733 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
Reconfigurable Intelligent Surfaces for Energy Efficiency in Wireless Communication
The adoption of a Reconfigurable Intelligent Surface (RIS) for downlink
multi-user communication from a multi-antenna base station is investigated in
this paper. We develop energy-efficient designs for both the transmit power
allocation and the phase shifts of the surface reflecting elements, subject to
individual link budget guarantees for the mobile users. This leads to
non-convex design optimization problems for which to tackle we propose two
computationally affordable approaches, capitalizing on alternating
maximization, gradient descent search, and sequential fractional programming.
Specifically, one algorithm employs gradient descent for obtaining the RIS
phase coefficients, and fractional programming for optimal transmit power
allocation. Instead, the second algorithm employs sequential fractional
programming for the optimization of the RIS phase shifts. In addition, a
realistic power consumption model for RIS-based systems is presented, and the
performance of the proposed methods is analyzed in a realistic outdoor
environment. In particular, our results show that the proposed RIS-based
resource allocation methods are able to provide up to higher energy
efficiency, in comparison with the use of regular multi-antenna
amplify-and-forward relaying.Comment: Accepted by IEEE TWC; additional materials on the topic are included
in the 2018 conference publications at ICASSP
(https://ieeexplore.ieee.org/abstract/document/8461496) and GLOBECOM 2018
(arXiv:1809.05397
Energy Efficient Massive MIMO and Beamforming for 5G Communications
Massive multiple-input multiple-output (MIMO) has been a key technique
in the next generation of wireless communications for its potential to achieve
higher capacity and data rates. However, the exponential growth of data
traffic has led to a significant increase in the power consumption and system
complexity. Therefore, we propose and study wireless technologies to improve the trade-off between system performance and power consumption of wireless communications.
This Thesis firstly proposes a strategy with partial channel state information
(CSI) acquisition to reduce the power consumption and hardware complexity of massive MIMO base stations. In this context, the employment of partial CSI is proposed in correlated communication channels with user mobility. By exploiting both the spatial correlation and temporal correlation of the channel, our analytical results demonstrate significant gains in the energy efficiency of the massive MIMO base station.
Moreover, relay-aided communications have experienced raising interest; especially, two-way relaying systems can improve spectral efficiency with short required operating time. Therefore, this Thesis focuses on an uncorrelated massive MIMO two-way relaying system and studies power
scaling laws to investigate how the transmit powers can be scaled to improve the energy efficiency up to several times the energy efficiency without power scaling while approximately maintaining the system performance.
In a similar line, large antenna arrays deployed at the space-constrained relay would give rise to the spatial correlation. For this reason, this Thesis presents an incomplete CSI scheme to evaluate the trade-off between the spatial correlation and system performance. In addition, the advantages of linear processing methods and the effects of channel aging are investigated to further improve the relay-aided system performance.
Similarly, large antenna arrays are required in millimeter-wave communications to achieve narrow beams with higher power gain. This poses the problem that locating the best beam direction requires high power and complexity consumption. Therefore, this Thesis presents several low-complexity beam alignment methods with respect to the state-of-the-art to evaluate the trade-off between complexity and system performance.
Overall, extensive analytical and numerical results show an improved performance and validate the effectiveness of the proposed techniques
Multipair Relaying With Space-Constrained Large-Scale MIMO Arrays: Spectral and Energy Efficiency Analysis With Incomplete CSI
In this paper, we study a multi-pair two-way large-scale multiple-input multiple-output (MIMO) decode-and-forward relay system. Multiple single-antenna user pairs exchange information via a shared relay working at half-duplex. The proposed scenario considers a practical case where an increasing number of antennas is deployed in a fixed physical space, giving rise to a trade-off between antenna gain and spatial correlation. The channel is assumed imperfectly known, and the relay employs linear processing methods. We study the large-scale approximations of the sum spectral efficiency (SE) and investigate the energy efficiency (EE) with a practical power consumption model when the number of relay antennas becomes large. We demonstrate the impact of the relay antenna number and spatial correlation with reducing inter-antenna distance on the EE performance. We exploit the increasing spatial correlation to allow an incomplete channel state information (CSI) acquisition where explicit CSI is acquired only for a subset of antennas. Our analytical derivations and numerical results show that applying the incomplete CSI strategy in the proposed system can improve the EE against complete CSI systems while maintaining the average SE performance
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