Robust Beamforming for Secure Communication in Systems with Wireless Information and Power Transfer (1311.2507v2)

Abstract: This paper considers a multiuser multiple-input single-output (MISO) downlink system with simultaneous wireless information and power transfer. In particular, we focus on secure communication in the presence of passive eavesdroppers and potential eavesdroppers (idle legitimate receivers). We study the design of a resource allocation algorithm minimizing the total transmit power for the case when the legitimate receivers are able to harvest energy from radio frequency signals. Our design advocates the dual use of both artificial noise and energy signals in providing secure communication and facilitating efficient wireless energy transfer. The algorithm design is formulated as a non-convex optimization problem. The problem formulation takes into account artificial noise and energy signal generation for protecting the transmitted information against both considered types of eavesdroppers when imperfect channel state information (CSI) of the potential eavesdroppers and no CSI of the passive eavesdroppers are available at the transmitter. In light of the intractability of the problem, we reformulate the considered problem by replacing a non-convex probabilistic constraint with a convex deterministic constraint. Then, a semi-definite programming (SDP) relaxation approach is adopted to obtain the optimal solution for the reformulated problem. Furthermore, we propose a suboptimal resource allocation scheme with low computational complexity for providing communication secrecy and facilitating efficient energy transfer. Simulation results demonstrate a close-to-optimal performance achieved by the proposed schemes and significant transmit power savings by optimization of the artificial noise and energy signal generation.

• The paper introduces a robust framework that minimizes transmit power while ensuring secure communication and effective SWIPT performance.
• It employs a semi-definite programming relaxation to transform non-convex constraints into tractable convex ones under imperfect CSI conditions.
• Numerical results reveal significant power savings and improved secrecy compared to traditional baseline methods.

Robust Beamforming for Secure Communication in Systems with Wireless Information and Power Transfer

This paper investigates the intricacies of designing a resource allocation algorithm for robust beamforming in multiuser MISO systems, where secure communication is imperative alongside simultaneous wireless information and power transfer (SWIPT). It specifically targets scenarios involving passive eavesdroppers and idle legitimate receivers that double as potential eavesdroppers. This research integrates advanced methodologies to optimize the dual objective of secure communication and efficient energy harvesting.

Methodology and Problem Formulation

The authors propose a robust framework for SWIPT systems, considering the unpredictability of channel state information (CSI) for eavesdroppers. The system models a transmitter with multiple antennas servicing multiple single-antenna users, considering an environment where eavesdropping threats are constant.

The resource allocation is presented as a non-convex optimization problem with the goal of minimizing total transmit power while ensuring Quality of Service (QoS) in terms of SINR for all users and a targeted outage probability for passive eavesdroppers. This necessitates an innovative utilization of both artificial noise and energy signals.

To overcome the intractability of directly solving the original problem, the authors reformulate it using a semi-definite programming (SDP) relaxation technique. They replace the non-convex probabilistic constraint associated with the eavesdroppers’ interception probability with a convex deterministic constraint. This approach allows for solving the relaxed problem more efficiently while maintaining robust optimization.

Numerical Results and Insights

The numerical simulations presented provide substantial evidence for the efficacy of the proposed algorithms. The authors leverage SDP-based methods to allocate resources that adeptly balance between transmitting power and ensuring security even when the channel estimations are imperfect.

Results indicate notable power savings when comparing the proposed optimal and suboptimal schemes against traditional baseline approaches. For instance, the proposed SDP algorithm consistently shows reduced power requirements while fulfilling secrecy and power transfer constraints often unmet by baseline methods.

Discussion on Implications and Future Research

From a practical perspective, the paper advances the understanding of secure beamforming in SWIPT systems, contributing to energy-efficient communication strategies applicable in environments sensitive to power and security constraints. The proposed algorithms substantiate a feasible path for deploying SWIPT in future wireless networks, potentially catalyzing innovations in mobile and IoT applications where energy harvesting and secure data transfer are critical.

Theoretically, the research introduces novel constraint handling techniques, opening avenues for further exploration of robust optimization in other communication models where uncertainties and constraints are prevalent. Future research could explore the applicability of these methodologies to more intricate systems involving multiple eavesdroppers with varied capabilities or enhanced secrecy requirements.

Conclusion

This paper represents a significant contribution to secure communication in energy-harvesting-based wireless systems. By elegantly integrating artificial noise and energy signals, the authors present a sophisticated approach to addressing the dual task of secure communication and efficient power transfer. These insights could be foundational in steering the development of next-generation wireless systems.