Cognitive radio as solution for ground-aerial surveillance through WSN and UAV infrastructure

Stâmâtescu, Grigore; Popescu, Dan; Dobrescu, Radu

doi:10.1109/ecai.2014.7090210

Cited by 27 publications

(11 citation statements)

References 16 publications

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“…Oriented from the CR concept, the opportunistic spectrum access (OSA) is a more specialized technology aimed at improving the spectrum utilization ratio by sharing spectrum resources opportunistically among users. The authors in [71] presented a multi-level system framework with an opportunistic communication scheme in which the time, frequency and spatial stream of the wireless environment were significantly improved. The authors in [8] described a policy-based radio for UAVs in which the radio can consider spectrum opportunities and perform dynamic spectrum access (DSA).…”

Section: Related Workmentioning

confidence: 99%

Dynamic Spectrum Management with Network Function Virtualization for UAV Communication

Petrunin

Tsourdos

2021

J Intell Robot Syst

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Rapid increases in unmanned aerial vehicles (UAVs) applications are attributed to severe spectrum collision issues, especially when UAVs operate in spectrum scarce environments, such as urban areas. Dynamic air-to-ground (A2G) link solutions can mitigate this issue by utilizing programmable communication hardware in the air and real-time assignment of spectrum resources to achieve high-throughput and low-latency connectivity between UAVs and operators. To mitigate the high-computation issue among ground control station (GCS) networks and provide a broad communication coverage for large number of UAVs, we propose an advanced UAV A2G communication solution integrated with the dynamic spectrum management (DSM) and network function virtualization (NFV) technology to serve urban operations. The edge-cutting UAV communication technologies are surveyed. The proposed scheme is discussed in terms of the high-level system architecture, virtual network architecture, specific virtual functions (SVFs), and affiliated operation support databases. Some major research challenges are highlighted and the possible directions of future research are identified.

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Section: Related Workmentioning

confidence: 99%

Dynamic Spectrum Management with Network Function Virtualization for UAV Communication

Petrunin

Tsourdos

2021

J Intell Robot Syst

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“…Currently, some improvements have been done through the employment of intelligent control technique, while others have been achieved by improving the communication protocol algorithms itself. For example, Stamatescu et al used cognitive radio (CR) scheme by exploiting, in an opportunistic fashion, the time, frequency, and spatial stream in a wireless environment. This method is expected to increase the communication reliability at each hierarchical level.…”

Section: Related Work On Swarm Robot Intercommunication and Collabormentioning

confidence: 99%

Label‐QoS switching protocol for quality of service assurance in dynamic swarm robot local network

Irawan

Jusoh

Abas

2018

Int J Communication

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Summary This paper presents the modeling and analysis of a proposed label–quality of service (QoS) switching protocol for heterogeneous robot in a swarm. Establishing the data communication and network in multirobot task allocation is an important aspect in robot collaboration. Instead of passing the data through the cloud network, each robot can be configured as a node in its swarm for intercommunication. This research was conducted to model and propose aggregation and classification methods in a swarm robot network inspired from multiprotocol label switching, namely, label‐QoS switching protocol. Each packet of data is forwarded with a proposed 2‐side label values that are concerned with addressing and QoS. This proposed protocol was applied in each of the node's routing, and it was set up with forwarding information table. The simulation and analysis were conducted in 2 situations: (1) with a constant n–label switch mobile robot and a number of packet data increasing with time and (2) with a constant number of packet and varying n–label switch mobile robot by time. With reference to the network parameter performances, it shows that the anomaly treatment by the proposed protocol is able to prioritize the data forwarding between the robots at the edge of the swarm with class of service although the robot community at the center is increasing or getting crowded.

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“…Drones have been considered both in the context of data gathering in wireless sensor networks [7]- [9], and more recently in the context of delivering data to mobile users in cellular networks. Since the focus of this paper is on cellular networks, we only review the drone-related research relevant to cellular networks.…”

Section: Related Workmentioning

confidence: 99%

Dynamic base station repositioning to improve spectral efficiency of drone small cells

Fotouhi

Ding

Hassan

2017

2017 IEEE 18th International Symposium on a World of Wireless, Mobile and Multimedia Networks (WoWMoM)

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With recent advancements in drone technology, researchers are now considering the possibility of deploying small cells served by base stations mounted on flying drones. A major advantage of such drone small cells is that the operators can quickly provide cellular services in areas of urgent demand without having to pre-install any infrastructure. Since the base station is attached to the drone, technically it is feasible for the base station to dynamic reposition itself in response to the changing locations of users for reducing the communication distance, decreasing the probability of signal blocking, and ultimately increasing the spectral efficiency. In this paper, we first propose distributed algorithms for autonomous control of drone movements, and then model and analyse the spectral efficiency performance of a drone small cell to shed new light on the fundamental benefits of dynamic repositioning. We show that, with dynamic repositioning, the spectral efficiency of drone small cells can be increased by nearly 100% for realistic drone speed, height, and user traffic model and without incurring any major increase in drone energy consumption.

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Cognitive radio as solution for ground-aerial surveillance through WSN and UAV infrastructure

Cited by 27 publications

References 16 publications

Dynamic Spectrum Management with Network Function Virtualization for UAV Communication

Dynamic Spectrum Management with Network Function Virtualization for UAV Communication

Label‐QoS switching protocol for quality of service assurance in dynamic swarm robot local network

Dynamic base station repositioning to improve spectral efficiency of drone small cells

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