An Autonomous Spectrum Management Scheme for Unmanned Aerial Vehicle Networks in Disaster Relief Operations

Abstract

This paper studies the problem of spectrum shortage in an unmanned aerial vehicle (UAV) network during critical missions such as wildfire monitoring, search and rescue, and disaster monitoring. Such applications involve a high demand for high-throughput data transmissions such as real-time video-, image-, and voice-streaming where the assigned spectrum to the UAV network may not be adequate to provide the desired Quality of Service (QoS). In these scenarios, the aerial network can borrow additional spectrum from the available terrestrial networks in trade of a relaying service for them. We propose a spectrum sharing model in which the UAVs are grouped into two classes of relaying UAVs that service the spectrum owner and the sensing UAVs that perform the disaster relief mission using the obtained spectrum. The operation of the UAV network is managed by a hierarchical mechanism in which a central controller assign the tasks of the UAVs based on their resources and determine their operation region based on the level of priority of impacted areas and then the UAVs autonomously fine-tune their position using a modelfree reinforcement learning algorithm to maximize the individual throughput and prolong their lifetime. We analyze the performance and the convergence for the proposed method analytically and with extensive simulations in different scenarios.INDEX TERMS Autonomous UAV networks, multi-agent systems, Q-learning, reinforcement learning, spectrum sharing.

Dynamic Spectrum Management with Network Function Virtualization for UAV Communication

“…Summaries of the dynamic A2G communication schemes are highlighted in Table 1. The few existing works related to sharing spectrum resources with UAVs, especially with the interweave method, allow UAVs to access spectrum resources opportunistically [66]. Recently, the concept of using the centralized spectrum allocation scheme for the UAV communication is proposed in [9], which is similar with our previous work in [83].…”

“…Unmanned aerial vehicles (UAVs) have drawn tremendous attention in recent decades due to their advantages in high mobility and convenient deployment; however, the inherent high-dynamic characteristic [23] in UAVs brings additional challenges in the information exchange between UAVs and users, specifically demanding a low-latency and highthroughput wireless air-to-ground (A2G) link. The communication schemes in A2G links typically employ a static link, such as aircraft communications addressing and reporting (ACARS), global system for mobile communication (GSM), and L band digital aeronautical communications systems (L-DACS) [31], with predetermined spectrum resources, which may result in a scarcity of bandwidth in cases of high-throughput communication during short-term periods [66]. In some operations with extreme spectrum scarcity, such as the urban environment, communication links are easily interfered with by other users, and sufficient bandwidth is lacking.…”

UASTrustChain: A Decentralized Blockchain- Based Trust Monitoring Framework for Autonomous Unmanned Aerial Systems

“…On the other hand, the DOs can form (6) and let it equal to (5). The tuple (x i , y i , z i ) in (6) represents the exact location of D i . Thus, any four DOs can make a system of four linear equations with four variables, i.e x, y, z, β, to find the exact UAV position and the deviation of its clock from the synchronized DO clocks.…”

Modeling and Performance Analysis of Opportunistic Link Selection for UAV Communication

“…OSA allows secondary users, i.e., UAVs in this case, to occupy spectrum resources in an opportunistic manner under a presumption of causing non-interference to primary users. As an interweave mode in CRN concept [ 9 ], typical OSA employs a listening-before-transmission mechanism [ 10 ], where the spectrum sensing phase is required before each transmission to protect PUs [ 10 , 11 , 12 ]. The authors in [ 11 ] proposed an efficient spectrum sensing enabled OSA scheme for the ultra-dense operations, and discussed the determination of spectrum processing time where the priority control mechanism is employed.…”