1,342 research outputs found
A Survey of Physical Layer Security Techniques for 5G Wireless Networks and Challenges Ahead
Physical layer security which safeguards data confidentiality based on the
information-theoretic approaches has received significant research interest
recently. The key idea behind physical layer security is to utilize the
intrinsic randomness of the transmission channel to guarantee the security in
physical layer. The evolution towards 5G wireless communications poses new
challenges for physical layer security research. This paper provides a latest
survey of the physical layer security research on various promising 5G
technologies, including physical layer security coding, massive multiple-input
multiple-output, millimeter wave communications, heterogeneous networks,
non-orthogonal multiple access, full duplex technology, etc. Technical
challenges which remain unresolved at the time of writing are summarized and
the future trends of physical layer security in 5G and beyond are discussed.Comment: To appear in IEEE Journal on Selected Areas in Communication
Joint Domain Based Massive Access for Small Packets Traffic of Uplink Wireless Channel
The fifth generation (5G) communication scenarios such as the cellular
network and the emerging machine type communications will produce massive small
packets. To support massive connectivity and avoid signaling overhead caused by
the transmission of those small packets, this paper proposes a novel method to
improve the transmission efficiency for massive connections of wireless uplink
channel. The proposed method combines compressive sensing (CS) with power
domain NOMA jointly, especially neither the scheduling nor the centralized
power allocation is necessary in the method. Both the analysis and simulation
show that the method can support up to two or three times overloading.Comment: 6 pages, 5 figures.submitted to globecom 201
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
Signal Processing and Learning for Next Generation Multiple Access in 6G
Wireless communication systems to date primarily rely on the orthogonality of
resources to facilitate the design and implementation, from user access to data
transmission. Emerging applications and scenarios in the sixth generation (6G)
wireless systems will require massive connectivity and transmission of a deluge
of data, which calls for more flexibility in the design concept that goes
beyond orthogonality. Furthermore, recent advances in signal processing and
learning have attracted considerable attention, as they provide promising
approaches to various complex and previously intractable problems of signal
processing in many fields. This article provides an overview of research
efforts to date in the field of signal processing and learning for
next-generation multiple access, with an emphasis on massive random access and
non-orthogonal multiple access. The promising interplay with new technologies
and the challenges in learning-based NGMA are discussed
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