232 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
Reconfigurable Intelligent Surfaces for Wireless Communications: Principles, Challenges, and Opportunities
Recently there has been a flurry of research on the use of reconfigurable
intelligent surfaces (RIS) in wireless networks to create smart radio
environments. In a smart radio environment, surfaces are capable of
manipulating the propagation of incident electromagnetic waves in a
programmable manner to actively alter the channel realization, which turns the
wireless channel into a controllable system block that can be optimized to
improve overall system performance. In this article, we provide a tutorial
overview of reconfigurable intelligent surfaces (RIS) for wireless
communications. We describe the working principles of reconfigurable
intelligent surfaces (RIS) and elaborate on different candidate implementations
using metasurfaces and reflectarrays. We discuss the channel models suitable
for both implementations and examine the feasibility of obtaining accurate
channel estimates. Furthermore, we discuss the aspects that differentiate RIS
optimization from precoding for traditional MIMO arrays highlighting both the
arising challenges and the potential opportunities associated with this
emerging technology. Finally, we present numerical results to illustrate the
power of an RIS in shaping the key properties of a MIMO channel.Comment: to appear in the IEEE Transactions on Cognitive Communications and
Networking (TCCN
Holographic MIMO Communications: Theoretical Foundations, Enabling Technologies, and Future Directions
Future wireless systems are envisioned to create an endogenously
holography-capable, intelligent, and programmable radio propagation
environment, that will offer unprecedented capabilities for high spectral and
energy efficiency, low latency, and massive connectivity. A potential and
promising technology for supporting the expected extreme requirements of the
sixth-generation (6G) communication systems is the concept of the holographic
multiple-input multiple-output (HMIMO), which will actualize holographic radios
with reasonable power consumption and fabrication cost. The HMIMO is
facilitated by ultra-thin, extremely large, and nearly continuous surfaces that
incorporate reconfigurable and sub-wavelength-spaced antennas and/or
metamaterials. Such surfaces comprising dense electromagnetic (EM) excited
elements are capable of recording and manipulating impinging fields with utmost
flexibility and precision, as well as with reduced cost and power consumption,
thereby shaping arbitrary-intended EM waves with high energy efficiency. The
powerful EM processing capability of HMIMO opens up the possibility of wireless
communications of holographic imaging level, paving the way for signal
processing techniques realized in the EM-domain, possibly in conjunction with
their digital-domain counterparts. However, in spite of the significant
potential, the studies on HMIMO communications are still at an initial stage,
its fundamental limits remain to be unveiled, and a certain number of critical
technical challenges need to be addressed. In this survey, we present a
comprehensive overview of the latest advances in the HMIMO communications
paradigm, with a special focus on their physical aspects, their theoretical
foundations, as well as the enabling technologies for HMIMO systems. We also
compare the HMIMO with existing multi-antenna technologies, especially the
massive MIMO, present various...Comment: double column, 58 page
Beam Focusing for Near-Field Multiuser MIMO Communications
Large antenna arrays and high-frequency bands are two key features of future wireless communication systems. The combination of large-scale antennas with high transmission frequencies often results in the communicating devices operating in the near-field (Fresnel) region. In this paper, we study the potential of beam focusing, feasible in near-field operation, in facilitating high-rate multi-user downlink multiple-input multiple-output (MIMO) systems. As the ability to achieve beam focusing is dictated by the transmit antenna, we study near-field signalling considering different antenna structures, including fully-digital architectures, hybrid phase shifter-based precoders, and the emerging dynamic metasurface antenna (DMA) architecture for massive MIMO arrays. We first provide a mathematical model to characterize near-field wireless channels as well as the transmission pattern for the considered antenna architectures. Then, we formulate the beam focusing problem for the goal of maximizing the achievable sum-rate in multi-user networks. We propose efficient solutions based on the sum-rate maximization task for fully-digital, (phase shifters based-) hybrid and DMA architectures. Simulation results show the feasibility of the proposed beam focusing scheme for both single- and multi-user scenarios. In particular, the designed focused beams provide a new degree of freedom to mitigate interference in both angle and distance domains, which is not achievable using conventional far-field beam steering, allowing reliable communications for uses even residing at the same angular direction
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
Dynamic Metasurface Antennas for Energy Efficient Massive MIMO Uplink Communications
Future wireless communications are largely inclined to deploy a massive
number of antennas at the base stations (BS) by exploiting energy-efficient and
environmentally friendly technologies. An emerging technology called dynamic
metasurface antennas (DMAs) is promising to realize such massive antenna arrays
with reduced physical size, hardware cost, and power consumption. This paper
aims to optimize the energy efficiency (EE) performance of DMAs-assisted
massive MIMO uplink communications. We propose an algorithmic framework for
designing the transmit precoding of each multi-antenna user and the DMAs tuning
strategy at the BS to maximize the EE performance, considering the availability
of the instantaneous and statistical channel state information (CSI),
respectively. Specifically, the proposed framework includes Dinkelbach's
transform, alternating optimization, and deterministic equivalent methods. In
addition, we obtain a closed-form solution to the optimal transmit signal
directions for the statistical CSI case, which simplifies the corresponding
transmission design. The numerical results show good convergence performance of
our proposed algorithms as well as considerable EE performance gains of the
DMAs-assisted massive MIMO uplink communications over the baseline schemes
Stacked Intelligent Metasurfaces for Multiuser Downlink Beamforming in the Wave Domain
Intelligent metasurface has recently emerged as a promising technology that
enables the customization of wireless environments by harnessing large numbers
of inexpensive configurable scattering elements. However, prior studies have
predominantly focused on single-layer metasurfaces, which have limitations in
terms of the number of beam patterns they can steer accurately due to practical
hardware restrictions. In contrast, this paper introduces a novel stacked
intelligent metasurface (SIM) design. Specifically, we investigate the
integration of SIM into the downlink of a multiuser multiple-input
single-output (MISO) communication system, where a SIM, consisting of a
multilayer metasurface structure, is deployed at the base station (BS) to
facilitate transmit beamforming in the electromagnetic wave domain. This
eliminates the need for conventional digital beamforming and high-resolution
digital-to-analog converters at the BS. To this end, we formulate an
optimization problem that aims to maximize the sum rate of all user equipments
by jointly optimizing the transmit power allocation at the BS and the
wave-based beamforming at the SIM, subject to both the transmit power budget
and discrete phase shift constraints. Furthermore, we propose a computationally
efficient algorithm for solving this joint optimization problem and elaborate
on the potential benefits of employing SIM in wireless networks. Finally, the
numerical results corroborate the effectiveness of the proposed SIM-enabled
wave-based beamforming design and evaluate the performance improvement achieved
by the proposed algorithm compared to various benchmark schemes. It is
demonstrated that considering the same number of transmit antennas, the
proposed SIM-based system achieves about 200\% improvement in terms of sum rate
compared to conventional MISO systems.Comment: 32 pages, 6 figures, submitted to IEEE TW
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