Power Allocation for Secure SWIPT Systems With Wireless-Powered Cooperative Jamming

This paper proposes a novel channel estimation method and a cluster-based opportunistic scheduling policy, for a wireless energy transfer (WET) system consisting of multiple low-complex energy receivers (ERs) with limited processing capabilities. Firstly, in the training stage, the energy transmitter (ET) obtains a set of Received Signal Strength Indicator (RSSI) feedback values from all ERs, and these values are used to estimate the channels between the ET and all ERs. Next, based on the channel estimates, the ERs are grouped into clusters, and the cluster that has its members closest to its centroid in phase is selected for dedicated WET. The beamformer that maximizes the minimum harvested energy among all ERs in the selected cluster is found by solving a convex optimization problem. All ERs have the same chance of being selected regardless of their distances from the ET, and hence, this scheduling policy can be considered to be opportunistic as well as fair. It is shown that the proposed method achieves significant performance gains over benchmark schemes.

This paper investigates the robust beamforming design in a secrecy multiple-input single-output (MISO) network aided by the intelligent reflecting surface (IRS) with simultaneous wireless information and power transfer (SWIPT). Specifically, by considering that the energy receivers (ERs) are potential eavesdroppers (Eves) and imperfect channel state information (CSI) of the direct and cascaded channels can be obtained, we investigate the max-min fairness robust secrecy design. The objective is to maximize the minimum robust information rate among the legitimate information receivers (IRs). To solve the formulated non-convex design problem in bounded and probabilistic CSI error models, we utilize the alternating optimization (AO) and successive convex approximation (SCA) methods to obtain an approximate problem. Then, an iteration-based algorithm framework was proposed, where the unit modulus constraint (UMC) of the IRS is handled by the penalty dual decomposition (PDD) method. Moreover, a stochastic SCA method is proposed to handle the outage constrained design with statistical CSI. Finally, simulation results validate the promising performance of the proposed design.

This article addresses the security problem for wireless powered cognitive satellite-terrestrial network, where a multibeam satellite sub-network shares the portion of millimeter wave bands with multiple cellular networks, each consisting of a base station, several mobile users (MUs) and energy receivers (ERs). Considering that the ERs are potential eavesdroppers of the MUs, and only imperfect knowledge of the angles of departure for the wiretap channels is available, we aim at maximizing aggregated rate of the considered network while guaranteeing the signal-to-interference-plus-noise ratio requirements of the MUs, the energy harvesting thresholds and the secrecy constraints at ERs. Since the formulated optimization problem is mathematically intractable, we exploit a discretization method and the Taylor expansion method to transform the non-convex objective and constraints into convex ones, and then propose an iterative beamforming (BF) algorithm to solve the problem. Furthermore, we present a combined multibeam scheme to obtain suboptimal BF weight vectors with low computational burden. Finally, simulation results reveal that the proposed BF schemes can efficiently improve the aggregated rate with fast convergence compared to the benchmark schemes.

This work considers a secure multiple‐input multiple‐output (MIMO) channel where the energy receiver (ER) is a potential eavesdropper (Eve). Specifically, we aim to maximize the secrecy energy efficiency (SEE) via jointly designing the transmit precoding matrix and the artificial noise (AN) covariance at the base station (BS), as well as the power splitting (PS) ratio at the desired receiver (DR), subject to the constraints of the transmit power budget and harvested energy threshold. To handle the formulated highly nonconvex fractional problem, we apply the successive convex approximation (SCA) method to transform the objective and constraint into a tractable form. Then, a penalty‐based iterative algorithm is proposed. Finally, simulation results validate the performance of the proposed design.

This paper investigates the multi-cell coordinated beamforming (MCBF) design for secure simultaneous wireless information and power transfer (SWIPT) in both centralized and distributed manners. In each cell, one transmitter serves multiple information receivers (IRs) and energy receivers (ERs) with the non-linear energy harvesting (EH) model. Meanwhile, several eavesdroppers (Eves) intend to intercept the confidential information transmitted for IRs. To achieve a secure transmission, the artificial noise (AN) is embedded in the transmit signals of each transmitter. The proposed design is formulated into a power-minimization problem to guarantee the IRs’ information and ERs’ energy requirements while avoiding the information being intercepted by Eves. Since the problem is non-convex and not easy to solve, a solution method based on semi-definition relaxation (SDR) is proposed and the global optimum is proved to be guaranteed with full channel state information (CSI). We further present a distributed AN-aided MCBF for the system by using alternating direction method of multipliers (ADMM), with which each transmitter is able to calculate its own beamforming vectors and AN covariance matrix based on its local CSI. Simulation results show that our proposed distributed design converges to the global optimum obtained by the centralized one. It is also shown that by employing AN, the total required power of the system is reduced and the effect of AN on the system performance decreases with increment of transmit antennas. Compared with traditional linear EH model, optimizing the system under the non-linear EH one avoids false output power at the ERs and saves power at the transmitter.

In this paper, we investigate methods for reducing the likelihood that a message transmitted between two multi-antenna nodes is intercepted by an undetected eavesdropper. In particular, we focus on the judicious transmission of artificial interference to mask the desired signal at the time it is broadcast. Unlike previous work that assumes some prior knowledge of the eavesdropper's channel and focuses on maximizing secrecy capacity, we consider the case where no information regarding the eavesdropper is available, and we use signal-to-interference-plus-noise-ratio (SINR) as our performance metric. Specifically, we focus on the problem of maximizing the amount of power available to broadcast a jamming signal intended to hide the desired signal from a potential eavesdropper, while maintaining a prespecified SINR at the desired receiver. The jamming signal is designed to be orthogonal to the information signal when it reaches the desired receiver, assuming both the receiver and the eavesdropper employ optimal beamformers and possess exact channel state information (CSI). In practice, the assumption of perfect CSI at the transmitter is often difficult to justify. Therefore, we also study the resulting performance degradation due to the presence of imperfect CSI, and we present robust beamforming schemes that recover a large fraction of the performance in the perfect CSI case. Numerical simulations verify our analytical performance predictions, and illustrate the benefit of the robust beamforming schemes.

Simultaneous wireless information and power transfer (SWIPT) in radio-frequency (RF) bands enables flexible deployment of battery-powered relays for extending communication coverage. Relays receive downlink RF signals emitted by a source for information decoding and energy harvesting, while the harvested energy is consumed for both information decoding and information forwarding to a destination. An energy harvesting based selective-decode-and-forward (EH-SDF) protocol is proposed, where only the relays having information correctly decoded are activated for information forwarding, while others harvest and store energy for the future use. By considering the channel aging effect, we propose a joint relay selection, power allocation, transmit beamforming and signal splitting design in order to maximise the end-to-end (e2e) throughput of this EH-SDF aided cooperative communication system. Two scenarios with/without direct link between the source and the destination are studied, respectively. The original formulated non-convex optimisation problems with coupled variables are decoupled into three subproblems which are solved by an iterative optimisation algorithm. Numerical results demonstrate that our design with the EH-SDF protocol achieves a higher e2e throughput than the traditional decode-and-forward (DF) counterpart. Moreover, the impact of the channel aging effect on the e2e throughput is also evaluated.

In this article, we investigate the application of user cooperation (UC) and non-orthogonal multiple access (NOMA) schemes for a wireless powered mobile edge computing (MEC) system under the non-linear energy harvesting model, in which two single-antenna mobile users first harvest energy from a multi-antenna access point (AP) integrated with an MEC server. Then, during the computation offloading phase, both mobile users simultaneously offload tasks to the MEC server with the harvested energy, by performing NOMA protocol. To better enhance the system performance, UC scheme is carried out, where the near user acts as a relay to help the far user offload computation tasks to the AP. To obtain energy efficient MEC design, our objective is to maximize the computation efficiency (i.e., the total computation bits divided by the consumed energy) by jointly designing the energy beamforming, time and power allocations, which yields a challenging nonconvex optimization problem. To deal with it, the original problem is first transformed into a more tractable formulation by applying the semidefinite relaxation (SDR) technique and then solved by utilizing the sequential convex approximation (SCA) method. Numerical results demonstrate that UC has a great impact when two users are close, while NOMA makes effect when two users are relatively far. Combining both NOMA and UC, the proposed scheme, named NOMA-UC MEC, yields better system performance than the benchmark schemes.

This paper proposes an secure transmit power allocation (STPA) scheme for a two-way denoise-and-forward (DNF) relaying network with the aim of maximizing the secrecy sum rate of the network. Here, the DNF relay could act not only as a forwarder but also a potential eavesdropper, i.e., an untrusted relay. First, the secure-rate-region of the two sources that their messages can be strictly kept secret is derived from an information theory point of view. On this basis, an optimal power allocation problem subject to an individual peak-power limit is studied, giving closed-form expressions of the individual transmit powers than can maximize the network secrecy sum rate. Computer simulation results show that compared with the conventional equal-power allocation scheme, the proposed STPA scheme is capable of enhancing the secrecy sum rate and reducing the intercept probability simultaneously.

This paper investigates artificial noise injection into the temporal and spatial dimensions of a legitimate wireless communication system to secure its transmissions from potential eavesdropping. We consider a multiple-input single-output (MISO) orthogonal frequency division multiplexing (OFDM) system in the presence of a single-antenna passive eavesdropper and derive both the secrecy rate and average secrecy rate of the legitimate system. It is assumed that the legitimate transmitter knows the full channel information of the legitimate transceivers but does not know the instantaneous channel state information of the passive eavesdropper. Closed-form expressions for the secrecy rate and average secrecy rate are derived for the asymptotic case with a large number of transmit antennas. We also investigate 1) the power allocation between the data and the AN; 2) the power allocation between the spatial and the temporal AN. Computer simulations are carried out to evaluate the performance of our proposed artificial noise scheme.

The inherent broadcast characteristics of wireless medium make wireless data transmission difficult to be shielded from unintended recipients. As such, secure communication over wireless channels becomes a critical issue in the design of wireless networks. In this study, the authors study cooperative jamming and power optimisation in untrusted relay networks to improve physical layer security. By exploiting the direct link, a source‐based jamming (SBJ) scheme is proposed to hinder the untrusted relay from intercepting the confidential message. Considering the total power budget, a power allocation strategy is also proposed to optimally determine the power of source and untrusted relay as well as the power of information and jamming signals. Furthermore, to evaluate the secrecy performance of the proposed SBJ scheme with the power allocation strategy, tight lower bound of ergodic secrecy capacity and asymptotic secrecy outage probability are derived in closed form. Simulation verifies the advantages of the proposed SBJ scheme and the power allocation strategy.

To enhance the secrecy of wireless transmission, we propose a cooperative user relaying NOMA scheme, in which the near user works in full-duplex mode by transmitting jamming signals and receiving desired signals in the first phase, and the base station sends jamming signals in the second phase. Two power allocation (PA) schemes between the legitimate and jamming signals are designed based on different knowledge of the eavesdropping channel state information (ECSI). The first scheme aims to jam the eavesdropping with highest power while meeting rate requirements without ECSI. In the second scheme, the closed-form expressions of secrecy outage probability (SOP) are first derived using the statistical ECSI. Then, the sum secrecy rate is maximized by optimizing the PA and redundant rate with SOP constraints. Simulation results are provided to show the effectiveness of the proposed schemes.

In this article, a classified system with a relay is investigated in wireless body area networks (WBANs), where some on-body sensors are divided into several sensor groups on the basis of different body parts. Not only can the network detect basic vital signs but also the physiological signals of special diseases. All groups of sensors and the relay harvest energy by the radio-frequency (RF) source broadcasting, then the same group of sensors simultaneously sends common information through cooperation to the source. Since the classified system is a confined system, we maximize the system throughput with a joint power allocation on maximum ratio combining (JPA-MRC) protocol, where the transmission power allocation at the relay is unequal for each relaying subslot. The optimal problem is solved by the Lagrange multiplier method and the Karush-Kuhn-Tucker (KKT) optimal conditions. To further the obtain optimal solution, we simplify co-optimization of relay power and sensor power to the optimization of single power by the equivalent channel gains. Analytical and simulation results show that our proposed optimal method can greatly improve the information throughput compared to the conventional mean power allocation method. In addition, the protocol based on the classified scheme outperforms than that of the conventional unclassified scheme. The impacts of various important system parameters are analyzed, which provide useful design insights under different cases.

In this work, we consider a point-to-point communication link where the transmitter has a hybrid supply of energy. Specifically, the hybrid energy is supplied by a constant energy source and an energy harvester, which harvests energy from its surrounding environment and stores it in a battery which suffers from energy leakage. Our goal is to minimize the power consumed by the constant energy source for transmission of a given amount of data in a given number of time intervals. Two scenarios are considered for packet arrival. In the first scenario, we assume that all data packets have arrived before transmission begins, whereas in the second scenario, we assume that data packets are arriving during the course of data transmission. For both scenarios, we propose an optimal offline transmit power allocation scheme which provides insight into how to efficiently consume the energy supplied by the constant energy source and the energy harvester. For offline power allocation, we assume that causal and non-causal information regarding the channel and the amount of harvested energy is available a priori. For optimal online power allocation, we adopt a stochastic dynamic programming (DP) approach for both considered scenarios. For online power allocation, only causal information regarding the channel and the amount of harvested energy is assumed available. Due to the inherent high complexity of DP, we propose suboptimal online algorithms which are appealing because of their low complexity. Simulation results reveal that the offline scheme performs best among all considered schemes and the suboptimal online scheme provides a good performance-complexity tradeoff.

This letter proposes a novel wirelessly-powered full-duplex amplify-and-forward (AF) relaying scheme, where the multi-antenna relay can harvest energy from the source and recycle energy from itself by using antenna switching protocol. Unlike conventional fixed antennas relay that can only harvest and recycle energy at the second transmission phase, in the proposed scheme, the relay can also harvest energy at the first transmission phase with dynamic antenna combination. To maximize the spectral efficiency of the system, the transmit power of the source, the beamforming matrix at the relay and its antenna allocation are jointly optimized. Also, to tackle the discontinuity and nonconvexity of the optimization problem, a semi-analytical iterative algorithm is developed. In particular, for a fixed antenna combination at the relay, a closed-form solution to the source power allocation and the beamforming matrix at the relay are derived. Then, a greedy antenna switching algorithm is designed to obtain the best antenna combination. Simulation results demonstrate the near optimality of the proposed algorithm and the superiority of the proposed scheme.