The secrecy rate region of wiretap interference channels with a multi-antenna passive eavesdropper is studied under receiver energy harvesting constraints. To stay operational in the network, the legitimate receivers demand energy alongside information, which is fulfilled by power transmission and exploiting a power splitting (PS) receiver. By simultaneous wireless information and power transfer (SWIPT), the amount of leakage to the eavesdropper increases, which in turn reduces the secrecy rates. For this setup, lower-bounds for secure communication rate are derived without imposing any limitation at the eavesdropper processing. These lower-bounds are then compared with the rates achieved by assuming the worst-case linear eavesdropper processing. We show that in certain special cases the worst-case eavesdropper does not enlarge the achievable secure rate region in comparison to the unconstrained eavesdropper case. It turns out that in order to achieve the Pareto boundary of the secrecy rate region, smart tuning of the transmit power and receiver PS coefficient is required. Hence, we propose an efficient algorithm to optimize these parameters jointly in polynomial-time. The secrecy rate region characterization is formulated as a weighted max-min optimization problem. This problem turns out to be a non-convex problem due to the non-convex constrained set. This set is replaced by a convex subset that in consequence leads to an achievable suboptimal solution which is improved iteratively. By solving the problem efficiently, we obtain the amount of rate loss for providing secrecy, meanwhile satisfying the energy demands.
The secrecy rate region of wiretap interference channels with a multi-antenna passive eavesdropper is studied under receiver energy harvesting constraints. To stay operational in the network, the legitimate receivers demand energy alongside information, which is fulfilled by power transmission and exploiting a power splitting (PS) receiver. By simultaneous wireless information and power transfer (SWIPT), the amount of leakage to the eavesdropper increases, which in turn reduces the secrecy rates. For this setup, lower-bounds for secure communication rate are derived without imposing any limitation at the eavesdropper processing. These lower-bounds are then compared with the rates achieved by assuming the worst-case linear eavesdropper processing. We show that in certain special cases the worst-case eavesdropper does not enlarge the achievable secure rate region in comparison to the unconstrained eavesdropper case. It turns out that in order to achieve the Pareto boundary of the secrecy rate region, smart tuning of the transmit power and receiver PS coefficient is required. Hence, we propose an efficient algorithm to optimize these parameters jointly in polynomial-time. The secrecy rate region characterization is formulated as a weighted max-min optimization problem. This problem turns out to be a non-convex problem due to the non-convex constrained set. This set is replaced by a convex subset that in consequence leads to an achievable suboptimal solution which is improved iteratively. By solving the problem efficiently, we obtain the amount of rate loss for providing secrecy, meanwhile satisfying the energy demands.
We study the secrecy rate region of wiretap interference channels with a multi-antenna passive eavesdropper under receiver energy harvesting constraints. To stay operational in the network, the legitimate receivers demand energy alongside information, which is fulfilled by power transmission and exploiting a power splitting (PS) receiver. Simultaneous wireless information and power transfer (SWIPT) results in a reduction in the secrecy rates due to the legitimate receivers PS for simultaneous information detection and energy harvesting. For this setup, lower-bounds for secure communication rate are derived without imposing any limitation on the eavesdropper processing. It turns out that in order to obtain the Pareto boundary of the secrecy rate region, smart tuning of the transmit power and receiver PS coefficient is required. Notice that, granting both, i.e., secrecy in communication as well as enabling energy harvesting, result in shrinkages in the reliable communication rate region, which is captured by this optimal tune. Hence, it is of crucial importance to investigate, which of these two services shrinks the rate region more. Interestingly, we observe that by enabling SWIPT, the convexity of the reliable rate region is preserved. However, granting secrecy for the communication results in a non-convex rate region as the interference power increases.
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.
In this paper, we address the problem of secrecy wireless information and power transfer (SWIPT) over interference channels, where an external eavesdropper is also interested in the transmitted message. Under a practical assumption that only imperfect eavesdropper channel state information (CSI) is available, our objective is to minimize the total transmit power while satisfying the constraints on the minimum amounts of individual harvested energy, the worst-case achievable secrecy rate of the wiretapped node, and the minimum signal-to-interference-plus-noise ratio (SINR) at the wiretap-free node. An optimal robust secure beamforming and power splitting scheme is obtained via the aid of a one-dimensional search. Moreover, in order to reduce the computational complexity, we also propose a suboptimal scheme based on zero-forcing beamforming (ZFB). Finally, simulation results validate the effectiveness of the proposed schemes.
In this paper, we consider a multiuser multiple-input multiple-output (MIMO) downlink communication system with simultaneous wireless information and power transfer (SWIPT). In particular, we focus on a realistic and efficient multi-receiver multi-eavesdropper MIMO SWIPT system, in which the channel state information (CSI) of each legitimate receiver and energy receiver (i.e., potential eavesdropper) is partially known to the transmitter. Based on this, we propose a robust artificial noise (AN)-aided secure transmission scheme for the system, where the channel uncertainties are modeled by the worst-case model. In the proposed scheme, we aim to maximize the worst-case achievable secrecy rate under the transmit power constraint and the energy harvesting (EH) constraint, by jointly optimizing the transmit precoding matrix and the AN covariance matrix. We utilize the S-Procedure and Taylor series approximation to transform the non-convex problem. Then, we apply the interior point method to tackle the transformed convex problem, obtaining the approximate optimal matrices and the corresponding maximum worst-case secrecy rate. Simulation results show that our proposed scheme achieves significant performance improvements in terms of convergence and the worst-case achievable secrecy rate.
This paper considers transmit covariance matrix design for secrecy rate maximization problem in a multiple-input single-output (MISO) multicasting simultaneous wireless information and power transfer (SWIPT) system. In order to enhance the performance of the system, artificial noise (AN) is added to the transmit signal in the design for the following purposes: to reduce the received signal-to-noise ratio (SNR) at the eavesdroppers and increase the harvested energy. We assume that all the channel-state-information (CSI) is perfectly known at the transmitter and all legitimate users are capable of simultaneously receiving information and harvesting energy. In addition, all the eavesdroppers are passive and they can harvest energy only when they are not intercepting or eavesdropping the messages intended for the legitimate users. The original secrecy rate maximization problem is not convex in terms of transmit and artificial covariance matrices as well as the power splitting (PS) ratio. In order to circumvent this non-convexity issue, we exploit the Charnes-Cooper Transformation and semidefinite relaxation (SDR) to convert this original problem into a convex one. However, this convex problem does not always yield the rank-one transmit and AN covariance matrices to obtain the solution of the original problem. Therefore, we analyze the optimal conditions and utilize a Gaussian randomization (GR) method to construct the rank-one solutions from the non-rank one results. Simulation results have been provided to demonstrate the performance of the proposed transmit covariance matrices design for MISO multicasting SWIPT system.
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.