Secrecy Energy Efficiency Research Articles

Power Allocation and Equivalent Transmit FDA Beamspace for 5G mmWave NOMA Networks: Meta-Heuristic Optimization Approach

Most of the existing works in millimeter wave (mmWave) and non-orthogonal multiple access (NOMA) communications (mmWave NOMA) employs phased array (PA) antennas which yield only angle beamspace without range dependent, range-interference suppression and “dot-shaped” array resolution. In this paper, we propose a collocated transmitter (Tx) - receiver (Rx) mmWave NOMA system where frequency diverse array (FDA) antennas are utilized. FDA employs small frequency increments across the element indices which yields angle-range dependent beamspace. Herein, an equivalent radiate beamspace is designed to serve the users. Further, to ensure user equity, we formulate objective function to max-min achievable sum rate subject to power allocation and BS equivalent FDA transmit beamspace along the users. Since the problem is not convex, a boundary-compressed Bat meta-heuristic optimization algorithm is devised to provide a sub-optimal solution by optimizing the frequency increments to synthesis the BS beamspace along the users. The achievable secrecy rate, cost efficiency (CE), economic efficiency (ECE), and secrecy energy efficiency (SEE) are derived for the users. Both theoretical analysis and simulation results indicate that the proposed scheme would constitute an excellent nominee for 5G mmWave NOMA communication applications.

Safeguarding NOMA Networks via Reconfigurable Dual-Functional Surface Under Imperfect CSI

This paper investigates the use of the reconfigurable dual-functional surface to guarantee the full-space secure transmission in non-orthogonal multiple access (NOMA) networks. In the presence of eavesdroppers, the downlink communication from the base station to the legitimate users is safeguarded by the simultaneously transmitting and reflecting reconfigurable intelligent surface (STAR-RIS), where three practical operating protocols, namely energy splitting (ES), mode selection (MS), and time splitting (TS), are studied. The joint optimization of power allocation, active and passive beamforming is investigated to maximize the secrecy energy efficiency (SEE), taking into account the imperfect channel state information (CSI) of all channels. For ES, by approximating the semi-infinite constraints with the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\mathcal {S}$</tex-math></inline-formula> -procedure and general sign-definiteness, the problem is solved by an alternating optimization framework. Besides, the proposed algorithm is extended to the MS protocol by solving a mixed-integer non-convex problem. While for TS, a two-layer iterative method is proposed. Simulation results show that: 1) The proposed STAR-RIS assisted NOMA networks are able to provide up to 33.6% higher SEE than conventional RIS counterparts; 2) TS and ES protocols are generally preferable for low and high power domain, respectively; 3) The accuracy of CSI estimation and the bit resolution power consumption are crucial to reap the SEE benefits offered by STAR-RIS.

Security Energy Efficiency Analysis of Analog Collaborative Beamforming With Stochastic Virtual Antenna Array of UAV Swarm

To extend the transmission range governed by limited transmit power, collaborative beamforming (CB) can be employed with a virtual antenna array (VAA) constructed by an unmanned aerial vehicle (UAV) swarm. CB techniques combined with physical layer security (PLS) algorithms are known to better secure transmissions of sensitive information in the presence of eavesdropping attacks, compared to co-located antenna-based schemes. In particular, analog collaborative beamforming (ACB) with random VAA topologies, which is suitable for UAV networks due to its lower signaling/channel estimation overhead compared to the digital CB, can provide a significantly higher secrecy rate by creating noise-like signals at eavesdroppers. However, the increase in energy consumption to improve secrecy rate had been ignored in the existing ACB-based PLS schemes, which is of paramount importance considering the limited onboard energy of UAVs. Thus, motivated by such limitation, in this paper, we examine the security energy efficiency of the ACB-based PLS technique, where a group of UAVs (or VAA elements) randomly change their locations in a distributed manner to randomize the array factor of the VAA, i.e., a stochastic VAA. The proposed stochastic VAA outperforms the existing static VAA in terms of secrecy energy efficiency as verified by analytic and numerical results. Further, the impact of phase errors of the proposed scheme is also presented, which indicates the significance of the accurate phase estimation.

Robust Secure Energy Efficient Beamforming for mmWave UAV Communications With Jittering

This letter proposes a robust secure and energy efficient beamforming (BF) scheme for a millimeter-wave unmanned aerial vehicle (UAV) communication system with imperfect angle-of-departure (AoD) estimation of air-to-ground channel caused by jittering. Specifically, an optimization problem is formulated to maximize the worst-case secrecy energy efficiency (SEE), defined as the ratio of the sum achievable secrecy rate (ASR) to the total power consumption, subject to the UAV transmit power constraint. Due to the difficulty in solving this problem arisen from the AoD uncertainties and the non-convex structures of SEE and ASR, we first adopt the discretization method to simplify AoD uncertainties to a deterministic form and then exploit the successive convex approximation approach with auxiliary variables to convert the original problem into a convex one. Finally, an iterative algorithm is designed to obtain the suboptimal solution. Numerical results are provided to confirm the effectiveness and superiority of the proposed robust BF scheme compared to some benchmark schemes.

On the Security of Full-Duplex Relay-Assisted Underwater Acoustic Network With NOMA

Wireless underwater acoustic (UWA) networks serve several civilian and military applications. The multiple reflections and dispersion, along with the long propagation delay limit the sum rate of UWA networks. Earlier works discussed adding full-duplex (FD), relay assistance, and non-orthogonal multiple access (NOMA) to enhance the system sum rate. Another challenge in UWA networks is the power limitation of devices. Hence, power optimization is crucial to maximize the energy efficiency. Furthermore, securing the UWA network against eavesdropping is essential to guarantee the confidentiality of communication. This work optimizes the power to maximize the secrecy sum rate (SSR) of a FD relay-assisted NOMA (FD-R-NOMA) underwater acoustic network subjected to an eavesdropper (Eve) attack. The network is studied in two states: when the network has or not the channel information (CI) of the threat. FD-R-NOMA UWA network shows to be more resilient to eavesdropping with higher secrecy energy efficiency when compared to the conventional half-duplex orthogonal multiple access network. Also, the results reveal that knowing the CI of the Eve improves the SSR of the network. Besides, the results show the effect of factors like the location of Eve, interference cancellation efficiency, noise in the environment, and sensor distributions in the system.

Achieving Secrecy Energy Efficiency Fairness in UAV-Enabled Multi-User Communication Systems

This letter investigates the secrecy energy efficiency (SEE) fairness of unmanned aerial vehicle (UAV)-enabled multi-user communication systems where a UAV disseminates data to multiple ground users (GUs) in the presence of an eavesdropper (EVE). Taking into account the security threats from EVE, the limited on-board energy of UAV and the fairness among GUs, we formulate a user-oriented SEE maximization problem to maximize the minimum GU&#x2019;s SEE by jointly optimizing the UAV trajectory and resource allocation subject to the UAV motion constraints and resource budgets. Due to the difficulty in solving this problem that arises from the fractional structure of SEE and the coupling characteristic of optimization variables, we first exploit the successive convex approximation to transform the original problem to a convex one, which is further converted into a second order cone program to reduce the computational complexity. Then, a convergent iterative algorithm is designed to find the suboptimal solution. Simulation results show that the proposed scheme significantly improves SEE fairness of GUs as compared to some benchmark schemes.

Intelligent Omni-Surface Enhanced Aerial Secure Offloading

Different from conventional reflecting-only metasurfaces, intelligent omni-surfaces (IOSs) are capable of reflecting and transmitting the received signals simultaneously. As such, users located at the both sides of IOSs can be served efficiently. In this paper, a novel IOS-enhanced aerial secure offloading system is proposed in the presence of multiple ground eavesdroppers. Specifically, the IOS is adopted to prevent information leakage, improve legitimate reception quality and expand the security deployment range of unmanned aerial vehicles (UAVs). To maximize the secrecy energy efficiency (SEE) of the considered system, a non-convex resource allocation problem is formulated by allocating computing frequency, determining offloading strategy, controlling transmit power, designing phase shifts, and deploying UAV locations. The formulated problem is non-trivial and challenging to be solved directly due to the highly coupled variables. To tackle this issue, the alternating optimization technique is invoked to decouple the original one into five subproblems, and then the computing and communication settings are alternatively optimized using a low complexity iterative algorithm. Finally, simulation results demonstrate that: i) In terms of the SEE performance, our IOS-enhanced aerial secure offloading system significantly outperforms the benchmark schemes; ii) Compared with reflecting-only surfaces, IOSs can take full advantage of the flexible deployment ability of UAVs, such that their secure offloading space can be considerably expanded.

Terahertz Meets Untrusted UAV-Relaying: Minimum Secrecy Energy Efficiency Maximization via Trajectory and Communication Co-Design

Unmanned aerial vehicles (UAVs) and Terahertz (THz) technology are envisioned to play paramount roles in next-generation wireless communications. In this paper, we present a novel secure UAV-assisted mobile relaying system operating at THz bands for data acquisition from multiple ground user equipments (UEs) towards a destination. We assume that the UAV-mounted relay may act, besides providing relaying services, as a potential eavesdropper called the untrusted UAV-relay (UUR). To safeguard end-to-end communications, we present a secure two-phase transmission strategy with cooperative jamming. Then, we devise an optimization framework in terms of a new measure $-$ secrecy energy efficiency (SEE), defined as the ratio of achievable average secrecy rate to average system power consumption, which enables us to obtain the best possible security level while taking UUR's inherent flight power limitation into account. For the sake of quality of service fairness amongst all the UEs, we aim to maximize the minimum SEE (MSEE) performance via the joint design of key system parameters, including UUR's trajectory and velocity, communication scheduling, and network power allocation. Since the formulated problem is a mixed-integer nonconvex optimization and computationally intractable, we decouple it into four subproblems and propose alternative algorithms to solve it efficiently via greedy/sequential block successive convex approximation and non-linear fractional programming techniques. Numerical results demonstrate significant MSEE performance improvement of our designs compared to other known benchmarks.

Secrecy Energy Efficiency Maximization in UAV-Enabled Wireless Sensor Networks Without Eavesdropper’s CSI

Unmanned aerial vehicles (UAVs) are anticipated to be a potential data collection solution for wireless sensor networks (WSNs). The main challenges of integrating UAVs in WSNs are security threats and UAV’s onboard energy limitation. To cope with these two challenges, this article examines the secrecy energy efficiency (SEE) maximization problem in UAV-enabled WSN. Specifically, a full-duplex (FD) UAV gathers confidential information from ground sensor nodes (SNs) in the uplink while sending jamming signals to confound a ground eavesdropper (Eve) in the downlink. Considering a passive eavesdropping scenario lacking Eve’s instantaneous channel state information (CSI), the resulting problem is subject to the constraints of connection outage probability (COP), secrecy outage probability (SOP), securely collected bits, and flight trajectory. To tackle the intractable nonconvex problem, we first derive the optimal codeword rate and redundancy rate in closed-form expressions and then develop a low-complexity algorithm using the block coordinate descent (BCD) approach to alternatively optimize the SN scheduling, SN transmit power, UAV transmit power, and UAV trajectory. Simulation results verify the performance gains of the proposed scheme compared with the benchmark schemes. In particular, the proposed scheme achieves nearly the same secrecy rate gains at a lower UAV’s energy consumption cost than the sum secrecy rate maximization (SSRM) baseline. Moreover, it is revealed that trajectory optimization of the proposed scheme plays a crucial role in improving SEE performance compared with the circle trajectory (CT) baseline.

Secure and Energy Efficient Transmission for IRS-Assisted Cognitive Radio Networks

The spectrum efficiency (SE) and security of the secondary users (SUs) in the cognitive radio networks (CRNs) have become two main issues due to the limitation interference to the primary users (PUs) and the shared spectrum with the PUs. Intelligent reflecting surface (IRS) has been recently proposed as a revolutionary technique which can help to enhance the SE and physical layer security of wireless communications. This paper investigates the application of IRS in an underlay CRN, where a multi-antenna cognitive base station (CBS) utilizes spectrum assigned to the PU to communicate with a SU via IRS in the presence of multiple coordinated eavesdroppers (Eves). To achieve the trade-off between the secrecy rate (SR) and energy consumption, we investigate the secrecy energy efficiency (SEE) maximization problem by jointly designing the transmit beamforming at the CBS and the reflect beamforming at the IRS. To solve the non-convex problem with coupled variables, we propose an iterative alternating optimization algorithm to solve the sub-problems alternately, by utilizing an iterative penalty function based algorithm for sub-problem 1 and the difference of two-convex functions method for sub-problem 2. Furthermore, we provide a second-order-cone-programming (SOCP) approximation approach to reduce the computational complexity. Finally, the simulation results demonstrate that IRS can help significantly improve the SE and enhance the physical layer security in the CRNs. Moreover, the effectiveness and superiority of our proposed algorithm in achieving the trade-off between the SR and energy consumption are verified.

Energy-Efficient Secure Short-Packet Transmission in NOMA-Assisted mMTC Networks With Relaying

Massive Machine-Type Communication (mMTC) is proposed by ITU to provide a large scale of connectivity services for billions of machine-type communications devices (MTCDs) via cellular networks. However, MTCDs are generally energy-constrained, security capability limited and short-packet transmission dominated. It has great challenges for massive MTCDs to perform short-packet transmission simultaneously while guaranteeing the confidentiality and energy efficiency of the information transmission. In this paper, we investigate the energy-efficient secure short-packet transmission of Non-Orthogonal Multiple Access (NOMA) assisted mMTC networks, in which MTCDs aim to transmit secrecy messages to the destination base station via trusted relays with a passive eavesdropper present. To realize secure, reliable and energy-efficient transmission, we maximize the secrecy energy efficiency (SEE) by implementing joint relay and power level selection. Furthermore, we formulate a decentralized stateless Q-learning-based multi-agent reinforcement learning (MARL) algorithm for the dynamic and complex mMTC systems. The simulation results show that adopting the proposed decentralized MARL algorithm and relaying with NOMA can improve the performance of SEE while reducing information exchange overhead.

Secure Transmission for Energy Efficient Parallel Mixed FSO/RF System in Presence of Independent Eavesdroppers

In this paper, the physical layer security (PLS) challenges for a decode and forward (DF) based dual hop mixed free space optical (FSO) / radio frequency (RF) communication system in the presence of multiple eavesdroppers has been investigated. In order to improve the PLS of the energy efficient co-operative communication system, diversity combining techniques have been introduced at the destination node. In addition to this, collusion and non collusion eavesdropper scenarios are considered to make the system more practical. The FSO and RF links are assumed to experience independent Málaga ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\mathcal {M}$</tex-math></inline-formula> ) and Nakagami- <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$m$</tex-math></inline-formula> fading distributions, respectively. Additionally, the FSO link model considers the impact of boresigt and non-zero boresight pointing errors and type of optical demodulation scheme. To investigate the security performance, the lower bound for the secrecy outage probability (SOP) and effective secrecy throughput (EST) have been obtained in terms of Meijer’s G function. Thereafter, asymptotic expressions have been derived for the considered system and the numerical results have been verified by the Monte-Carlo simulation method. Finally, we have analyzed the secrecy energy efficiency (SEE) based on secrecy rate ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$R_s$</tex-math></inline-formula> ) of the considered system to provide practical insights into the effect of major parameters on the energy efficient secure transmission design.

SLNR-based Secure Energy Efficient Beamforming in Multibeam Satellite Systems

Motivated by the fact that both security and energy efficiency are the fundamental requirements and design targets of future satellite communications, this letter investigates secure energy efficient beamforming in multibeam satellite systems, where the satellite user in each beam is surrounded by an eavesdropper attempting to intercept the confidential information. To simultaneously improve the transmission security and reduce power consumption, our design objective is to maximize the system secrecy energy efficiency (SEE) under the constraint of total transmit power budget. Different from the existing schemes with high complexity, we propose an alternating optimization scheme to address the SEE problem by decomposing the original nonconvex problem into subproblems. Specifically, we first utilize the signal-to-leakage-plus-noise ratio (SLNR) metric to obtain closed-form normalized beamforming weight vectors, while the successive convex approximation (SCA) method is used to efficiently solve the power allocation subproblem. Then, an iterative algorithm is proposed to obtain the suboptimal solutions. Finally, simulation results are provided to verify the superiority of the proposed scheme compared to the benchmark schemes.

Resource Allocation for Secure SWIPT-Enabled D2D Communications With $\alpha$ Fairness

Device-to-device (D2D) communication is an emerging paradigm that can improve system capacity and spectral efficiency by using cooperative communication coexisting with cellular networks. In spite of these advantages, D2D communication suffers from unfair resource usage, security risks posed by eavesdroppers, and limited energy storage. To deal with these issues, in this paper, we propose a resource allocation algorithm to maximize the security-aware energy efficiency (EE) for D2D users (DUs) in a simultaneous wireless information and power transfer (SWIPT)-enabled D2D communication system with <inline-formula><tex-math notation="LaTeX">$\alpha$</tex-math></inline-formula> fairness, where multiple random eavesdroppers are present. In particular, we formulate a multi-objective resource allocation problem by jointly optimizing the transmit power, power-splitting (PS) factors of DUs, and the sub-channel allocation factor under multiple constraints, including the maximum interference power for each cellular user, the maximum transmit power of each DU, the PS factor, and the integer sub-channel assignment. To solve the non-convex problem, an iterative algorithm is developed to obtain the sub-optimal solution. Simulation results verify that the proposed algorithm outperforms benchmark algorithms in terms of balancing secrecy EE and fairness.

Security-aware spectrum sharing for NOMA in cognitive radio networks with discrete-time energy harvesting

In this paper, we propose a security-aware spectrum sharing scheme for wireless-powered cognitive radio networks (CRNs) with non-orthogonal multiple access (NOMA). In this system, a primary transmitter (PT) intends to send confidential signal to a primary receiver (PR) by assisting of a secondary transmitter (ST), while there is a potential eavesdropper (PE) within the scope of PR. It is assume that ST has no fixed energy supply but the NOMA cognitive transmission can be performed after harvesting sufficient radio frequency (RF) energy. To ensure that PT’s confidential signal is safety, PR will be equipped with two antennas and operating in full-duplex mode, so that while ST is performing cognitive transmission, one of the antennas sends artificial noise (AN) from PR to interfere the signal receiving of PE. According to whether the accumulated energy of ST is sufficient and whether ST can correctly decode the PT’s signal, the system can operate in three modes. Since ST needs to accumulate enough energy through several continuous transmission slots, the charging and discharging processes of the battery in the ST can be simulated as a discrete-time Markov chain. Based on these, we derive exact expressions of outage probabilities of the primary and secondary systems, then an approximate formula of secrecy outage probability (SOP) of primary system is also derived. In addition, in order to further improve the transmission performance of the system, optimal power allocation factor and power level of AN are obtained by maximizing the secrecy rate of the primary system, while guaranteeing the system energy efficiency. Compared with zero-forcing (ZF) technique, the proposed secure spectrum sharing scheme has a slight disadvantage in secrecy energy efficiency, but it is simple to deploy, low cost, and achieves a better secrecy rate, which can be applied for a variety of application scenarios.

Energy-Efficient Secure Communications for Wireless-Powered Cognitive Radio Networks.

In this study, we investigate energy-efficient secure communications for wireless-powered cognitive ratio networks, in which multiple secondary users (SUs) share the same frequency band with primary users (PUs) and energy harvesting (EH) nodes harvest energy from the transmitted signals, even though information decoding is not permitted. To maximize the average secrecy energy efficiency (SEE) of SUs while ensuring acceptable interference on PUs and the required amount of energy for the EH nodes, we propose an energy-efficient transmit power control algorithm using dual decomposition, wherein suboptimal transmit powers are determined in an iterative manner with low complexity. Through extensive simulations in various scenarios, we verify that the proposed scheme has a higher average SEE than conventional schemes and a considerably shorter computation time than the optimal scheme.

Dual-UAV Enabled Secure Data Collection With Propulsion Limitation

Unmanned aerial vehicles (UAVs) have been widely utilized to improve the end-to-end performance of wireless communications. However, its line-of-sight makes UAV communication vulnerable to malicious eavesdroppers. In this paper, we propose two cooperative dual-UAV enabled secure data collection schemes to ensure security, with the practical propulsion energy consumption considered. We first maximize the worst-case average secrecy rate with the average propulsion power limitation, where the scheduling, the transmit power, the trajectory and the velocity of the two UAVs are jointly optimized. To solve the non-convex multivariable problem, we propose an iterative algorithm based on block coordinate descent and successive convex approximation. To further save the on-board energy and prolong the flight time, we then maximize the secrecy energy efficiency of UAV data collection, which is a fractional and mixed integer nonlinear programming problem. Based on the Dinkelbach method, we transform the objective function into an integral expression and propose an iterative algorithm to obtain a suboptimal solution to secrecy energy efficiency maximization. Numerical results show that the average secrecy rate is maximized in the first scheme with propulsion limitation, while in the second scheme, the secrecy energy efficiency is maximized with the optimal velocity to save propulsion power and improve secrecy rate simultaneously.

Secrecy Energy Efficiency in Full-Duplex AF Relay Systems With Untrusted Energy Harvesters

In this letter, we investigate an artificial noise (AN) aided beamforming scheme for full-duplex amplify-and-forward relay network in the presence of multiple untrusted energy harvesting receivers (EHRs). We establish an optimization problem to maximize the secrecy energy efficiency (SEE), while meeting the self-interference nulling and transmit power constraints at relay as well as maintaining the energy harvesting threshold at the EHRs by jointly designing the relay beamforming (BF) and AN covariance matrices. Due to the non-convex structure of the SEE maximization problem, we first design a null-space BF scheme at relay to eliminate the SI and simplify the joint optimization and then propose an iterative algorithm to achieve a local optimum based on the penalty function and the successive convex approximation methods. Numerical results are provided to validate the effectiveness of our proposed design.

Joint Resource, Trajectory, and Artificial Noise Optimization in Secure Driven 3-D UAVs With NOMA and Imperfect CSI

Driven by the practicality of unmanned aerial vehicle (UAV), we consider a dual-UAV based non-orthogonal multiple access (NOMA) scenario, which consists of one communication UAV for services and one jamming UAV against eavesdropping. The goal is to maximize the secrecy energy efficiency through the successive convex approximation based communication resource, UAV trajectory, and artificial noise optimization. Considering the probabilistic constraint of outage probability from imperfect channel state information, we transform it to a non-probabilistic problem by Markov inequality and Marcum <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$Q$ </tex-math></inline-formula> -function, then the problem is decomposed into three subproblems. We apply matching-swapping method to assign subchannel in non-orthogonal multiple access (NOMA) UAV networks before the joint process, then convert the power optimization problem to a standard convex optimization form by upper bound of the concave function. The communication UAV trajectory is studied under the constraints of flying energy consumption, maximum speed, and flying altitude. To track this NP-hard problem, Taylor expansion and various slack variables sets are introduced to transform the non-convex problem to convex one. For the artificial noise optimization problem, we use the lower bound to replace the convex term turning it into an easy-to-solve convex optimization problem. In the end, simulations results reveal that: 1) The reasonable jamming scheme can improve the secrecy energy efficiency of the NOMA UAV networks, even if it can cause interference for legitimate users; 2) UAV will fly to a place where the performance gain from users is high when flying energy consumption permits.

Securing Mobile Multiuser Transmissions With UAVs in the Presence of Multiple Eavesdroppers

This paper discusses the problem of securing the transmissions of multiple ground users against eavesdropping attacks. We propose and optimize the deployment of a single unmanned aerial vehicle (UAV), which serves as an aerial relay between the user cluster and the base station. The focus is on maximizing the secrecy energy efficiency by jointly optimizing the uplink transmission powers of the ground users and the position of the UAV. The joint optimization problem is nonconvex; therefore we split it into two subproblems and solve them using an iterative algorithm.