arXiv subjects

Ki-Hong Park

Publications and source records attributed to Ki-Hong Park.

At least 19 recordsLinked to original sources

arXiv2026

Resource Allocation for Secure Dual-UAV-Assisted ISAC System

Integrated sensing and communication (ISAC) is a rising technology in the next wireless communication networks, enabling the simultaneous execution of communication and sensing tasks by fully utilizing limited spectrum resources. In this work, we investigate the secrecy performance of a dual-uncrewed aerial vehicle (UAV)-assisted secure ISAC system. Specifically, a base station UAV communicates with users and transmits radar signals to locate potential eavesdroppers, while simultaneously providing information to a jammer UAV to perform jamming tasks. Considering constraints such as maximum UAV velocity, transmit power, propulsion energy, and sensing thresholds, we maximize the average secrecy rate by optimizing user scheduling strategies, time allocation, transmit power, and UAV trajectories. The presence of a non-convex problem, originating from tightly coupled variables, is tackled by an efficient iterative algorithm. In particular, the original optimization problem is decomposed into six subproblems, and non-convex subproblems are transformed into approximately convex forms via successive convex approximation. Then, block coordinate descent techniques are employed to solve all subproblems sequentially. Numerical results demonstrate the convergence and effectiveness of the proposed algorithm.

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arXiv2026

Trade-off for Secure UAV-ISCC Systems

The integrated sensing, communication, and computing (ISCC) system overcomes the limitations of conventional standalone architectures. Through resource sharing and collaborative design, it dynamically optimizes and jointly enhances communication, sensing, and computing performance, thereby significantly improving overall system efficiency. This work investigates the performance trade-off among secure communication rate, radar estimation rate, and computational energy efficiency in an uncrewed aerial vehicle (UAV)-assisted ISCC system. By jointly optimizing the UAV's three-dimensional (3D) trajectory, beamforming, user scheduling, and computational frequency, three optimization problems are formulated to maximize the average secrecy rate, sensing rate, and computational energy efficiency, respectively, thus establishing the system's performance boundaries under diverse scenarios. On this basis, the trade-off among security, sensing, and computation is further explored with the goal of maximizing the normalized weighted sum of the three performance metrics, which provides a theoretical basis for the performance-coordinated design of aerial ISCC systems.

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arXiv2026

Joint 3D Trajectory Design and Resource Allocation for Secure Dual-UAV-aided Underlay Systems

Uncrewed aerial vehicles (UAVs) are increasingly being employed for data collection tasks, thanks to their high mobility and easy deployment, acting as aerial platforms to collect data from ground devices (GDs). This study considers a secure underlay data collection system assisted by dual UAVs and focuses on the joint design of the UAVs' three-dimensional (3D) flight paths, the power of the jamming UAV, the power of GDs, and the scheduling of the underlay GDs in the context of an aerial eavesdropper. The highly coupled objective function and non-convex constraints make the formulated problem more complicated to solve. We first utilize an approximate lower bound on the expected spectral efficiency to streamline the solution process. The average secrecy spectral efficiency (ASSE) is maximized by jointly designing the 3D trajectory of the UAVs, the transmit power of GDs, and the user scheduling. The optimization problem is decomposed into four subproblems using block coordinate descent, with each of them into manageable convex optimization tasks by incorporating slack variables and employing successive convex approximation methods. The numerical results validate the effectiveness of our proposed approach, demonstrating that the design of UAV 3D trajectories remarkably improves the ASSE of the considered system.

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arXiv2026

On Secure EKF-enhanced UAV-ISAC Systems

Integrated sensing and communication (ISAC) has emerged as a promising key technology for future wireless networks, enabling the efficient coordination of sensing and communication functions within limited resources. This work investigates a secure ISAC system assisted by an uncrewed aerial vehicle (UAV). By incorporating the extended Kalman filter (EKF), the proposed system is capable of delivering communication services to legitimate users while simultaneously jamming eavesdroppers and performing joint prediction and tracking of the trajectories of both legitimate and illegitimate users. Considering practical constraints such as {sensing beamwidth}, transmit power, and UAV's propulsion energy consumption, the secrecy rate is maximized through the joint design of transmit beamforming and UAV trajectory. To tackle the resulting highly non-convex optimization problem, an efficient iterative algorithm is developed by integrating block coordinate descent, successive convex approximation, and EKF, thereby yielding a high-quality suboptimal solution. Extensive simulation results validate the superior performance of the proposed scheme compared to benchmarks.

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arXiv2025

Two Birds With One Stone: Beamforming Design for Target Sensing and Proactive Eavesdropping

This work studies the beamforming design in the joint proactive eavesdropping (PE) and target sensing (TS) systems. The base station (BS) wiretaps the information transmitted by the illegal transmitter and sends the waveform for TS. The shared waveform also serves as artificial noise to interfere with the illegal receiver, thereby achieving successful PE.We firstly optimize the transmitting beampattern of the BS only to maximize the eavesdropping rate or only to minimize the Cram{é}r-Rao bound, respectively. Then, the joint design of PE and TS is investigated by formulating the PE-centric, the TS-centric, and the normalized weighted optimization problems. The formulated problems are solved by the semi-definite relaxation technique and the sequential rank-one constraint relaxation method to address the complexity of the original problem. Furthermore, the scenario in which the quality of the eavesdropping channel is stronger than that of the illegal channel is considered. Numerical results demonstrate that the proposed algorithm can effectively realize PE and TS simultaneously.

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arXiv2025

On secure UAV-aided ISCC systems

Integrated communication and sensing, which can make full use of the limited spectrum resources to perform communication and sensing tasks simultaneously, is an up-and-coming technology in wireless communication networks. In this work, we investigate the secrecy performance of an uncrewed aerial vehicle (UAV)-assisted secure integrated communication, sensing, and computing system, where the UAV sends radar signals to locate and disrupt potential eavesdroppers while providing offload services to ground users (GUs). Considering the constraints of UAV maximum speed, transmit power, and propulsion energy, as well as secure offloading, data transmission, and computation time, the total energy consumption of GUs is minimized by jointly optimizing user offloading ratio, user scheduling strategy, transmit beamforming, and UAV trajectory. An efficient iterative optimization algorithm is proposed to solve the non-convex optimization problem caused by tightly coupled dependent variables. In particular, the original optimization problem is decomposed into four sub-optimization problems, and the non-convex sub-problems are transformed into approximately convex forms via successive convex approximation. Then, all sub-problems are solved successively by using the block coordinate descent technique. Numerical results demonstrate the convergence and validate the effectiveness of the proposed algorithm.

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arXiv2025

Beamforming for Secure RSMA-Aided ISAC Systems

This work investigates the physical layer security of rate-splitting multiple access (RSMA)-aided integrated communication and sensing (ISAC) systems. The ISAC base station (BS) transmits signals to communicate with users in an eavesdropped scenario and to estimate the parameters of the sensed targets. The research considers different sensing signals under RSMA technology and the Cram{é}r-Rao bound of the parameter estimation is utilized as the sensing metric. With the channel state information (CSI) of eavesdroppers known, the transmitting beam of the BS is optimized to maximize the energy efficiency in terms of the minimum user rate and secrecy capacity, considering the fairness among users and ensuring the sensing performance and communication security. With the CSI of eavesdroppers unknown, the transmitting beam of the BS is designed to minimize the energy consumption for sensing and communication, and the residual power is utilized for artificial noise, which is isotropically emitted to achieve interference with potential eavesdroppers. To solve the non-convex problems, three iterative algorithms based on successive convex approximation and penalty function are proposed. The simulation results illustrate the effectiveness of the proposed schemes.

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arXiv2025

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.

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arXiv2025

Channel Capacity Saturation Point and Beamforming Acceleration for Near-Field XL-MIMO Multiuser Communications

One of the most important technologies in the fifth generation (5G) and the sixth generation (6G) is massive multiple input multiple outputs (MIMO) or extremely large-scale MIMO (XL-MIMO). With the evolving high-frequency technologies in millimeter band or tereHz band, the communication scene is changing into near-field rather than the conventional far-field scenario. In this letter, instead of advertising the XL-MIMO in the near-field, we appeal that a limit should be set on the size of the antenna array, beyond which the channel capacity will not show a significant increase. We show capacity saturation point can be analytically determined. Moreover, we propose a new beamforming algorithm that relieve the heavy computation due to the large antenna size even around the saturation point. Numerical results are provided to validate our analysis and show the performance of our newly proposed beamforming scheme.

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arXiv2024

Secure Offloading in NOMA-Aided Aerial MEC Systems Based on Deep Reinforcement Learning

Mobile edge computing (MEC) technology can reduce user latency and energy consumption by offloading computationally intensive tasks to the edge servers. Unmanned aerial vehicles (UAVs) and non-orthogonal multiple access (NOMA) technology enable the MEC networks to provide offloaded computing services for massively accessed terrestrial users conveniently. However, the broadcast nature of signal propagation in NOMA-based UAV-MEC networks makes it vulnerable to eavesdropping by malicious eavesdroppers. In this work, a secure offload scheme is proposed for NOMA-based UAV-MEC systems with the existence of an aerial eavesdropper. The long-term average network computational cost is minimized by jointly designing the UAV's trajectory, the terrestrial users' transmit power, and computational frequency while ensuring the security of users' offloaded data. Due to the eavesdropper's location uncertainty, the worst-case security scenario is considered through the estimated eavesdropping range. Due to the high-dimensional continuous action space, the deep deterministic policy gradient algorithm is utilized to solve the non-convex optimization problem. Simulation results validate the effectiveness of the proposed scheme.

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arXiv2024

Proactive Eavesdropping in Relay Systems via Trajectory and Power Optimization

Wireless relays can effectively extend the transmission range of information. However, if relay technology is utilized unlawfully, it can amplify potential harm. Effectively surveilling illegitimate relay links poses a challenging problem. Unmanned aerial vehicles (UAVs) can proactively surveil wireless relay systems due to their flexible mobility. This work focuses on maximizing the eavesdropping rate (ER) of UAVs by jointly optimizing the trajectory and jamming power. To address this challenge, we propose a new iterative algorithm based on block coordinate descent and successive convex approximation technologies. Simulation results demonstrate that the proposed algorithm significantly enhances the ER through trajectory and jamming power optimization.

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arXiv2024

Multi-UAV Trajectory Design for Fair and Secure Communication

Unmanned aerial vehicles (UAVs) play an essential role in future wireless communication networks due to their high mobility, low cost, and on-demand deployment. In air-to-ground links, UAVs are widely used to enhance the performance of wireless communication systems due to the presence of high-probability line-of-sight (LoS) links. However, the high probability of LoS links also increases the risk of being eavesdropped, posing a significant challenge to the security of wireless communications. In this work, the secure communication problem in a multi-UAV-assisted communication system is investigated in a moving airborne eavesdropping scenario. To improve the secrecy performance of the considered communication system, aerial eavesdropping capability is suppressed by sending jamming signals from a friendly UAV. An optimization problem under flight conditions, fairness, and limited energy consumption constraints of multiple UAVs is formulated to maximize the fair sum secrecy throughput. Given the complexity and non-convex nature of the problem, we propose a two-step-based optimization approach. The first step employs the $K$-means algorithm to cluster users and associate them with multiple communication UAVs. Then, a multi-agent deep deterministic policy gradient-based algorithm is introduced to solve this optimization problem. The effectiveness of this proposed algorithm is not only theoretically but also rigorously verified by simulation results.

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arXiv2024

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.

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arXiv2024

Jamming Intrusions in Extreme Bandwidth Communication: A Comprehensive Overview

As the evolution of wireless communication progresses towards 6G networks, extreme bandwidth communication (EBC) emerges as a key enabler to meet the ambitious key performance indicator set for this next-generation technology. 6G aims for peak data rates of 1 Tb/s, peak spectral efficiency of 60 b/s/Hz, maximum bandwidth of 100 GHz, and mobility support up to 1000 km/h, while maintaining a high level of security. The capability of 6G to manage enormous data volumes introduces heightened security vulnerabilities, such as jamming attacks, highlighting the critical need for in-depth research into jamming in EBC. Understanding these attacks is vital for developing robust countermeasures, ensuring 6G networks can maintain their integrity and reliability amidst these advanced threats. Recognizing the paramount importance of security in 6G applications, this survey paper explores prevalent jamming attacks and the corresponding countermeasures in EBC technologies such as millimeter wave, terahertz, free-space optical, and visible light communications. By comprehensively reviewing the literature on jamming in EBC, this survey paper aims to provide a valuable resource for researchers, engineers, and policymakers involved in the development and deployment of 6G networks. Understanding the nuances of jamming in different EBC technologies is essential for devising robust security mechanisms and ensuring the success of 6G communication systems in the face of emerging threats.

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arXiv2024

Outage Analysis of Aerial Semi-Grant-Free NOMA Systems

In this paper, we analyze the outage performance of unmanned aerial vehicles (UAVs)-enabled downlink non-orthogonal multiple access (NOMA) communication systems with the semi-grant-free (SGF) transmission scheme. A UAV provides coverage services for a grant-based (GB) user and one user is allowed to utilize the same channel resource opportunistically. The hybrid successive interference cancellation scheme is implemented in the downlink NOMA scenarios for the first time. The analytical expressions for the exact and asymptotic outage probability (OP) of the grant-free (GF) user are derived. The results demonstrate that no-zero diversity order can be achieved only under stringent conditions on users' quality of service requirements. Subsequently, we propose an efficient dynamic power allocation (DPA) scheme to relax such data rate constraints to address this issue. The analytical expressions for the exact and asymptotic OP of the GF user with the DPA scheme are derived. Finally, Monte Carlo simulation results are presented to validate the correctness of the derived analytical expressions and demonstrate the effects of the UAV's location and altitude on the OP of the GF user.

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arXiv2023

Dynamic Resource Management in CDRT Systems through Adaptive NOMA

This paper introduces a novel adaptive transmission scheme to amplify the prowess of coordinated direct and relay transmission (CDRT) systems rooted in non-orthogonal multiple access principles. Leveraging the maximum ratio transmission scheme, we seamlessly meet the prerequisites of CDRT while harnessing the potential of dynamic power allocation and directional antennas to elevate the system's operational efficiency. Through meticulous derivations, we unveil closed-form expressions depicting the exact effective sum throughput. Our simulation results adeptly validate the theoretical analysis and vividly showcase the effectiveness of the proposed scheme.

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arXiv2023

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.

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arXiv2022

Technical Report: Development of an Ultrahigh Bandwidth Software-defined Radio Platform

For the development of new digital signal processing systems and services, the rapid, easy, and convenient prototyping of ideas and the rapid time-to-market of products are becoming important with advances in technology. Conventionally, for the development stage, particularly when confirming the feasibility or performance of a new system or service, an idea is first confirmed through a computerbased software simulation after developing an accurate model of the operating environment. Next, this idea is validated and tested in the real operating environment. The new systems or services and their operating environments are becoming increasingly complicated. Hence, their development processes too are more complex cost- and time-intensive tasks that require engineers with skill and professional knowledge/experience. Furthermore, for ensuring fast time-to-market, all the development processes encompassing the (i) algorithm development, (ii) product prototyping, and (iii) final product development, must be closely linked such that they can be quickly completed. In this context, the aim of this paper is to propose an ultrahigh bandwidth software-defined radio platform that can prototype a quasi-real-time operating system without a developer having sophisticated hardware/software expertise. This platform allows the realization of a software-implemented digital signal processing system in minimal time with minimal efforts and without the need of a host computer.

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