Due to the sparse node distribution and the harsh propagation environment in Maritime Internet of Things (MIoT), traditional local mobile self-organizing networks relying on direct Device-to-device (D2D) communications face limited coverage and frequent link outages. To address these issues, this letter investigates the unmanned aerial vehicle (UAV)-assisted MIoT, where UAVs serve as aerial base stations to provide enhanced coverage. Using stochastic geometry, we develop a system model that consists of the D2D tier and the UAV tier, respectively employing the Fluctuating Two-Ray (FTR) model and Nakagami- $m$ model. Then, analytical expressions of coverage probability and achievable rate, along with their tight upper and lower bounds, are derived. Simulation results validate the theoretical analysis, confirming both the coverage improvement from UAV deployment and the effectiveness of the FTR model. It is further shown that by optimizing the UAV deployment with appropriate density, altitude, and antenna array size, the inter-layer interference can be effectively mitigated thus improving the coverage probability and achievable rate.
Driven by the vision of a thriving low-altitude economy and aiming to provide on-demand services for diverse entities, this paper investigates an integrated sensing and communication (ISAC)-enabled low-altitude wireless network (LAWN). Benefiting from flexible mobility and cost-effective cooperative deployment, multiple ISAC-enabled uncrewed aerial vehicles (UAVs) are emerging as an ISAC paradigm for on-demand deployment in LAWN. However, due to the complex inter-UAV interference and resource coupling in LAWN, it is difficult to properly coordinate different constrained resources, including spatial deployment, energy, and wireless channels, to simultaneously meet the sensing and communication requirements. To address these challenges, this paper formulates a sensing–communication optimization (SCO) problem in LAWN by jointly optimizing subcarrier allocation, transmit power allocation, and three-dimensional (3D) UAV deployments to maximize network utility while satisfying quality of service (QoS) requirements for multiple users and target sensing mutual information (MI) requirements. To enable efficient solutions, we propose a hierarchical optimization approach that vertically decouples the SCO problem into two subproblems: a top level employing a Gibbs Sampling–based multi-UAV 3D deployment algorithm for efficient exploration and deployment optimization, and a bottom level performing resource allocation via a dual-based joint power and subcarrier allocation algorithm. Simulation results demonstrate that the proposed approach achieves a favorable trade-off between communication and sensing and significantly enhances the overall performance and adaptability of the LAWN.
Cheng Ma, Zewei Jing, Qinghai Yang et al.· IEEE Transactions on Wireles...· 0 citations
—Unmanned aerial vehicle (UAV) swarm-assisted integrated sensing and communication (ISAC) networks are a crucial technology for providing communication and sensing services in emergency rescue scenarios without base station support. However, the strong coupling between communication and sensing resources in such networks fundamentally limits the communication and sensing performance of ISAC systems. This paper jointly optimizes spectrum allocation, UAV association and deployment to maximize average system throughput while ensuring localization accuracy in such networks, where sensing is realized through localization. We begin by deriving an analytical expression for localization accuracy, which explicitly captures the joint effects of link quality and anchor geometry under shared communication-localization spectrum resources. We then formulate average system throughput maximization as a mixed-integer nonlinear and non-convex optimization problem with the constraints of localization accuracy, sub-channels, UAV association, UAV deployment and signal-to-interference-plus-noise ratio. We further develop an alternating iterative optimization method to solve this complex optimization problem. Within this method, a particle swarm optimization-based method is developed to jointly optimize spectrum allocation and UAV association, and a dueling double deep Q-network-based method is further employed for UAV deployment optimization. Finally, extensive simulation results are presented to validate the efficiency of our optimization method, and also to illustrate how key parameters influence average system throughput and localization accuracy.
Zhuo-Jia Yang, Wei Su, Bin Yang et al.· IEEE Transactions on Mobile...· 0 citations
This paper investigates the outage performance of unmanned aerial vehicle (UAV)-assisted free-space optical (FSO) communication systems operating in foggy channels. The analysis jointly accounts for atmospheric turbulence, fog-induced attenuation, generalized Beckmann-distributed pointing errors (PE), and angle-of-arrival (AoA) fluctuations caused by UAV orientation jitter. A comprehensive statistical channel model is developed, from which closed-form expressions for outage probability and an analytical characterization of outage capacity are derived. The effects of receiver field-of-view (FoV) limitations and multi-UAV amplify-and-forward relaying on link reliability are also investigated. Numerical results validate the proposed analysis and reveal that AoA fluctuations impose a fundamental performance limit, resulting in an outage floor, particularly under dense fog and narrow-FoV conditions. These findings provide practical design insights for improving the reliability of UAV-assisted FSO communication systems in adverse weather environments.
Mahdi Ataee, S. Sadough, Khadijeh Ali Mahmoodi· EAI Endorsed Transactions on...· 0 citations
In temporary emergency communication coverage scenarios where terrestrial communication infrastructure is damaged or lacks sufficient capacity, UAVs equipped with base stations have emerged as an effective solution due to their flexible deployment and rapid response capability. However, in multi-UAV networks, the three-dimensional deployment of UAVs significantly affects air-to-ground link quality, while power allocation further determines the level of system interference and throughput performance. To address this issue, this paper considers a multi-UAV communication system and jointly takes into account user link reliability and service requirement satisfaction, thereby establishing a joint optimization model for QoS-constrained coverage and network throughput. To address the non-convex joint optimization problem, a problem-tailored dual-population cooperative NSGA-II framework, termed IDPC-NSGA-II, is developed. By coupling dual-population evolution, adaptive mutation, uncovered-user-guided local search, and interference-aware repair with the characteristics of multi-UAV emergency communications, the proposed method improves the trade-off between QoS-constrained coverage and network throughput. Simulation results in a representative emergency communication scenario show that the proposed method achieves a favorable trade-off between QoS-constrained coverage and throughput, and outperforms the compared algorithms under the considered network setting.
Gui-Fen Chen, Ruiyang Liu· Digital Signal and Computer...· 0 citations
Uncrewed aerial vehicle (UAV)-assisted free-space optics (FSO) communication provides an effective means to extend the capability and resilience of existing network infrastructures by offering flexible aerial relaying. In particular, the use of UAVs as relay nodes helps to mitigate the strict line-of-sight (LoS) requirements of conventional FSO links. In this work, a multi-UAV-based FSO communication system employing decode-and-forward (DF) relaying with energy harvesting (EH) at the relay is investigated, where both partial relay selection (PRS) and opportunistic relay selection (ORS) strategies are adopted to determine the optimal UAV for data forwarding. The optical wireless channel is modeled using two comprehensive turbulence distributions, namely the Málaga distribution and the doubly inverted Gamma–Gamma (IGGG) distribution, which jointly capture the effects of atmospheric turbulence, atmospheric attenuation, 2D and 3D pointing error misalignment, and angle-of-arrival (AoA) fluctuations. Closed-form expressions are derived for key performance metrics, including outage probability (OP), while the average symbol error rate (SER) and ergodic capacity (EC) are evaluated using Gauss–Laguerre (GL) quadrature under both relay selection schemes and channel models. Moreover, an asymptotic performance analysis is carried out in the high signal-to-noise ratio (SNR) regime, through which the diversity gain of the proposed system is explicitly characterized. The accuracy of the analytical results is validated through extensive Monte-Carlo simulations. Numerical results illustrate the influence of relay selection strategies, turbulence severity, and system parameters on the overall performance and provide clear insights into the achievable diversity gains and robustness of multi-UAV-assisted FSO systems under realistic atmospheric conditions.
Prashant Sharma, Deepshikha Singh, S. R.· IEEE Open Journal of the Com...· 0 citations
The evolution of sixth-generation (6G) networks increasingly demands seamless and reliable connectivity across heterogeneous and geographically dispersed environments, with maritime regions remaining a major challenge due to vast coverage areas, limited terrestrial infrastructure, and complex propagation conditions. In this paper, we investigate the capacity characteristics of space-air-ground-sea integrated networks (SAGSINs) for maritime communications. Specifically, we consider a SAGSIN system comprising a terrestrial base station (BS), a geostationary satellite, a decode-and-forward (DF) relay, and maritime users randomly distributed according to a Poisson point process (PPP). The relay, implemented by either an uncrewed aerial vehicle (UAV) or a large ship, serves multiple maritime users, providing a unified framework for comparing heterogeneous relay platforms and backhaul options. Based on this model, the system performance is analyzed under two representative fading regimes: 1) quasi-static fading, where analytical expressions and tight upper bounds are derived for the outage probability and corresponding outage capacity; and 2) block fading, where closed-form ergodic capacity formulations are obtained to evaluate the long-term average throughput. Extensive Monte Carlo simulations validate the theoretical analysis and quantify the effects of key system parameters. Our results offer insights into the design and optimization of high-reliability maritime communication links, providing guidelines for practical implementation and future 6G SAGSINs development.
Jinpeng Xu, Yingqi He, Lin Zhou et al.· IEEE Transactions on Wireles...· 0 citations
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