[Paper Review] Robust AN-Aided Beamforming and Power Splitting Design for Secure MISO Cognitive Radio With SWIPT

Fuhui Zhou, Zan Li+3 more|arXiv (Cornell University)|Feb 22, 2016

Energy Harvesting in Wireless Networks35 references12 citations

TL;DR

This paper proposes a robust artificial noise-aided beamforming and power splitting design for secure MISO cognitive radio networks with simultaneous wireless information and power transfer (SWIPT), under imperfect channel state information (CSI). It formulates transmit power minimization and max-min fairness energy harvesting problems under bounded and probabilistic CSI error models, using S-procedure and Bernstein-type inequalities to derive optimal and suboptimal solutions, respectively, while balancing secrecy rate and energy harvesting performance.

ABSTRACT

A multiple-input single-output cognitive radio downlink network is studied with simultaneous wireless information and power transfer. In this network, a secondary user coexists with multiple primary users and multiple energy harvesting receivers. In order to guarantee secure communication and energy harvesting, the problem of robust secure artificial noise-aided beamforming and power splitting design is investigated under imperfect channel state information (CSI). Specifically, the transmit power minimization problem and the max-min fairness energy harvesting problem are formulated for both the bounded CSI error model and the probabilistic CSI error model. These problems are non-convex and challenging to solve. A one-dimensional search algorithm is proposed to solve these problems based on ${\cal S} ext{-Procedure} $ under the bounded CSI error model and based on Bernstein-type inequalities under the probabilistic CSI error model. It is shown that the optimal robust secure beamforming can be achieved under the bounded CSI error model, whereas a suboptimal beamforming solution can be obtained under the probabilistic CSI error model. A tradeoff is elucidated between the secrecy rate of the secondary user receiver and the energy harvested by the energy harvesting receivers under a max-min fairness criterion.

Motivation & Objective

• To address the challenge of securing secondary user communications in cognitive radio networks with energy-constrained receivers.
• To design robust beamforming and power splitting strategies that ensure secure information transmission and efficient energy harvesting under imperfect CSI.
• To balance the trade-off between secrecy rate for the secondary user and energy harvesting fairness among multiple energy harvesting receivers.
• To formulate and solve non-convex optimization problems under bounded and probabilistic CSI error models.
• To provide optimal and suboptimal solutions using S-procedure and Bernstein-type inequalities, respectively.

Proposed method

• Formulates a transmit power minimization problem and a max-min fairness energy harvesting problem under bounded CSI error model using S-procedure for robustness.
• Applies Bernstein-type inequalities to handle probabilistic CSI error models, enabling tractable solution derivation.
• Uses semidefinite relaxation and duality theory to transform the non-convex problems into solvable forms via Lagrangian dual decomposition.
• Derives necessary conditions using partial KKT conditions and proves that the optimal beamforming solution has rank-one structure under feasible conditions.
• Employs a one-dimensional search algorithm to solve the robust beamforming problems efficiently.
• Integrates artificial noise beamforming to enhance physical-layer secrecy while supporting energy harvesting at multiple receivers.

Experimental results

Research questions

• RQ1 How can robust beamforming be designed to ensure secure communication in MISO cognitive radio networks with SWIPT under bounded CSI errors?
• RQ2 What is the performance trade-off between secrecy rate and energy harvesting fairness under imperfect CSI?
• RQ3 How does the probabilistic CSI error model affect the design of secure beamforming and power splitting in SWIPT-enabled CR systems?
• RQ4 Can the proposed method achieve optimal or suboptimal solutions under different CSI error models?
• RQ5 What is the impact of artificial noise on secrecy rate and energy harvesting efficiency in the presence of multiple energy harvesting receivers?

Key findings

• The proposed method achieves optimal robust secure beamforming under the bounded CSI error model using the S-procedure.
• Under the probabilistic CSI error model, a suboptimal beamforming solution is obtained using Bernstein-type inequalities, ensuring robustness with lower computational complexity.
• A trade-off is explicitly revealed between the secrecy rate of the secondary user and the energy harvested by energy harvesting receivers under a max-min fairness criterion.
• The rank of the beamforming matrix is proven to be one under feasible conditions, enabling efficient implementation of the optimal solution.
• The one-dimensional search algorithm effectively solves the non-convex optimization problems, ensuring convergence to the optimal or suboptimal solution.
• Numerical results confirm that the proposed scheme enhances both secrecy rate and energy harvesting fairness compared to conventional beamforming designs.