20 research outputs found
Hardware-Impaired Rician-Faded Cell-Free Massive MIMO Systems With Channel Aging
We study the impact of channel aging on the uplink of a cell-free (CF)
massive multiple-input multiple-output (mMIMO) system by considering i)
spatially-correlated Rician-faded channels; ii) hardware impairments at the
access points and user equipments (UEs); and iii) two-layer large-scale fading
decoding (LSFD). We first derive a closed-form spectral efficiency (SE)
expression for this system, and later propose two novel optimization techniques
to optimize the non-convex SE metric by exploiting the
minorization-maximization (MM) method. The first one requires a numerical
optimization solver, and has a high computation complexity. The second one with
closed-form transmit power updates, has a trivial computation complexity. We
numerically show that i) the two-layer LSFD scheme effectively mitigates the
interference due to channel aging for both low- and high-velocity UEs; and ii)
increasing the number of AP antennas does not mitigate the SE deterioration due
to channel aging. We numerically characterize the optimal pilot length required
to maximize the SE for various UE speeds. We also numerically show that the
proposed closed-form MM optimization yields the same SE as that of the first
technique, which requires numerical solver, and that too with a much reduced
time-complexity.Comment: This work has been submitted to the IEEE Transactions on
Communications for possible publication. Copyright may be transferred without
notice, after which this version may no longer be accessible, 32 pages, 14
figure
Foundations of User-Centric Cell-Free Massive MIMO
Imagine a coverage area where each mobile device is communicating with a
preferred set of wireless access points (among many) that are selected based on
its needs and cooperate to jointly serve it, instead of creating autonomous
cells. This effectively leads to a user-centric post-cellular network
architecture, which can resolve many of the interference issues and
service-quality variations that appear in cellular networks. This concept is
called User-centric Cell-free Massive MIMO (multiple-input multiple-output) and
has its roots in the intersection between three technology components: Massive
MIMO, coordinated multipoint processing, and ultra-dense networks. The main
challenge is to achieve the benefits of cell-free operation in a practically
feasible way, with computational complexity and fronthaul requirements that are
scalable to enable massively large networks with many mobile devices. This
monograph covers the foundations of User-centric Cell-free Massive MIMO,
starting from the motivation and mathematical definition. It continues by
describing the state-of-the-art signal processing algorithms for channel
estimation, uplink data reception, and downlink data transmission with either
centralized or distributed implementation. The achievable spectral efficiency
is mathematically derived and evaluated numerically using a running example
that exposes the impact of various system parameters and algorithmic choices.
The fundamental tradeoffs between communication performance, computational
complexity, and fronthaul signaling requirements are thoroughly analyzed.
Finally, the basic algorithms for pilot assignment, dynamic cooperation cluster
formation, and power optimization are provided, while open problems related to
these and other resource allocation problems are reviewed. All the numerical
examples can be reproduced using the accompanying Matlab code.Comment: This is the authors' version of the manuscript: \"Ozlem Tugfe Demir,
Emil Bj\"ornson and Luca Sanguinetti (2021), "Foundations of User-Centric
Cell-Free Massive MIMO", Foundations and Trends in Signal Processing: Vol.
14, No. 3-4, pp 162-47
RIS-Aided Cell-Free Massive MIMO Systems for 6G: Fundamentals, System Design, and Applications
An introduction of intelligent interconnectivity for people and things has
posed higher demands and more challenges for sixth-generation (6G) networks,
such as high spectral efficiency and energy efficiency, ultra-low latency, and
ultra-high reliability. Cell-free (CF) massive multiple-input multiple-output
(mMIMO) and reconfigurable intelligent surface (RIS), also called intelligent
reflecting surface (IRS), are two promising technologies for coping with these
unprecedented demands. Given their distinct capabilities, integrating the two
technologies to further enhance wireless network performances has received
great research and development attention. In this paper, we provide a
comprehensive survey of research on RIS-aided CF mMIMO wireless communication
systems. We first introduce system models focusing on system architecture and
application scenarios, channel models, and communication protocols.
Subsequently, we summarize the relevant studies on system operation and
resource allocation, providing in-depth analyses and discussions. Following
this, we present practical challenges faced by RIS-aided CF mMIMO systems,
particularly those introduced by RIS, such as hardware impairments and
electromagnetic interference. We summarize corresponding analyses and solutions
to further facilitate the implementation of RIS-aided CF mMIMO systems.
Furthermore, we explore an interplay between RIS-aided CF mMIMO and other
emerging 6G technologies, such as next-generation multiple-access (NGMA),
simultaneous wireless information and power transfer (SWIPT), and millimeter
wave (mmWave). Finally, we outline several research directions for future
RIS-aided CF mMIMO systems.Comment: 30 pages, 15 figure
Cell-free Massive MIMO and SWIPT: Access Point Operation Mode Selection and Power Control
This paper studies cell-free massive multiple-input multiple-output
(CF-mMIMO) systems incorporating simultaneous wireless information and power
transfer (SWIPT) for separate information users (IUs) and energy users (EUs) in
Internet of Things (IoT) networks. To optimize both the spectral efficiency
(SE) of IUs and harvested energy (HE) of EUs, we propose a joint access point
(AP) operation mode selection and power control design, wherein certain APs are
designated for energy transmission to EUs, while others are dedicated to
information transmission to IUs. We investigate the problem of maximizing the
total HE for EUs, considering constraints on SE for individual IUs and minimum
HE for individual EUs. Our numerical results showcase that the proposed AP
operation mode selection algorithm can provide up to and
performance gains over random AP operation mode selection with and without
power control, respectively.Comment: 6 pages, 2 figures, to be presented at GLOBECOM 2023, Kuala Lumpu
Efficient Battery Usage in Wireless-Powered Cell-Free Systems with Self-Energy Recycling
This paper investigates wireless-powered cell-free systems, in which the
users send their uplink data signal while simultaneously harvesting energy from
network nodes and user terminals - including the transmitting user terminal
itself - by performing self-energy recycling. In this rather general setting, a
closed-form lower bound of the amount of harvested energy and the achieved
signal-to-interference-plus-noise ratio expressions are derived. Then, to
improve the energy efficiency, we formulate the problem of minimizing the
users' battery energy usage while satisfying minimum data rate requirements.
Due to the non-convexity of the problem, a novel alternating optimization
algorithm is proposed, and its proof of convergence is provided. Finally,
numerical results show that the proposed method is more efficient than a
state-of-art algorithm in terms of battery energy usage and outage rate.Comment: Accepted as a correspondance at IEEE TV