213 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
Artificial-Noise-Aided Secure Multi-Antenna Transmission with Limited Feedback
We present an optimized secure multi-antenna transmission approach based on
artificial-noise-aided beamforming, with limited feedback from a desired
single-antenna receiver. To deal with beamformer quantization errors as well as
unknown eavesdropper channel characteristics, our approach is aimed at
maximizing throughput under dual performance constraints - a connection outage
constraint on the desired communication channel and a secrecy outage constraint
to guard against eavesdropping. We propose an adaptive transmission strategy
that judiciously selects the wiretap coding parameters, as well as the power
allocation between the artificial noise and the information signal. This
optimized solution reveals several important differences with respect to
solutions designed previously under the assumption of perfect feedback. We also
investigate the problem of how to most efficiently utilize the feedback bits.
The simulation results indicate that a good design strategy is to use
approximately 20% of these bits to quantize the channel gain information, with
the remainder to quantize the channel direction, and this allocation is largely
insensitive to the secrecy outage constraint imposed. In addition, we find that
8 feedback bits per transmit antenna is sufficient to achieve approximately 90%
of the throughput attainable with perfect feedback.Comment: to appear in IEEE Transactions on Wireless Communication
Resource allocation for NOMA wireless systems
Power-domain non-orthogonal multiple access (NOMA) has been widely recognized as
a promising candidate for the next generation of wireless communication systems. By
applying superposition coding at the transmitter and successive interference cancellation
at the receiver, NOMA allows multiple users to access the same time-frequency resource
in power domain. This way, NOMA not only increases the system’s spectral and energy
efficiencies, but also supports more users when compared with the conventional orthogonal
multiple access (OMA). Meanwhile, improved user fairness can be achieved by NOMA.
Nonetheless, the promised advantages of NOMA cannot be realized without proper
resource allocation. The main resources in wireless communication systems include time,
frequency, space, code and power. In NOMA systems, multiple users are accommodated
in each time/frequency/code resource block (RB), forming a NOMA cluster. As a result,
how to group the users into NOMA clusters and allocate the power is of significance. A
large number of studies have been carried out for developing efficient power allocation
(PA) algorithms in single-input single-output (SISO) scenarios with fixed user clustering.
To fully reap the gain of NOMA, the design of joint PA and user clustering is required.
Moreover, the study of PA under multiple-input multiple-output (MIMO) systems still
remains at an incipient stage. In this dissertation, we develop novel algorithms to allocate
resource for both SISO-NOMA and MIMO-NOMA systems.
More specifically, Chapter 2 compares the system capacity of MIMO-NOMA with
MIMO-OMA. It is proved analytically that MIMO-NOMA outperforms MIMO-OMA in terms of both sum channel capacity and ergodic sum capacity when there are multiple
users in a cluster. Furthermore, it is demonstrated that the more users are admitted to
a cluster, the lower is the achieved sum rate, which illustrates the tradeoff between the
sum rate and maximum number of admitted users.
Chapter 3 addresses the PA problem for a general multi-cluster multi-user MIMONOMA
system to maximize the system energy efficiency (EE). First, a closed-form solution
is derived for the corresponding sum rate (SE) maximization problem. Then, the EE
maximization problem is solved by applying non-convex fractional programming.
Chapter 4 investigates the energy-efficient joint user-RB association and PA problem
for an uplink hybrid NOMA-OMA system. The considered problem requires to jointly
optimize the user clustering, channel assignment and power allocation. To address this
hard problem, a many-to-one bipartite graph is first constructed considering the users
and RBs as the two sets of nodes. Based on swap matching, a joint user-RB association
and power allocation scheme is proposed, which converges within a limited number of
iterations. Moreover, for the power allocation under a given user-RB association, a low complexity
optimal PA algorithm is proposed.
Furthermore, Chapter 5 focuses on securing the confidential information of massive
MIMO-NOMA networks by exploiting artificial noise (AN). An uplink training scheme is
first proposed, and on this basis, the base station precodes the confidential information
and injects the AN. Following this, the ergodic secrecy rate is derived for downlink transmission.
Additionally, PA algorithms are proposed to maximize the SE and EE of the
system.
Finally, conclusions are drawn and possible extensions to resource allocation in NOMA
systems are discussed in Chapter 6
A survey of symbiotic radio: Methodologies, applications, and future directions
The sixth generation (6G) wireless technology aims to achieve global connectivity with environmentally sustainable networks to improve the overall quality of life. The driving force behind these networks is the rapid evolution of the Internet of Things (IoT), which has led to a proliferation of wireless applications across various domains through the massive deployment of IoT devices. The major challenge is to support these devices with limited radio spectrum and energy-efficient communication. Symbiotic radio (SRad) technology is a promising solution that enables cooperative resource-sharing among radio systems through symbiotic relationships. By fostering mutualistic and competitive resource sharing, SRad technology enables the achievement of both common and individual objectives among the different systems. It is a cutting-edge approach that allows for the creation of new paradigms and efficient resource sharing and management. In this article, we present a detailed survey of SRad with the goal of offering valuable insights for future research and applications. To achieve this, we delve into the fundamental concepts of SRad technology, including radio symbiosis and its symbiotic relationships for coexistence and resource sharing among radio systems. We then review the state-of-the-art methodologies in-depth and introduce potential applications. Finally, we identify and discuss the open challenges and future research directions in this field
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