In this paper, we study simultaneous wireless information and power transfer (SWIPT) in orthogonal frequency division multiple access (OFDMA) systems with the coexistence of information receivers (IRs) and energy receivers (ERs). The IRs are served with best-effort secrecy data and the ERs harvest energy with minimum required harvested power. To enhance the physical layer security for IRs and yet satisfy energy harvesting requirements for ERs, we propose a new frequency-domain artificial noise (AN) aided transmission strategy. With the new strategy, we study the optimal resource allocation for the weighted sum secrecy rate maximization for IRs by power and subcarrier allocation at the transmitter. The studied problem is shown to be a mixed integer programming problem and thus nonconvex, while we propose an efficient algorithm for solving it based on the Lagrange duality method. To further reduce the computational complexity, we also propose a suboptimal algorithm of lower complexity. The simulation results illustrate the effectiveness of proposed algorithms as compared against other heuristic schemes.
In this paper, we study simultaneous wireless information and power transfer (SWIPT) in orthogonal frequency division multiple access (OFDMA) systems with the coexistence of information receivers (IRs) and energy receivers (ERs). The IRs are served with best-effort secrecy data and the ERs harvest energy with minimum required harvested power. To enhance the physical layer security for IRs and yet satisfy energy harvesting requirements for ERs, we propose a new frequency-domain artificial noise (AN) aided transmission strategy. With the new strategy, we study the optimal resource allocation for the weighted sum secrecy rate maximization for IRs by power and subcarrier allocation at the transmitter. The studied problem is shown to be a mixed integer programming problem and thus nonconvex, while we propose an efficient algorithm for solving it based on the Lagrange duality method. To further reduce the computational complexity, we also propose a suboptimal algorithm of lower complexity. The simulation results illustrate the effectiveness of proposed algorithms as compared against other heuristic schemes.
Simultaneous wireless information and power transfer (SWIPT) has recently drawn significant interests for its dual use of radio signals to provide wireless data and energy access at the same time. However, a challenging secrecy communication problem arises in the SWIPT system since the messages sent to information receivers (IRs) may be eavesdropped by energy receivers (ERs), which are presumed to receive energy from the same signals broadcast by the transmitter. To tackle this problem, we propose in this paper an artificial noise (AN) aided transmission scheme to facilitate the secrecy information transmission to IRs and yet meet the energy harvesting requirement for ERs, under the assumption that the AN can be cancelled at IRs but not at ERs. Specifically, the proposed scheme splits the power at the transmitter into two parts, to send the confidential message to the IR and an AN to interfere with the ER against eavesdropping, respectively. Under a simplified three-node wiretap channel setup, the transmit power allocations and power splitting ratios over fading channels are jointly optimized to maximize the average secrecy information rate for the IR subject to a combination of average and peak power constraints at the transmitter as well as an average energy harvesting constraint at the ER. The formulated problem is shown to be non-convex, for which we propose an efficient algorithm by iteratively optimizing the transmit power allocations and power splitting ratios over fading channels. Finally, the performance of the proposed scheme is evaluated by simulations and compared against other heuristic schemes in terms of achievable (secrecy) rate-energy trade-off.
Simultaneous wireless information and power transfer (SWIPT) has recently drawn significant interest for its dual use of radio signals to provide wireless data and energy access at the same time. However, a challenging secrecy communication issue arises as the messages sent to the information receivers (IRs) may be eavesdropped upon by energy receivers (ERs), which are presumed to harvest energy only from received signals. To tackle this problem, we propose in this paper an artificial-noise (AN)-aided transmission scheme to facilitate the secrecy information transmission to IRs and, yet, meet the energy harvesting requirement for ERs, under the assumption that the AN can be canceled at IRs but not at ERs. Specifically, the proposed scheme splits the transmit power into two parts: to send the confidential message to the IR and an AN to interfere with the ER, respectively. Under a simplified three-node wiretap channel setup, the transmit power allocations and power splitting ratios over fading channels are jointly optimized to minimize the outage probability for delay-limited secrecy information transmission or to maximize the average rate for no-delay-limited secrecy information transmission, subject to a combination of average and peak power constraints (APC and PPC) at the transmitter (Tx) and an average energy harvesting constraint at the ER. Both the secrecy outage probability minimization and average rate maximization problems are shown to be nonconvex, and for each, we propose the optimal solution based on the dual decomposition and the suboptimal solution based on the alternating optimization. Furthermore, two benchmark schemes are introduced for comparison where the AN is not used at the Tx and where the AN is used but cannot be canceled by the IR, respectively. Finally, the performances of proposed schemes are evaluated by simulations in terms of various tradeoffs for wireless (secrecy) information versus energy transmissions.
PHY-layer security is one of promising techniques for enhanced security and privacy protection in 5G communications. In this paper, the joint resource allocation and artificial noise (AN) design problem of multiuser wiretap orthogonal frequency-division multiplexing (OFDM) systems is investigated to improve the system secrecy rate and power efficiency, which can help to provide waveform design references for secure 5G communications. In such a multiuser wiretap OFDM system, one legitimate transmitter (Alice), multiple legitimate receivers (Bobs), and one eavesdropper (Eve) are simultaneously considered. The time-domain artificial noise is firstly involved to guarantee the target secrecy rates of multiple Bobs. Then a sum secrecy rate maximization problem with nonconvex integer nonlinear programming is formulated to jointly optimize the power, subcarrier allocation and AN design. To solve this tough problem with low computational complexity, a heuristical sub-optimal subcarrier allocation method is proposed, followed by the Lagrange dual method based joint power allocation and AN design scheme. Moreover, considering that sum secrecy rate maximization may result in unfairness for Bobs with bad channel gains, the transmit power minimization problem that ensures a target secrecy rate for each individual Bob is further addressed. An iterative algorithm is proposed to solve this power minimization problem by updating the subcarrier, power allocation and AN design alternatively. Numerical results demonstrate the effectiveness of the proposed algorithms.
This paper investigates the secrecy energy efficiency maximization (SEEM) problem in a simultaneous wireless information and power transfer (SWIPT) system, wherein a legitimate user (LU) exploits the power splitting (PS) scheme for simultaneous information decoding (ID) and energy harvesting (EH). To prevent interference from eavesdroppers on the LU, artificial noise (AN) is incorporated into the confidential signal at the transmitter. We maximize the secrecy energy efficiency (SEE) by joining the power of the confidential signal, the AN power, and the PS ratio, while taking into account the minimum secrecy rate requirement of the LU, the required minimum harvested energy, the allowed maximum radio frequency transmission power, and the PS ratio. The formulated SEEM problem involves nonconvex fractional programming and is generally intractable. Our solution is Lagrangian relaxation method than can transform the original problem into a two-layer optimization problem. The outer layer problem is a single variable optimization problem with a Lagrange multiplier, which can be solved easily. Meanwhile, the inner layer one is fractional programming, which can be transformed into a subtractive form solved using the Dinkelbach method. A closed-form solution is derived for the power of the confidential signal. Simulation results verify the efficiency of the proposed SEEM algorithm and prove that AN-aided design is an effective method for improving system SEE.
This paper studies the secure transmission issue for simultaneous wireless information and power transfer (SWIPT) in a multiuser system with multiple eavesdroppers, where the base station transmitter broadcasts confidential message to legitimate multiple single-antenna information receivers (IRs) and multiple single-antenna energy-harvesting receivers (ERs). Our objective is to optimize the information bearing beam and artificial energy-carrying noise beam in order to maximize the secrecy rate of the IRs subject to individual harvested energy constraints of the ERs for the case where the ERs can form eavesdropping party to carry out joint decoding in an attempt to illicitly decode the secret message intended for the IRs. The initial non-convex problem is converted to convex problem through semi-definite programming (SDP) relaxation for both perfect CSI and imperfect CSI. Numerical simulations are presented to demonstrate the performance.
In this paper, we study a multi-user multiple-inputmultiple- output secrecy simultaneous wireless information and power transfer (SWIPT) channel which consists of one transmitter, one cooperative jammer (CJ), multiple energy receivers (potential eavesdroppers, ERs), and multiple co-located receivers (CRs). We exploit the dual of artificial noise (AN) generation for facilitating efficient wireless energy transfer and secure transmission. Our aim is to maximize the minimum harvested energy among ERs and CRs subject to secrecy rate constraints for each CR and total transmit power constraint. By incorporating norm-bounded channel uncertainty model, we propose a iterative algorithm based on sequential parametric convex approximation to find a near-optimal solution. Finally, simulation results are presented to validate the performance of the proposed algorithm outperforms that of the conventional AN-aided scheme and CJaided scheme.