magazine, Accepte
Performance Analysis of Cell-Free Massive MIMO Systems: A Stochastic Geometry Approach
© 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.Cell-free (CF) massive multiple-input-multiple-output (MIMO) has emerged as an alternative deployment for conventional cellular massive MIMO networks. As revealed by its name, this topology considers no cells, while a large number of multi-antenna access points (APs) serves simultaneously a smaller number of users over the same time/frequency resources through time-division duplex (TDD) operation. Prior works relied on the strong assumption (quite idealized) that the APs are uniformly distributed, and actually, this randomness was considered during the simulation and not in the analysis. However, in practice, ongoing and future networks become denser and increasingly irregular. Having this in mind, we consider that the AP locations are modeled by means of a Poisson point process (PPP) which is a more realistic model for the spatial randomness than a grid or uniform deployment. In particular, by virtue of stochastic geometry tools, we derive both the downlink coverage probability and achievable rate. Notably, this is the only work providing the coverage probability and shedding light on this aspect of CF massive MIMO systems. Focusing on the extraction of interesting insights, we consider small-cells (SCs) as a benchmark for comparison. Among the findings, CF massive MIMO systems achieve both higher coverage and rate with comparison to SCs due to the properties of favorable propagation, channel hardening, and interference suppression. Especially, we showed for both architectures that increasing the AP density results in a higher coverage which saturates after a certain value and increasing the number of users decreases the achievable rate but CF massive MIMO systems take advantage of the aforementioned properties, and thus, outperform SCs. In general, the performance gap between CF massive MIMO systems and SCs is enhanced by increasing the AP density. Another interesting observation concerns that a higher path-loss exponent decreases the rate while the users closer to the APs affect more the performance in terms of the rate.Peer reviewe
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
A Holistic Investigation on Terahertz Propagation and Channel Modeling Toward Vertical Heterogeneous Networks
User-centric and low latency communications can be enabled not only by small
cells but also through ubiquitous connectivity. Recently, the vertical
heterogeneous network (V-HetNet) architecture is proposed to backhaul/fronthaul
a large number of small cells. Like an orchestra, the V-HetNet is a polyphony
of different communication ensembles, including geostationary orbit (GEO), and
low-earth orbit (LEO) satellites (e.g., CubeSats), and networked flying
platforms (NFPs) along with terrestrial communication links. In this study, we
propose the Terahertz (THz) communications to enable the elements of V-HetNets
to function in harmony. As THz links offer a large bandwidth, leading to
ultra-high data rates, it is suitable for backhauling and fronthauling small
cells. Furthermore, THz communications can support numerous applications from
inter-satellite links to in-vivo nanonetworks. However, to savor this harmony,
we need accurate channel models. In this paper, the insights obtained through
our measurement campaigns are highlighted, to reveal the true potential of THz
communications in V-HetNets.Comment: It has been accepted for the publication in IEEE Communications
Magazin
Thirty Years of Machine Learning: The Road to Pareto-Optimal Wireless Networks
Future wireless networks have a substantial potential in terms of supporting
a broad range of complex compelling applications both in military and civilian
fields, where the users are able to enjoy high-rate, low-latency, low-cost and
reliable information services. Achieving this ambitious goal requires new radio
techniques for adaptive learning and intelligent decision making because of the
complex heterogeneous nature of the network structures and wireless services.
Machine learning (ML) algorithms have great success in supporting big data
analytics, efficient parameter estimation and interactive decision making.
Hence, in this article, we review the thirty-year history of ML by elaborating
on supervised learning, unsupervised learning, reinforcement learning and deep
learning. Furthermore, we investigate their employment in the compelling
applications of wireless networks, including heterogeneous networks (HetNets),
cognitive radios (CR), Internet of things (IoT), machine to machine networks
(M2M), and so on. This article aims for assisting the readers in clarifying the
motivation and methodology of the various ML algorithms, so as to invoke them
for hitherto unexplored services as well as scenarios of future wireless
networks.Comment: 46 pages, 22 fig
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