Robust AN-Aided Beamforming and Power Splitting Design for Secure MISO Cognitive Radio With SWIPT (1602.06913v1)

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}\text{-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.

• The paper introduces AN-aided beamforming methods to minimize transmit power while ensuring secure communications and efficient energy harvesting in MISO cognitive radio networks.
• It employs bounded and probabilistic CSI error models using semidefinite relaxation and Bernstein-type inequalities to yield robust and suboptimal solutions respectively.
• The study identifies a critical trade-off between securing the secondary user and maximizing energy harvested by EHRs, providing actionable insights for network design.

Overview of Robust AN-Aided Beamforming and Power Splitting Design for Secure MISO Cognitive Radio Networks

This paper explores the intricate challenges and proposed solutions related to robust beamforming in a multiple-input single-output (MISO) cognitive radio (CR) network framework that integrates simultaneous wireless information and power transfer (SWIPT). The authors address the problem of ensuring robust secure communications and efficient energy harvesting despite the uncertainty in channel state information (CSI). The focus is on minimizing transmit power and optimizing the energy harvested under two CSI error models: bounded and probabilistic.

Problem Formulation and Methodology

The paper considers a MISO CR network where a cognitive base station (CBS) supports a secondary user (SU) coexistently with primary users (PU) and energy harvesting receivers (EHRs). The secure communications are jeopardized due to potentially malicious EHRs and imperfect CSI. Two core optimization problems are investigated:

1. Transmit Power Minimization: The authors aim to minimize the transmit power at the CBS while ensuring secure communications and requisite energy harvesting at the SU and EHRs.
2. Max-Min Fairness Energy Harvesting: This involves optimizing the energy harvested by multiple EHRs under a fairness criterion while maintaining communication secrecy and respecting interference constraints on PUs.

Both problems are framed within the context of AN-aided beamforming, where artificial noise is leveraged to enhance secrecy and energy harvesting capabilities.

Key Contributions

1. Bounded CSI Error Model: The bounded CSI error model is used to encapsulate channel uncertainties. Under this model, the authors propose a one-dimensional search algorithm utilizing semidefinite relaxation (SDR) and the $\mathcal{S}$-procedure. It is demonstrated that the optimal solution for beamforming is always achievable, maintaining a rank one solution for the beamforming matrix and demonstrating the robustness against the worst-case CSI errors.
2. Probabilistic CSI Error Model: The probabilistic approach employs Bernstein-type inequalities to approximate the outage constraints. While this model offers less conservative solutions compared to the bounded model, it can only guarantee suboptimal solutions due to the inherent nature of probabilistic constraints.
3. Trade-off Analysis: An insightful trade-off is identified between securing the communication link of the SU and maximizing energy harvested by the EHRs. This trade-off is significant for network operators aiming to balance the twin objectives of security and efficiency.
4. Complexity Considerations: The paper also meticulously evaluates the computational complexity associated with each of the proposed solutions, providing a thorough analysis of the trade-offs between solution performance and computational overhead.

Implications and Future Directions

Robust beamforming and power splitting for CR networks with SWIPT hold substantial implications for the design of future wireless communication systems, especially those requiring energy-efficient operations coupled with stringent security needs. The quantification of trade-offs between secrecy and harvested energy provides a critical insight into system-level design and operational strategies for next-generation cognitive radio deployments.

Future research can build on this work by exploring more adaptive schemes for CSI error modeling, potentially integrating real-time learning mechanisms to dynamically adjust beamforming strategies. Additionally, experimentation in practical settings can further validate the theoretical insights provided.

In conclusion, this paper offers a detailed and systematic approach to managing the dual objectives of robust communication and efficient energy harvesting in MISO CR networks, laying down groundwork for continued advancements in secure and energy-aware wireless communications.