224 research outputs found
Max-min Fair Beamforming for SWIPT Systems with Non-linear EH Model
We study the beamforming design for multiuser systems with simultaneous
wireless information and power transfer (SWIPT). Employing a practical
non-linear energy harvesting (EH) model, the design is formulated as a
non-convex optimization problem for the maximization of the minimum harvested
power across several energy harvesting receivers. The proposed problem
formulation takes into account imperfect channel state information (CSI) and a
minimum required signal-to-interference-plus-noise ratio (SINR). The globally
optimal solution of the design problem is obtained via the semidefinite
programming (SDP) relaxation approach. Interestingly, we can show that at most
one dedicated energy beam is needed to achieve optimality. Numerical results
demonstrate that with the proposed design a significant performance gain and
improved fairness can be provided to the users compared to two baseline
schemes.Comment: Invited paper, IEEE VTC 2017, Fall, Toronto, Canad
Beamforming and Power Splitting Designs for AN-aided Secure Multi-user MIMO SWIPT Systems
In this paper, an energy harvesting scheme for a multi-user
multiple-input-multiple-output (MIMO) secrecy channel with artificial noise
(AN) transmission is investigated. Joint optimization of the transmit
beamforming matrix, the AN covariance matrix, and the power splitting ratio is
conducted to minimize the transmit power under the target secrecy rate, the
total transmit power, and the harvested energy constraints. The original
problem is shown to be non-convex, which is tackled by a two-layer
decomposition approach. The inner layer problem is solved through semi-definite
relaxation, and the outer problem, on the other hand, is shown to be a single-
variable optimization that can be solved by one-dimensional (1- D) line search.
To reduce computational complexity, a sequential parametric convex
approximation (SPCA) method is proposed to find a near-optimal solution. The
work is then extended to the imperfect channel state information case with
norm-bounded channel errors. Furthermore, tightness of the relaxation for the
proposed schemes are validated by showing that the optimal solution of the
relaxed problem is rank-one. Simulation results demonstrate that the proposed
SPCA method achieves the same performance as the scheme based on 1-D but with
much lower complexity.Comment: 12 pages, 6 figures, submitted for possible publicatio
Transmitter Optimization Techniques for Physical Layer Security
Information security is one of the most critical issues in wireless networks as the signals transmitted through wireless medium are more vulnerable for interception. Although the existing conventional security techniques are proven to be safe, the broadcast nature of wireless communications introduces different challenges in terms of key exchange and distributions. As a result, information theoretic physical layer security has been proposed to complement the conventional security techniques for enhancing security in wireless transmissions. On the other hand, the rapid growth of data rates introduces different challenges on power limited mobile devices in terms of energy requirements. Recently, research work on wireless power transfer claimed that it has been considered as a potential technique to extend the battery lifetime of wireless networks. However, the algorithms developed based on the conventional optimization approaches often require iterative techniques, which poses challenges for real-time processing. To meet the demanding requirements of future ultra-low latency and reliable networks, neural network (NN) based approach can be employed to determine the resource allocations in wireless communications.
This thesis developed different transmission strategies for secure transmission in wireless communications. Firstly, transmitter designs are focused in a multiple-input single-output simultaneous wireless information and power transfer system with unknown eavesdroppers. To improve the performance of physical layer security and the harvested energy, artificial noise is incorporated into the network to mask the secret information between the legitimate terminals. Then, different secrecy energy efficiency designs are considered for a MISO underlay cognitive radio network, in the presence of an energy harvesting receiver. In particular, these designs are developed with different channel state information assumptions at the transmitter. Finally, two different power allocation designs are investigated for a cognitive radio network to maximize the secrecy rate of the secondary receiver: conventional convex optimization framework and NN based algorithm
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