873 research outputs found
Dynamic UAV Swarm Collaboration for Multi-Targets Tracking under Malicious Jamming: Joint Power, Path and Target Association Optimization
In this paper, the multi-target tracking (MTT) with an unmanned aerial
vehicle (UAV) swarm is investigated in the presence of jammers, where UAVs in
the swarm communicate with each other to exchange information of targets during
tracking. The communication between UAVs suffers from severe interference,
including inter-UAV interference and jamming, thus leading to a deteriorated
quality of MTT. To mitigate the interference and achieve MTT, we formulate a
interference minimization problem by jointly optimizing UAV's sub-swarm
division, trajectory, and power, subject to the constraint of MTT, collision
prevention, flying ability, and UAV energy consumption. Due to the multiple
coupling of sub-swarm division, trajectory, and power, the proposed
optimization problem is NP-hard. To solve this challenging problem, it is
decomposed into three subproblems, i.e., target association, path plan, and
power control. First, a cluster-evolutionary target association (CETA)
algorithm is proposed, which involves dividing the UAV swarm into the multiple
sub-swarms and individually matching these sub-swarms to targets. Second, a
jamming-sensitive and singular case tolerance (JSSCT)-artificial potential
field (APF) algorithm is proposed to plan trajectory for tracking the targets.
Third, we develop a jamming-aware mean field game (JA-MFG) power control
scheme, where a novel cost function is established considering the total
interference. Finally, to minimize the total interference, a dynamic
collaboration approach is designed. Simulation results validate that the
proposed dynamic collaboration approach reduces average total interference,
tracking steps, and target switching times by 28%, 33%, and 48%, respectively,
comparing to existing baselines.Comment: 14 pages, 17 figure
Some Applications of Polynomial Optimization in Operations Research and Real-Time Decision Making
We demonstrate applications of algebraic techniques that optimize and certify
polynomial inequalities to problems of interest in the operations research and
transportation engineering communities. Three problems are considered: (i)
wireless coverage of targeted geographical regions with guaranteed signal
quality and minimum transmission power, (ii) computing real-time certificates
of collision avoidance for a simple model of an unmanned vehicle (UV)
navigating through a cluttered environment, and (iii) designing a nonlinear
hovering controller for a quadrotor UV, which has recently been used for load
transportation. On our smaller-scale applications, we apply the sum of squares
(SOS) relaxation and solve the underlying problems with semidefinite
programming. On the larger-scale or real-time applications, we use our recently
introduced "SDSOS Optimization" techniques which result in second order cone
programs. To the best of our knowledge, this is the first study of real-time
applications of sum of squares techniques in optimization and control. No
knowledge in dynamics and control is assumed from the reader
Intelligent-Reflecting-Surface-Assisted UAV Communications for 6G Networks
In 6th-Generation (6G) mobile networks, Intelligent Reflective Surfaces
(IRSs) and Unmanned Aerial Vehicles (UAVs) have emerged as promising
technologies to address the coverage difficulties and resource constraints
faced by terrestrial networks. UAVs, with their mobility and low costs, offer
diverse connectivity options for mobile users and a novel deployment paradigm
for 6G networks. However, the limited battery capacity of UAVs, dynamic and
unpredictable channel environments, and communication resource constraints
result in poor performance of traditional UAV-based networks. IRSs can not only
reconstruct the wireless environment in a unique way, but also achieve wireless
network relay in a cost-effective manner. Hence, it receives significant
attention as a promising solution to solve the above challenges. In this
article, we conduct a comprehensive survey on IRS-assisted UAV communications
for 6G networks. First, primary issues, key technologies, and application
scenarios of IRS-assisted UAV communications for 6G networks are introduced.
Then, we put forward specific solutions to the issues of IRS-assisted UAV
communications. Finally, we discuss some open issues and future research
directions to guide researchers in related fields
Satellite-assisted UAV Trajectory Control in HostileJamming Environments
Satellite and unmanned aerial vehicle (UAV) net-works have been introduced as enhanced approach to providedynamic control, massive connections and global coverage forfuture wireless communication systems. This paper considersa coordinated satellite-UAV communication system, where theUAV performs the environmental reconnaissance task with theassistance of satellite in a hostile jamming environment. To fulfillthis task, the UAV needs to realize autonomous trajectory controland upload the collected data to the satellite. With the aid ofthe uploading data, the satellite builds the environment situationmap integrating the beam quality, jamming status, and trafficdistribution. Accordingly, we propose a closed-loop anti-jammingdynamic trajectory optimization approach, which is divided intothree stages. Firstly, a coarse trajectory planning is made accord-ing to the limited prior information and preset points. Secondly,the flight control between two adjacent preset points is formulatedas a Markov decision process, and reinforcement learning (RL)based automatic flying control algorithms are proposed to explorethe unknown hostile environment and realize autonomous andprecise trajectory control. Thirdly, based on the collected dataduring the UAV’s flight, the satellite utilizes an environmentsituation estimating algorithm to build an environment situationmap, which is used to reselect the preset points for the first stageand provide better initialization for the RL process in the secondstage. Simulation results verify the validity and superiority of theproposed approach
Optimal Jammer Placement in UAV-assisted Relay Networks
We consider the relaying application of unmanned aerial vehicles (UAVs), in
which UAVs are placed between two transceivers (TRs) to increase the throughput
of the system. Instead of studying the placement of UAVs as pursued in existing
literature, we focus on investigating the placement of a jammer or a major
source of interference on the ground to effectively degrade the performance of
the system, which is measured by the maximum achievable data rate of
transmission between the TRs. We demonstrate that the optimal placement of the
jammer is in general a non-convex optimization problem, for which obtaining the
solution directly is intractable. Afterward, using the inherent characteristics
of the signal-to-interference ratio (SIR) expressions, we propose a tractable
approach to find the optimal position of the jammer. Based on the proposed
approach, we investigate the optimal positioning of the jammer in both dual-hop
and multi-hop UAV relaying settings. Numerical simulations are provided to
evaluate the performance of our proposed method.Comment: 6 pages, 6 figure
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