4,379 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
Secure Communications in Millimeter Wave Ad Hoc Networks
Wireless networks with directional antennas, like millimeter wave (mmWave)
networks, have enhanced security. For a large-scale mmWave ad hoc network in
which eavesdroppers are randomly located, however, eavesdroppers can still
intercept the confidential messages, since they may reside in the signal beam.
This paper explores the potential of physical layer security in mmWave ad hoc
networks. Specifically, we characterize the impact of mmWave channel
characteristics, random blockages, and antenna gains on the secrecy
performance. For the special case of uniform linear array (ULA), a tractable
approach is proposed to evaluate the average achievable secrecy rate. We also
characterize the impact of artificial noise in such networks. Our results
reveal that in the low transmit powerregime, the use of low mmWave frequency
achieves better secrecy performance, and when increasing transmit power, a
transition from low mmWave frequency to high mmWave frequency is demanded for
obtaining a higher secrecy rate. More antennas at the transmitting nodes are
needed to decrease the antenna gain obtained by the eavesdroppers when using
ULA. Eavesdroppers can intercept more information by using a wide beam pattern.
Furthermore, the use of artificial noise may be ineffective for enhancing the
secrecy rate.Comment: Accepted by IEEE Transactions on Wireless Communication
UAV Swarm-Enabled Aerial CoMP: A Physical Layer Security Perspective
Unlike aerial base station enabled by a single unmanned aerial vehicle (UAV),
aerial coordinated multiple points (CoMP) can be enabled by a UAV swarm. In
this case, the management of multiple UAVs is important. This paper considers
the power allocation strategy for a UAV swarm-enabled aerial network to enhance
the physical layer security of the downlink transmission, where an eavesdropper
moves following the trajectory of the swarm for better eavesdropping. Unlike
existing works, we use only the large-scale channel state information (CSI) and
maximize the secrecy throughput in a whole-trajectory-oriented manner. The
overall transmission energy constraint on each UAV and the total transmission
duration for all the legitimate users are considered. The non-convexity of the
formulated problem is solved by using max-min optimization with iteration. Both
the transmission power of desired signals and artificial noise (AN) are derived
iteratively. Simulation results are presented to validate the effectiveness of
our proposed power allocation algorithm and to show the advantage of aerial
CoMP by using only the large-scale CSI
Thirty Years of Machine Learning: The Road to Pareto-Optimal Wireless Networks
Future wireless networks have a substantial potential in terms of supporting
a broad range of complex compelling applications both in military and civilian
fields, where the users are able to enjoy high-rate, low-latency, low-cost and
reliable information services. Achieving this ambitious goal requires new radio
techniques for adaptive learning and intelligent decision making because of the
complex heterogeneous nature of the network structures and wireless services.
Machine learning (ML) algorithms have great success in supporting big data
analytics, efficient parameter estimation and interactive decision making.
Hence, in this article, we review the thirty-year history of ML by elaborating
on supervised learning, unsupervised learning, reinforcement learning and deep
learning. Furthermore, we investigate their employment in the compelling
applications of wireless networks, including heterogeneous networks (HetNets),
cognitive radios (CR), Internet of things (IoT), machine to machine networks
(M2M), and so on. This article aims for assisting the readers in clarifying the
motivation and methodology of the various ML algorithms, so as to invoke them
for hitherto unexplored services as well as scenarios of future wireless
networks.Comment: 46 pages, 22 fig
Safeguarding Massive MIMO Aided HetNets Using Physical Layer Security
This paper exploits the potential of physical layer security in massive
multiple-input multiple-output (MIMO) aided two-tier heterogeneous networks
(HetNets). We focus on the downlink secure transmission in the presence of
multiple eavesdroppers. We first address the impact of massive MIMO on the
maximum receive power based user association. We then derive the tractable
upper bound expressions for the secrecy outage probability of a HetNets user.We
show that the implementation of massive MIMO significantly improves the secrecy
performance, which indicates that physical layer security could be a promising
solution for safeguarding massive MIMO HetNets. Furthermore, we show that the
secrecy outage probability of HetNets user first degrades and then improves
with increasing the density of PBSs
- …