LEO-Satellite-Assisted UAV: Joint Trajectory and Data Collection for Internet of Remote Things in 6G Aerial Access Networks

Jia, Ziye; Sheng, Min; Li, Jiandong; Niyato, Dusit; Han, Zhu

doi:10.1109/jiot.2020.3021255

Cited by 174 publications

(62 citation statements)

References 39 publications

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“…Of course routing, as one of the most difficult problems in the area of the traditional IoT and there is some certain degree of mutual coupling with the MAC protocol, is also the key point of the research with respect to the emerging IoRT. The design of the routing protocol will be also seriously affected by the corresponding MAC protocol and the characteristics of IoRT such as longer transmission distance, huge propagation latency, extreme channel condition [10]. As a result, a significant challenge on the design of routing protocol for the applications of IoRT are posed due to the inherent characteristics of the physical medium.…”

Section: Background and Motivationmentioning

confidence: 99%

QoTa-MPR: QoS-oriented and traffic-aware multi-path routing protocol for internet of remote things

Liu

Guo

et al. 2021

Telecommun Syst

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Internet of Remote Things (IoRT) is widely used in both military and civilian applications. However, due to the unique characteristics, which is characterized as long-distance and high-latency, the design of the routing protocol is a great challenge of IoRT. In this paper, a QoS-oriented and traffic-aware multi-path routing protocol (QoTa-MRP) is proposed for IoRT. QoTa-MRP is composed of two parts. The first part is the link traffic-aware based muti-paths source route discovery mechanism, which is used to establish multipaths with lower link disjoint degree. The second part is path similarity and traffic priority based multi-path selection mechanism, which is used to determine the transmission mode of the traffic flows to enhance the reliability or effectiveness of the transmission. Simultaneously, the protocol is theoretically analyzed in terms of the successful transmission rate of routing transmission data packet. Finally, the dynamic source routing, which is a very representative protocol and is usually used as the baseline comparison protocol, is revisited for the performance verification of the QoTa-MRP in IoRT. It is shown in the simulation results that there are significant superiorities of QoTa-MRP than that of DSR in terms of network throughput, packet loss rate and routing packet header overhead in IoRT.

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Section: Background and Motivationmentioning

confidence: 99%

QoTa-MPR: QoS-oriented and traffic-aware multi-path routing protocol for internet of remote things

Liu

Guo

et al. 2021

Telecommun Syst

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“…Although fifth-generation (5G) wireless systems are being deployed around the world [1], the explosive growth of mobile data traffic still poses significant challenges for future networks, i.e., beyond 5G or sixthgeneration (6G). It is predicted that individual user data of satellite and UAVs in satellite-UAV-terrestrial network (ISUTN) [7], [16]- [18]. While [7], [16], [17] only considered dominated line-of-sight (LoS) channel in UAV communications, [18] proposed a general analytic framework for energy-efficient beamforming scheme of a satellite-aerial-terrestrial network (SATN).…”

Section: Introductionmentioning

confidence: 99%

“…It is predicted that individual user data of satellite and UAVs in satellite-UAV-terrestrial network (ISUTN) [7], [16]- [18]. While [7], [16], [17] only considered dominated line-of-sight (LoS) channel in UAV communications, [18] proposed a general analytic framework for energy-efficient beamforming scheme of a satellite-aerial-terrestrial network (SATN). Despite noticeable achievements for UAV communications [7], [16]- [18], aforementioned works did not take caching into account.…”

Section: Introductionmentioning

confidence: 99%

“…Unlike previous works that only investigated the integration between satellite and UAV [16]- [18] or UAV and caching [21]- [25], there are very few works on satelliteand cache-assisted UAV communication networks in the literature [26], [27]. Shushi et al [26] studied the energyaware coded caching design cache-enabled satellite-UAV vehicle integrated network (CSUVIN).…”

Section: Introductionmentioning

confidence: 99%

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Satellite- and Cache-Assisted UAV: A Joint Cache Placement, Resource Allocation, and Trajectory Optimization for 6G Aerial Networks

Tran

Chatzinotas

Ottersten

2022

IEEE Open J. Veh. Technol.

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This paper considers Low Earth Orbit (LEO) satellite-and cache-assisted unmanned aerial vehicle (UAV) communications for content delivery in terrestrial networks, which shows great potential for next-generation systems to provide ubiquitous connectivity and high capacity. Specifically, caching is provided by the UAV to reduce backhaul congestion, and the LEO satellite supports the UAV's backhaul link. In this context, we aim to maximize the minimum achievable throughput per ground user (GU) by jointly optimizing cache placement, the UAV's resource allocation, and trajectory while cache capacity and flight time are limited. The formulated problem is challenging to solve directly due to its non-convexity and combinatorial nature. To find a solution, the problem is decomposed into three sub-problems: (1) cache placement optimization with fixed UAV resources and trajectory, followed by (2) the UAV resources optimization with fixed cache placement vector and trajectory, and finally, (3) we optimize the UAV trajectory with fixed cache placement and UAV resources. Based on the solutions of sub-problems, an efficient alternating algorithm is proposed utilizing the block coordinate descent (BCD) and successive convex approximation (SCA) methods. Simulation results show that the max-min throughput and total achievable throughput enhancement can be achieved by applying our proposed algorithm instead of other benchmark schemes.

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“…Similarly, using drones as relays, Wang et al in [21] proposed a SAG-IoRT framework and designed an iterative algorithm via the joint optimization of the devices access scheduling, power control, and UAV trajectory to maximize the system throughput. While in [22], the authors used UAV to collect data for IoRT sensors with the assistance of low earth orbit (LEO) satellite networks. They designed column generation based algorithms to minimize the total UAVs' trajectory and transmission energy cost with the guarantee of IoRT demands.…”

Section: Introductionmentioning

confidence: 99%

Joint Gateway Selection and Resource Allocation for Cross-Tier Communication in Space-Air-Ground Integrated IoT Networks

2021

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LEO-Satellite-Assisted UAV: Joint Trajectory and Data Collection for Internet of Remote Things in 6G Aerial Access Networks

Cited by 174 publications

References 39 publications

QoTa-MPR: QoS-oriented and traffic-aware multi-path routing protocol for internet of remote things

QoTa-MPR: QoS-oriented and traffic-aware multi-path routing protocol for internet of remote things

Satellite- and Cache-Assisted UAV: A Joint Cache Placement, Resource Allocation, and Trajectory Optimization for 6G Aerial Networks

Joint Gateway Selection and Resource Allocation for Cross-Tier Communication in Space-Air-Ground Integrated IoT Networks

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