187 research outputs found
Multiple Access in Aerial Networks: From Orthogonal and Non-Orthogonal to Rate-Splitting
Recently, interest on the utilization of unmanned aerial vehicles (UAVs) has
aroused. Specifically, UAVs can be used in cellular networks as aerial users
for delivery, surveillance, rescue search, or as an aerial base station (aBS)
for communication with ground users in remote uncovered areas or in dense
environments requiring prompt high capacity. Aiming to satisfy the high
requirements of wireless aerial networks, several multiple access techniques
have been investigated. In particular, space-division multiple access(SDMA) and
power-domain non-orthogonal multiple access (NOMA) present promising
multiplexing gains for aerial downlink and uplink. Nevertheless, these gains
are limited as they depend on the conditions of the environment. Hence, a
generalized scheme has been recently proposed, called rate-splitting multiple
access (RSMA), which is capable of achieving better spectral efficiency gains
compared to SDMA and NOMA. In this paper, we present a comprehensive survey of
key multiple access technologies adopted for aerial networks, where aBSs are
deployed to serve ground users. Since there have been only sporadic results
reported on the use of RSMA in aerial systems, we aim to extend the discussion
on this topic by modelling and analyzing the weighted sum-rate performance of a
two-user downlink network served by an RSMA-based aBS. Finally, related open
issues and future research directions are exposed.Comment: 16 pages, 6 figures, submitted to IEEE Journa
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
Hybrid precoding for beamspace MIMO systems with sub-connected switches: a machine learning approach
By employing lens antenna arrays, the number of radio frequency (RF) chains in millimeter-wave (mmWave) communications can be significantly reduced. However, most existing studies consider the phase shifters (PSs) as the main components of the analog beamformer, which may result in a significant loss of energy efficiency (EE). In this paper, we propose a switch selecting network to solve this issue, where the analog part of the beamspace MIMO system is realized by a sub-connected switch selecting network rather than the PS network. Based on the proposed architecture and inspired by the cross-entropy (CE) optimization developed in machine learning, an optimal hybrid cross-entropy (HCE)-based hybrid precoding scheme is designed to maximize the achievable sum rate, where the probability distribution of the hybrid precoder is updated by minimizing CE with unadjusted probabilities and smoothing constant. Simulation results show that the proposed HCE-based hybrid precoding can not only effectively achieve the satisfied sum-rate, but also outperform the PSs schemes concerning energy efficiency
Evolution of NOMA Toward Next Generation Multiple Access (NGMA) for 6G
Due to the explosive growth in the number of wireless devices and diverse
wireless services, such as virtual/augmented reality and
Internet-of-Everything, next generation wireless networks face unprecedented
challenges caused by heterogeneous data traffic, massive connectivity, and
ultra-high bandwidth efficiency and ultra-low latency requirements. To address
these challenges, advanced multiple access schemes are expected to be
developed, namely next generation multiple access (NGMA), which are capable of
supporting massive numbers of users in a more resource- and
complexity-efficient manner than existing multiple access schemes. As the
research on NGMA is in a very early stage, in this paper, we explore the
evolution of NGMA with a particular focus on non-orthogonal multiple access
(NOMA), i.e., the transition from NOMA to NGMA. In particular, we first review
the fundamental capacity limits of NOMA, elaborate on the new requirements for
NGMA, and discuss several possible candidate techniques. Moreover, given the
high compatibility and flexibility of NOMA, we provide an overview of current
research efforts on multi-antenna techniques for NOMA, promising future
application scenarios of NOMA, and the interplay between NOMA and other
emerging physical layer techniques. Furthermore, we discuss advanced
mathematical tools for facilitating the design of NOMA communication systems,
including conventional optimization approaches and new machine learning
techniques. Next, we propose a unified framework for NGMA based on multiple
antennas and NOMA, where both downlink and uplink transmissions are considered,
thus setting the foundation for this emerging research area. Finally, several
practical implementation challenges for NGMA are highlighted as motivation for
future work.Comment: 34 pages, 10 figures, a survey paper accepted by the IEEE JSAC
special issue on Next Generation Multiple Acces
6G Enabled Smart Infrastructure for Sustainable Society: Opportunities, Challenges, and Research Roadmap
The 5G wireless communication network is currently faced with the challenge of limited data speed exacerbated by the proliferation of billions of data-intensive applications. To address this problem, researchers are developing cutting-edge technologies for the envisioned 6G wireless communication standards to satisfy the escalating wireless services demands. Though some of the candidate technologies in the 5G standards will apply to 6G wireless networks, key disruptive technologies that will guarantee the desired quality of physical experience to achieve ubiquitous wireless connectivity are expected in 6G. This article first provides a foundational background on the evolution of different wireless communication standards to have a proper insight into the vision and requirements of 6G. Second, we provide a panoramic view of the enabling technologies proposed to facilitate 6G and introduce emerging 6G applications such as multi-sensory–extended reality, digital replica, and more. Next, the technology-driven challenges, social, psychological, health and commercialization issues posed to actualizing 6G, and the probable solutions to tackle these challenges are discussed extensively. Additionally, we present new use cases of the 6G technology in agriculture, education, media and entertainment, logistics and transportation, and tourism. Furthermore, we discuss the multi-faceted communication capabilities of 6G that will contribute significantly to global sustainability and how 6G will bring about a dramatic change in the business arena. Finally, we highlight the research trends, open research issues, and key take-away lessons for future research exploration in 6G wireless communicatio
MmWave V2V Localization in MU-MIMO Hybrid Beamforming
Recent trends for vehicular localization in millimetre-wave (mmWave) channels include employing a combination of parameters such as angle of arrival (AOA), angle of departure (AOD), and time of arrival (TOA) of the transmitted/received signals. These parameters are challenging to estimate, which along with the scattering and random nature of mmWave channels, and vehicle mobility lead to errors in localization. To circumvent these challenges, this paper proposes mmWave vehicular localization employing difference of arrival for time and frequency, with multiuser (MU) multiple-input-multiple-output (MIMO) hybrid beamforming; rather than relying on AOD/AOA/TOA estimates. The vehicular localization can exploit the number of vehicles present, as an increase in a number of vehicles reduces the Cramr-Rao bound (CRB) of error estimation. At 10 dB signal-to-noise ratio (SNR) both spatial multiplexing and beamforming result in comparable localization errors. At lower SNR values, spatial multiplexing leads to larger errors compared to beamforming due to formation of spurious peaks in the cross ambiguity function. Accuracy of the estimated parameters is improved by employing an extended Kalman filter leading to a root mean square (RMS) localization error of approximately 6.3 meters
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