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

By Derrick Wing Kwan Ng, Ernest S. Lo, Robert Schober. IEEE Transactions on Wireless Communications, 2013

571 citations recorded by the source corpus.

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. Besides, the problem formulation also takes into account different quality of service (QoS) requirements: a minimum required signal-to-interference-plus-noise ratio (SINR) at the desired receiver; maximum tolerable SINRs at the potential eavesdroppers; a minimum required outage probability at the passive eavesdroppers; and minimum required heterogeneous amounts of power transferred to the idle legitimate receivers. 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 the close-to-optimal performance of the proposed schemes and significant transmit power savings by optimization of the artificial noise and energy signal generation.

Subfields: Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/6fa946f867a6e70bb6e1599b7ae165d556bf3952

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Citations in the corpus

Communications and Signals Design for Wireless Power Transmission (2016, background): “Another interesting application in SWIPT systems is to utilize the energy signals as artificial noise to protect the messages for the information receivers from being eavesdropped by the non-intended energy receivers [197], [198].”
Massive Access for 5G and Beyond (2020, background): “To overcome this problem, the concept of energy beamforming was introduced for wireless energy transfer [177], [178].”
Simultaneous wireless information and power transfer in modern communication systems (2014, background): “Besides, opportunistic power control can be used to exploit the channel fading for improved energy and information transfer efﬁciency [10]–[12].”
Security for 5G and Beyond (2019, methodology): “Currently various methods are used to protect the information from eavesdropping, however using the strength of MIMO to securely perform other tasks, for example wireless power transfer [397], constitute interesting future research.”
Practical Non-Linear Energy Harvesting Model and Resource Allocation for SWIPT Systems (2015, methodology): “Remark 2: The signal model adopted in this letter can be extended to include dedicated energy beams for the ERs by following a similar approach as in [13].”
Simultaneous Wireless Information and Power Transfer (SWIPT): Recent Advances and Future Challenges (2018, unknown): “Afterwards, both power streams are sent to an information decoder and energy harvester to make possible simultaneous ID and EH [59], [60].”
Wireless Networks With RF Energy Harvesting: A Contemporary Survey (2014, background): “Although some of the above works such as [184], [185] design secure transmit beamforming based on rank-one semidefi-”
Fundamentals of Wireless Information and Power Transfer: From RF Energy Harvester Models to Signal and System Designs (2018, background): “Moreover, the linear beamforming design for achieving the optimal tradeoff between the secrecy rate of the IRs and energy harvested by the ERs is studied in [102] and [103], in which the ERs are treated as potential eavesdroppers.”
Robust Resource Allocation for MIMO Wireless Powered Communication Networks Based on a Non-Linear EH Model (2016, methodology): “We assume that each wireless powered user is equipped with a rechargeable battery which has a sufficiently large capacity to store the amount of energy harvested during the WET period [10], [14], [15].”