Beamforming Design for Joint Target Sensing and Proactive Eavesdropping

This work studies the beamforming design in the joint target sensing and proactive eavesdropping (JTSAPE) system. The JTSAPE base station (BS) receives the information transmitted by the illegal transmitter and transmits the waveform for target sensing. The shared waveform also serves as artificial noise to interfere with the illegal receiver, thereby achieving proactive eavesdropping. We firstly optimize the transmitting beam of the BS to maximize the eavesdropping signal-to-interference-plus-noise ratio or minimize the target estimation parameter Cram{\'{e}}r-Rao bound, respectively. Then, the joint optimization of proactive eavesdropping and target sensing is investigated, and the normalized weighted optimization problem is formulated. To address the complexity of the original problem, the formulated problem is decomposed into two subproblems: proactive eavesdropping and target sensing, which are solved by the semi-definite relaxation technique. Furthermore, the scenario in which the quality of the eavesdropping channel is stronger than that of the illegal channel is considered. We utilize the sequential rank-one constraint relaxation method and iteration technique to obtain the high-quality suboptimal solution of the beam transmit covariance matrix. Numerical simulation shows the effectiveness of our proposed algorithm.

Aerial Relay to Achieve Covertness and Security

In this work, a delay-tolerant unmanned aerial vehicle (UAV) relayed covert and secure communication framework is investigated. In this framework, a legitimate UAV serves as an aerial relay to realize communication when the direct link between the terrestrial transmitter and receiver is blocked and also acts as a friendly jammer to suppress the malicious nodes presented on the ground. Subsequently, considering the uncertainty of malicious nodes' positions, a robust fractional programming optimization problem is built to maximize energy efficiency by jointly optimizing the trajectory of the UAV, the transmit power of the transmitter, and the time-switching factor. For the extremely complicated covert constraint, Pinsker's inequality, Jensen's inequality, and the bisection search method are employed to construct a tractable shrunken one. After this, an alternate optimization-based algorithm is proposed to solve the fractional programming optimization problem. To achieve low complexity, we design the primal-dual search-based algorithm and the successive convex approximation-based algorithm, respectively, for each sub-problem. Numerical results show the effectiveness of our proposed algorithm.

3D Trajectory Design for Energy-constrained Aerial CRNs Under Probabilistic LoS Channel

Unmanned aerial vehicles (UAVs) have been attracting significant attention because there is a high probability of line-of-sight links being obtained between them and terrestrial nodes in high-rise urban areas. In this work, we investigate cognitive radio networks (CRNs) by jointly designing three-dimensional (3D) trajectory, the transmit power of the UAV, and user scheduling. Considering the UAV's onboard energy consumption, an optimization problem is formulated in which the average achievable rate of the considered system is maximized by jointly optimizing the UAV's 3D trajectory, transmission power, and user scheduling. Due to the non-convex optimization problem, a lower bound on the average achievable rate is utilized to reduce the complexity of the solution. Subsequently, the original optimization problem is decoupled into four subproblems by using block coordinate descent, and each subproblem is transformed into manageable convex optimization problems by introducing slack variables and successive convex approximation. Numerical results validate the effectiveness of our proposed algorithm and demonstrate that the 3D trajectories of UAVs can enhance the average achievable rate of aerial CRNs.

Secure Rate-Splitting Multiple Access Transmissions in LMS Systems

This letter investigates the secure delivery performance of the rate-splitting multiple access scheme in land mobile satellite (LMS) systems, considering that the private messages intended by a terminal can be eavesdropped by any others from the broadcast signals. Specifically, the considered system has an N-antenna satellite and numerous single-antenna land users. Maximum ratio transmission (MRT) and matched-filtering (MF) precoding techniques are adopted at the satellite separately for the common messages (CMs) and for the private messages (PMs), which are both implemented based on the estimated LMS channels suffering from the Shadowed-Rician fading. Then, closed-form expressions are derived for the ergodic rates for decoding the CM, and for decoding the PM at the intended user respectively, and more importantly, we also derive the ergodic secrecy rate against eavesdropping. Finally, numerical results are provided to validate the correctness of the proposed analysis models, as well as to show some interesting comparisons.

Trajectory and Power Design for Aerial Multi-User Covert Communications

Unmanned aerial vehicles (UAVs) can provide wireless access to terrestrial users, regardless of geographical constraints, and will be an important part of future communication systems. In this paper, a multi-user downlink dual-UAVs enabled covert communication system was investigated, in which a UAV transmits secure information to ground users in the presence of multiple wardens as well as a friendly jammer UAV transmits artificial jamming signals to fight with the wardens. The scenario of wardens being outfitted with a single antenna is considered, and the detection error probability (DEP) of wardens with finite observations is researched. Then, considering the uncertainty of wardens' location, a robust optimization problem with worst-case covertness constraint is formulated to maximize the average covert rate by jointly optimizing power allocation and trajectory. To cope with the optimization problem, an algorithm based on successive convex approximation methods is proposed. Thereafter, the results are extended to the case where all the wardens are equipped with multiple antennas. After analyzing the DEP in this scenario, a tractable lower bound of the DEP is obtained by utilizing Pinsker's inequality. Subsequently, the non-convex optimization problem was established and efficiently coped by utilizing a similar algorithm as in the single-antenna scenario. Numerical results indicate the effectiveness of our proposed algorithm.

Trajectory and power design for aerial CRNs with colluding eavesdroppers

Unmanned aerial vehicles (UAVs) can provide wireless access services to terrestrial users without geographical limitations and will become an essential part of the future communication system. However, the openness of wireless channels and the mobility of UAVs make the security of UAV-based communication systems particularly challenging. This work investigates the security of aerial cognitive radio networks (CRNs) with multiple uncertainties colluding eavesdroppers. A cognitive aerial base station transmits messages to cognitive terrestrial users using the spectrum resource of the primary users. All secondary terrestrial users and illegitimate receivers jointly decode the received message. The average secrecy rate of the aerial CRNs is maximized by jointly optimizing the UAV's trajectory and transmission power. An iterative algorithm based on block coordinate descent and successive convex approximation is proposed to solve the non-convex mixed-variable optimization problem. Numerical results verify the effectiveness of our proposed algorithm and show that our scheme improves the secrecy performance of airborne CRNs.

On Secure Uplink Transmission in Hybrid RF-FSO Cooperative Satellite-Aerial-Terrestrial Networks

This work investigates the secrecy outage performance of the uplink transmission of a radio-frequency (RF)-free-space optical (FSO) hybrid cooperative satellite-aerial-terrestrial network (SATN). Specifically, in the considered cooperative SATN, a terrestrial source (S) transmits its information to a satellite receiver (D) via the help of a cache-enabled aerial relay (R) terminal with the most popular content caching scheme, while a group of eavesdropping aerial terminals (Eves) trying to overhear the transmitted confidential information. Moreover, RF and FSO transmissions are employed over S-R and R-D links, respectively. Considering the randomness of R, D, and Eves, and employing a stochastic geometry framework, the secrecy outage performance of the cooperative uplink transmission in the considered SATN is investigated and a closed-form analytical expression for the end-to-end secrecy outage probability is derived. Finally, Monte-Carlo simulations are shown to verify the accuracy of our analysis.

Effect of Strong Time-Varying Transmission Distance on LEO Satellite-Terrestrial Deliveries

In this paper, we investigate the effect of the strong time-varying transmission distance on the performance of the low-earth orbit (LEO) satellite-terrestrial transmission (STT) system. We propose a new analytical framework using finite-state Markov channel (FSMC) model and time discretization method. Moreover, to demonstrate the applications of the proposed framework, the performances of two adaptive transmissions, rate-adaptive transmission (RAT) and power-adaptive transmission (PAT) schemes, are evaluated for the cases when the transmit power or the transmission rate at the LEO satellite is fixed. Closed-form expressions for the throughput, energy efficiency (EE), and delay outage rate (DOR) of the considered systems are derived and verified, which are capable of addressing the capacity, energy efficiency, and outage rate performance of the considered LEO STT scenarios with the proposed analytical framework.

On the Security of LEO Satellite Communication Systems: Vulnerabilities, Countermeasures, and Future Trends

Low Earth Orbit (LEO) satellite systems undergo a period of rapid development driven by the ever-increasing user demands, reduced costs, and technological progress. Since there is a paucity of literature on the security issues of LEO Satellite Communication Systems (SCSs), we aim for filling this knowledge gap. Specifically, we critically appraise the inherent characteristics of LEO SCSs and summarize their unique security vulnerabilities. In light of this, we further discuss their security vulnerabilities, including the issues of passive and active eavesdropping attacks, interference scenarios, single event upsets, and space debris. Subsequently, we discuss the corresponding active and passive security countermeasures, followed by unveiling a range of trade-offs, security vulnerabilities and their countermeasures. Furthermore, we shed light on several promising future research directions for enhancing the security of LEO SCSs, such as secure quantum communications, three-dimensional virtual arrays, artificial intelligence-based security measures, space-based blockchain, and intelligent reflecting surface enabled secure transmission. Finally, the take-away messages of this paper are crystallized in our concluding design guidelines.

Applying Deep-Learning-Based Computer Vision to Wireless Communications: Methodologies, Opportunities, and Challenges

Deep learning (DL) has obtained great success in computer vision (CV) field, and the related techniques have been widely used in security, healthcare, remote sensing, etc. On the other hand, visual data is universal in our daily life, which is easily generated by prevailing but low-cost cameras. Therefore, DL-based CV can be explored to obtain and forecast some useful information about the objects, e.g., the number, locations, distribution, motion, etc. Intuitively, DL-based CV can facilitate and improve the designs of wireless communications, especially in dynamic network scenarios. However, so far, it is rare to see such kind of works in the existing literature. Then, the primary purpose of this article is to introduce ideas of applying DL-based CV in wireless communications to bring some novel degrees of freedom for both theoretical researches and engineering applications. To illustrate how DL-based CV can be applied in wireless communications, an example of using DL-based CV to millimeter wave (mmWave) system is given to realize optimal mmWave multiple-input and multiple-output (MIMO) beamforming in mobile scenarios. In this example, we proposed a framework to predict the future beam indices from the previously-observed beam indices and images of street views by using ResNet, 3-dimensional ResNext, and long short term memory network. Experimental results show that our frameworks can achieve much higher accuracy than the baseline method, and visual data can help significantly improve the performance of MIMO beamforming system. Finally, we discuss the opportunities and challenges of applying DL-based CV in wireless communications.