[Paper Review] Secure SWIPT Networks Based on a Non-linear Energy Harvesting Model

Elena Boshkovska, Nikola Zlatanov+3 more|arXiv (Cornell University)|Jan 26, 2017

Energy Harvesting in Wireless Networks13 references4 citations

TL;DR

This paper proposes a novel resource allocation framework for secure SWIPT networks using a non-linear energy harvesting (EH) model, optimizing transmit beamforming and artificial noise covariance to maximize harvested power while ensuring secrecy. The method transforms the non-convex sum-of-ratios problem into a parametric subtractive form and solves it via iterative semidefinite programming (SDP) relaxation, achieving globally optimal rank-one beamforming and outperforming linear EH-based designs in energy harvesting and security.

ABSTRACT

We optimize resource allocation to enable communication security in simultaneous wireless information and power transfer (SWIPT) for internet-of-things (IoT) networks. The resource allocation algorithm design is formulated as a non-convex optimization problem. We aim at maximizing the total harvested power at energy harvesting (EH) receivers via the joint optimization of transmit beamforming vectors and the covariance matrix of the artificial noise injected to facilitate secrecy provisioning. The proposed problem formulation takes into account the non-linearity of energy harvesting circuits and the quality of service requirements for secure communication. To obtain a globally optimal solution of the resource allocation problem, we first transform the resulting non-convex sum-of-ratios objective function into an equivalent objective function in parametric subtractive form, which facilitates the design of a novel iterative resource allocation algorithm. In each iteration, the semidefinite programming (SDP) relaxation approach is adopted to solve a rank-constrained optimization problem optimally. Numerical results reveal that the proposed algorithm can guarantee communication security and provide a significant performance gain in terms of the harvested energy compared to existing designs which are based on the traditional linear EH model.

Motivation & Objective

• To address the limitations of linear energy harvesting models in SWIPT systems, which fail to reflect real-world circuit non-linearities.
• To jointly optimize transmit beamforming and artificial noise covariance to maximize total harvested energy at EH receivers.
• To ensure secure communication by guaranteeing quality-of-service constraints under physical-layer security.
• To develop a globally optimal solution for a non-convex resource allocation problem under non-linear EH constraints.
• To demonstrate performance gains in energy harvesting and secrecy over conventional linear EH-based designs.

Proposed method

• Formulates the resource allocation problem as a non-convex sum-of-ratios optimization with non-linear EH constraints.
• Transforms the non-convex objective into an equivalent parametric subtractive form to enable iterative optimization.
• Uses semidefinite programming (SDP) relaxation to solve the rank-constrained subproblems in each iteration.
• Applies Karush-Kuhn-Tucker (KKT) conditions to prove that the optimal beamforming matrix is rank-one, ensuring practical implementation.
• Integrates artificial noise injection to degrade eavesdropper channels while maximizing legitimate user energy harvesting.
• Employs a bisection-based algorithm to solve the parametric problem, iteratively refining the solution until convergence.

Experimental results

Research questions

• RQ1 How does the non-linear energy harvesting model affect the design of secure SWIPT systems compared to linear models?
• RQ2 Can a globally optimal solution be achieved for the non-convex resource allocation problem in secure SWIPT with non-linear EH?
• RQ3 What is the impact of artificial noise and beamforming design on both secrecy and energy harvesting performance?
• RQ4 How does the proposed algorithm compare to existing linear EH-based designs in terms of harvested energy and security?
• RQ5 Under what conditions does the optimal beamforming solution remain rank-one, enabling practical implementation?

Key findings

• The proposed algorithm achieves globally optimal resource allocation by transforming the non-convex sum-of-ratios problem into a parametric subtractive form.
• The optimal beamforming matrix is proven to be rank-one, enabling practical transmission with a single data stream.
• The algorithm guarantees communication security by satisfying secrecy rate constraints under artificial noise injection.
• Numerical results show a significant performance gain in harvested energy compared to linear EH-based designs.
• The method outperforms existing schemes in both energy harvesting efficiency and secrecy provisioning under realistic non-linear EH circuit models.
• The iterative SDP-based approach converges to a solution that maximizes total harvested power while maintaining QoS and secrecy requirements.