In this paper, we study a multiuser wireless powered communication system, where an energy-constrained full-duplex information transmitter (IT), powered by wireless energy from a dedicated energy transmitter (ET), intends to send confidential information to the information receiver (IR) in the presence of multiple idle users that could be the potential eavesdroppers. In the practical scenario of imperfect channel state information and assuming that the idle users need to harvest energy from the ET, we aim to maximize the worst-case secrecy rate at the IR by jointly optimizing the transmit covariance matrix at the ET as well as the information beamforming and artificial noise covariance at the IT, subject to their individual transmit power constraints and the minimum required power transferred to the idle users. We employ the semidefinite relaxation (SDR) and extended S-procedure approaches to transform the original nonconvex optimization problem into convex problem, which can be efficiently solved by solving a sequence of semidefinite programs. Furthermore, we show that the SDR is tight since there always exists a rank-one optimal solution. For performance comparison, two heuristic schemes for ease of implementation are also developed. Numerical results are presented to show the effectiveness of our proposed schemes.
In this paper, we study a multiuser wireless powered communication system, where an energy-constrained full-duplex information transmitter (IT), powered by wireless energy from a dedicated energy transmitter (ET), intends to send confidential information to the information receiver (IR) in the presence of multiple idle users that could be the potential eavesdroppers. In the practical scenario of imperfect channel state information and assuming that the idle users need to harvest energy from the ET, we aim to maximize the worst-case secrecy rate at the IR by jointly optimizing the transmit covariance matrix at the ET as well as the information beamforming and artificial noise covariance at the IT, subject to their individual transmit power constraints and the minimum required power transferred to the idle users. We employ the semidefinite relaxation (SDR) and extended S-procedure approaches to transform the original nonconvex optimization problem into convex problem, which can be efficiently solved by solving a sequence of semidefinite programs. Furthermore, we show that the SDR is tight since there always exists a rank-one optimal solution. For performance comparison, two heuristic schemes for ease of implementation are also developed. Numerical results are presented to show the effectiveness of our proposed schemes.
This paper investigates a secure wireless-powered integrated service system with full-duplex self-energy recycling. Specifically, an energy-constrained information transmitter (IT), powered by a power station (PS) in a wireless fashion, broadcasts two types of services to all users: a multicast service intended for all users and a confidential unicast service subscribed to by only one user while protecting it from any other unsubscribed users and an eavesdropper. Our goal is to jointly design the optimal input covariance matrices for the energy beamforming, the multicast service, the confidential unicast service, and the artificial noises from the PS and the IT, such that the secrecy-multicast rate region (SMRR) is maximized subject to the transmit power constraints. Due to the non-convexity of the SMRR maximization (SMRRM) problem, we employ a semidefinite programming-based two-level approach to solve this problem and find all of its Pareto optimal points. In addition, we extend the SMRRM problem to the imperfect channel-state information case, where a worst-case SMRRM formulation is investigated. Moreover, we exploit the optimized transmission strategies for the confidential service and energy transfer by analyzing their own rank-one profile. Finally, numerical results are provided to validate our proposed schemes.
This paper considers a multiple-input single-output downlink system consisting of one multiantenna transmitter, one single-antenna information receiver (IR), and multiple single-antenna energy-harvesting receivers (ERs) for simultaneous wireless information and power transfer. The design is to keep the message secret to the ERs while maximizing the information rate at the IR and meeting the energy harvesting constraints at the ERs. Technically, our objective is to optimize the information-bearing beam and artificial noise energy beam for maximizing the secrecy rate of the IR subject to individual harvested energy constraints of the ERs for the case where the ERs can collude to perform joint decoding in an attempt to illicitly decode the secret message to the IR. As a by-product, we also solve the total power minimization problem subject to secrecy rate and energy harvesting constraints. Both scenarios of perfect and imperfect channel state information (CSI) at the transmitter are addressed. For the imperfect CSI case, we study both eavesdroppers' channel covariance-based and worst case-based designs. Using semidefinite relaxation (SDR) techniques, we show that there always exists a rank-one optimal transmit covariance solution for the IR. Furthermore, if the SDR results in a higher rank solution, we propose an efficient algorithm to always construct an equivalent rank-one optimal solution. Computer simulations are carried out to demonstrate the performance of the proposed algorithms.
In this letter, we study a novel multi-antenna wireless powered communication (WPC) system consisting of an energy source (ES), a full-duplex self-energy recycling information source (IS), an information receiver (IR), and an energy receiver (ER) (potential eavesdropper). The energy-constrained IS, powered by ES, sends the confidential information to IR over the wiretap channel. Our goal is to maximize the secrecy rate for IR by jointly optimizing the energy and information beamforming vectors, under the constraints of the transmit power at ES and IS and the harvested energy at ER. To solve the formulated non-convex problem, a partial Lagrange dual method coupled with two-stage optimization method is proposed, which derives the optimal solution in semi-closed form. Numerical results show the superiority of our proposed design compared with the existing schemes.
This paper investigates an energy-constrained relay-assisted secure communication system in the presence of a legitimate source-destination pair and a passive eavesdropper with imperfect channel state information (CSI). The energy-constrained relay exploits a power splitting (PS) protocol to simultaneously harvest energy and decode information from the received signal from the source, and then forwards the confidential signal to the full-duplex (FD) destination while it simultaneously transmits artificial noise (AN) to confuse the passive eavesdropper. This robust beamforming design is developed by maximizing the secrecy rate under the constraints of energy harvesting (EH) requirement at the relay and AN transmit power at the destination. Specifically, we formulate the joint relay beamforming and PS ratio as well as the AN power optimization as a non-convex quadratically-constrained problem. In order to circumvent this non-convexity issue, we decompose the original problem into three subproblems which can be determined by the proposed semidefinite relaxation (SDR) and successive convex optimization methods. Furthermore, we derive closed-form expressions for the optimal solutions of each subproblem. Finally, the original non-convex problem can be solved through a convergence guaranteed iterative algorithm. Simulation results are provided to demonstrate the effectiveness and superior performance of the proposed robust design compared with the benchmark schemes.
This paper studies the secure transmission issue for simultaneous wireless information and power transfer in a multiuser multiple-input-multiple-output system with multiple external eavesdroppers, where the transmitter broadcasts independent confidential messages to different legitimate receivers. Each receiver can be seen as an internal eavesdropper intended by other receivers. Our objective is to achieve the robust beamforming design under imperfect channel state information, in which the total transmission power is minimized with constraints on the achievable secrecy rate and the energy harvesting. Since the problem is nonconvex, we propose a two-level optimization scheme. For the inner problem, we investigate two conservative relaxation approaches, large-deviation inequality and Bernstein-type inequality (BTI), to reformulate the outage secrecy rate constraints into some convex ones, yielding a convex optimization by semidefinite programming (SDP) relaxation. For the outer problem, it is a K-variable optimization problem, which can be solved via the novel line-dimensional-like search method. Moreover, we characterize the rank profile of SDP relaxed solution for these two approaches. Specifically, the optimal solution is proved to be rank-one. Numerical results are provided to verify the performance of the proposed algorithms, where the LDI-based scheme outperforms the BTI-based scheme in terms of energy efficiency.
In this paper, we consider a multiple-input-multiple-output (MIMO) simultaneous wireless information and power transfer (SWIPT) system, which consists of a transmitter, a full-duplex (FD) desired receiver (DR) and multiple energy receivers (ERs), i.e., potential eavesdroppers. The transmitter and DR can send artificial noise (AN) and jamming signals to interfere and carry the energy to the ERs, respectively. Considering the imperfect channel state information (CSI) related to ERs, we aim to maximize the worst-case secrecy rate by jointly optimize the information covariance matrix, AN covariance matrix at the transmitter as well as the jamming covariance matrix at the DR, subject to their individual transmit power constraints and the minimum required power transferred to the ERs. In order to solve this non-convex and semi-infinite problem, we employ the S-procedure and propose a successive convex approximation (SCA) scheme based on Taylor series approximation, which can be efficiently solved by the proposed iterative method. Simulation results are finally presented to show the effectiveness of the new robust secrecy design.