Performance Analysis of Routing Protocols for UAV Communication Networks

Tan, Xiaopeng; Zuo, Zhen; Su, Shaojing; Guo, Xiaojun; Sun, Xiang; Deng, Jiankang

doi:10.1109/access.2020.2995040

Cited by 37 publications

(13 citation statements)

References 40 publications

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“…In UAV group networks [260,261], the mobility and altitude of UAVs, transmitted power, inter-UAV distances, extraneous noise, uneven UAV access users' traffic distribution in both spatial and temporal domains, will largely affect the routing protocol [262] and conventional routing protocols fail to work. Several novel routing algorithms have been proposed recently for UAV group networks to achieve better performance [263][264][265][266][267][268]. Nevertheless, routing strategies which can adapt to high mobility, dynamic topology, and different routing capabilities in LEO satellite networks and UAV group networks are still in their early stage and need further studies.…”

Section: Space-air-ground-sea Integrated Networkmentioning

confidence: 99%

Towards 6G wireless communication networks: vision, enabling technologies, and new paradigm shifts

You

Wang

Huang

et al. 2020

Sci. China Inf. Sci.

1,329

495

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The fifth generation (5G) wireless communication networks are being deployed worldwide from 2020 and more capabilities are in the process of being standardized, such as mass connectivity, ultra-reliability, and guaranteed low latency. However, 5G will not meet all requirements of the future in 2030 and beyond, and sixth generation (6G) wireless communication networks are expected to provide global coverage, enhanced spectral/energy/cost efficiency, better intelligence level and security, etc. To meet these requirements, 6G networks will rely on new enabling technologies, i.e., air interface and transmission technologies and novel network architecture, such as waveform design, multiple access, channel coding schemes, multi-antenna technologies, network slicing, cell-free architecture, and cloud/fog/edge computing. Our vision on 6G is that it will have four new paradigm shifts. First, to satisfy the requirement of global coverage, 6G will not be limited to terrestrial communication networks, which will need to be complemented with non-terrestrial networks such as satellite and unmanned aerial vehicle (UAV) communication networks, thus achieving a space-air-ground-sea integrated communication network. Second, all spectra will be fully explored to further increase data rates and connection density, including the sub-6 GHz, millimeter wave (mmWave), terahertz (THz), and optical frequency bands. Third, facing the big datasets generated by the use of extremely heterogeneous networks, diverse communication scenarios, large numbers of antennas, wide bandwidths, and new service requirements, 6G networks will enable a new range of smart applications with the aid of artificial intelligence (AI) and big data technologies. Fourth, network security will have to be strengthened when developing 6G networks. This article provides a comprehensive survey of recent advances and future trends in these four aspects. Clearly, 6G with additional technical requirements beyond those of 5G will enable faster and further communications to the extent that the boundary between physical and cyber worlds disappears.

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Section: Space-air-ground-sea Integrated Networkmentioning

confidence: 99%

Towards 6G wireless communication networks: vision, enabling technologies, and new paradigm shifts

You

Wang

Huang

et al. 2020

Sci. China Inf. Sci.

1,329

495

View full text Add to dashboard Cite

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“…Traditional routing protocols have developed rapidly in the last few decades. The authors of [23] carried out performance tests and comparisons concerning classical routing protocols for AODV, OLSR, Dynamic Source Routing (DSR), and the geographic routing protocol (GRP). The simulation results indicate that different routing protocols can be used in different UAV communication network scenarios.…”

Section: Conventional Routing Protocolmentioning

confidence: 99%

DDQN with Prioritized Experience Replay-Based Optimized Geographical Routing Protocol of Considering Link Stability and Energy Prediction for UANET

Zhang

Qiu

2022

Sensors

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Unmanned aerial vehicles (UAVs) are important equipment for efficiently executing search and rescue missions in disaster or air-crash scenarios. Each node can communicate with the others by a routing protocol in UAV ad hoc networks (UANETs). However, UAV routing protocols are faced with the challenges of high mobility and limited node energy, which hugely lead to unstable link and sparse network topology due to premature node death. Eventually, this severely affects network performance. In order to solve these problems, we proposed the deep-reinforcement-learning-based geographical routing protocol of considering link stability and energy prediction (DSEGR) for UANETs. First of all, we came up with the link stability evaluation indicator and utilized the autoregressive integrated moving average (ARIMA) model to predict the residual energy of neighbor nodes. Then, the packet forward process was modeled as a Markov Decision Process, and according to a deep double Q network with prioritized experience replay to learn the routing-decision process. Meanwhile, a reward function was designed to obtain a better convergence rate, and the analytic hierarchy process (AHP) was used to analyze the weights of the considered factors in the reward function. Finally, to verify the effectiveness of DSEGR, we conducted simulation experiments to analyze network performance. The simulation results demonstrate that our proposed routing protocol remarkably outperforms others in packet delivery ratio and has a faster convergence rate.

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“…This self‐organized model is developed to maintain the speed and mobility during the transmission to optimize the residual energy of the node. Zafar et al 14 suggested a multiple cluster based topology where a separate link table is maintained among the neighbor nodes to analyze the performance parameters of the other node to optimize the energy consumption. Bhandari et al 15 suggested a dynamic clustering framework where the overheads are reduced by limiting the resources to stabilize the network.…”

Section: Related Workmentioning

confidence: 99%

Topology based energy efficient routing using integration of fuzzy based markov chain cluster‐optimized novel ant bee colony approach in FANET

Ali

Ruby

2022

Concurrency and Computation

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Summary Flying adhoc network (FANET) is a rapidly flourishing technology in recent years which has an excellent scope of growth in the to the improvised mobility and the frequency changing topology FANETs are considered as a challenging technology to design an optimal network model. This problem is fixed with the topology based routing technique. Hence a novel hybrid clustering algorithm where fuzzy based Markov chain cluster (FMC2) is integrated with the optimized novel ant bee colony (ONABC) optimization algorithm (IoFMC2‐ONABC). This algorithm demonstrates an improvised efficiency with the novel ant bee colony algorithm. The proposed model simulation is done in an NS‐2 simulator and results are compared against the existing conventional approaches like adhoc on‐demand distance vector, efficient intelligent packet broadcasting protocol, energy‐efficient routing in flying ad hoc networks, and energy‐efficient gray wolf. This method aims at achieving improvised connectivity, optimizing the power consumption thereby increasing the residual energy augmenting the performance efficiency of the network through selection of the proper cluster center during each transmission. Thus the energy consumption of the node was optimized to 7.6 J with the highest packet delivery ratio of about 85.15 ensuring minimal packet losses during huge data transmission.

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Performance Analysis of Routing Protocols for UAV Communication Networks

Cited by 37 publications

References 40 publications

Towards 6G wireless communication networks: vision, enabling technologies, and new paradigm shifts

Towards 6G wireless communication networks: vision, enabling technologies, and new paradigm shifts

DDQN with Prioritized Experience Replay-Based Optimized Geographical Routing Protocol of Considering Link Stability and Energy Prediction for UANET

Topology based energy efficient routing using integration of fuzzy based markov chain cluster‐optimized novel ant bee colony approach in FANET

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