Spectrum allocation and performance analysis for backhauling of UAV assisted cellular network

Lei, Jiansheng; Chen, Jingran; Zhang, Feng

doi:10.23919/jcc.2019.08.008

Cited by 10 publications

(6 citation statements)

References 18 publications

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“…Furthermore, by considering a resilient communication network to continue operations after a calamity, the co-existence of UAVs that were carrying small cells and cellular networks was investigated, the effects of the number of UAVs and their altitudes on the performance of ground users were analyzed in [20]. Moreover, a backhaul scheme was proposed to solve the extra interference caused by the wireless backhaul link in [21]. Different from the existing works that analyzed altitudes of UAVs in the performance analysis of the network, the positions of UAVs in UAV-assisted wireless networks were optimized in [22,23], and the transmission power of UAVs was analyzed in [24].…”

Section: Related Workmentioning

confidence: 99%

Modeling and Performance Analysis in UAV-Assisted Cellular Networks with Clustered Edge Users

Yao

Zhu

et al. 2022

Electronics

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A UAV-assisted cellular network can provide ubiquitous links to everything and it is considered to be one of the key technologies for 6G wireless networks. In this paper, we consider an uplink wireless network with a macrobase station (MBS) and cellular users. However, the coverage equality of edge users cannot be guaranteed in scenarios where data service is dense. Specifically, a novel topology of the UAV-assisted wireless network is considered. UAVs are deployed upon the cell edge to serve edge users with poor communication quality. To avoid larger interference caused by users and UAVs in the overlapping area, the locations of these UAVs are modeled as a homogeneous Poisson point process (HPPP) under the Poisson cluster distance constraint (PCDC). In addition, we assume that edge users cluster around each UAV and model their locations as Poisson cluster processes (PCPs). Initially, the Laplace transforms of intra-cluster interference, inter-cluster interference, and other interference are derived. Subsequently, coverage probability and area spectrum efficiency are derived for UAVs and MBS using tools from stochastic geometry. Moreover, the energy efficiency of the system is obtained. Simulation results are examined to validate the accuracy of theoretical analysis and provide insights into the effects of the system parameters as well as useful guidelines for practical system design.

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Section: Related Workmentioning

confidence: 99%

Modeling and Performance Analysis in UAV-Assisted Cellular Networks with Clustered Edge Users

Yao

Zhu

et al. 2022

Electronics

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“…Also, optimal placement can result in improved throughput, better QoS, and reduced delay. Further, a UAV‐assisted network requires additional backhaul for UAVs to connect with the terrestrial network leading to severe resource allocation challenges 17 . This calls for new resource allocation and spectrum sharing schemes to be devised for the two systems to coexist.…”

Section: Introductionmentioning

confidence: 99%

“…Further, a UAV-assisted network requires additional backhaul for UAVs to connect with the terrestrial network leading to severe resource allocation challenges. 17 This calls for new resource allocation and spectrum sharing schemes to be devised for the two systems to coexist. Resource allocation can involve different network resources, including communication (such as bandwidth, transmit power, etc.)…”

Section: Introductionmentioning

confidence: 99%

Resource optimization in UAV‐assisted wireless networks—A comprehensive survey

Basharat

Naeem

Qadir

et al. 2022

Trans Emerging Tel Tech

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Unmanned aerial vehicles (UAVs) are inevitable to meet the requirements of future wireless networks. Recently, researchers have investigated diverse issues related to UAV‐assisted networks (including placement of UAVs, resource management, and spectrum sharing) for a broad range of applications, including disaster management, data collection from the ground sensor network, surveillance, logistic support, etc. This article presents a comprehensive survey of recent advances in UAV‐assisted networks. We mainly emphasize the optimization perspective of UAV‐assisted wireless networks with different objectives, including coverage area, throughput, energy efficiency, quality of service, delay, and outage probability. We provide a detailed discussion for each objective with their constraints, optimization problem, solution approach, and performance metrics. We also provide relationships among different objectives and parameters considered in the literature. Finally, we list open research issues and future research directions to improve UAV‐assisted wireless networks in the context of optimization.

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“…The UAVs' trajectory and user partitioning were optimized to maximize the minimum throughput of all users. The UAVs were deployed to offer mmWave access for users who could not be served by macro cells due to blocking or interfering, where different backhauling modes were investigated [18]. In [19], the offloading from ground base stations to UAVs was analyzed, where UAVs hover at the typical location of the cell center in a quasi-static manner as a second layer to serve a portion of the users.…”

Section: Introductionmentioning

confidence: 99%

On the Performance of UAV-Aided Content Caching in Small-Cell Networks with Joint Transmission

2021

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Unmanned aerial vehicles (UAVs), featured by the high-mobility and high-quality propagation environment, have shown great potential in wireless communication applications. In this paper, a novel UAV-aided small-cell content caching network is proposed and analyzed, where joint transmission (JT) is considered in the dense small-cell networks and mobile UAVs are employed to shorten the serving distance. The system performance is evaluated in terms of the average cache hit probability and the ergodic transmission rate. From the analytical results, we find that (i) the proposed UAV-aided small-cell network shows superior caching performance and, even with a small density of UAVs the system’s cache hit probability, can be improved significantly; (ii) the content’s optimal caching probability to maximize the cache hit probability is proportional to the (K+1)-th root of its request probability, where K is the number of small-cell base stations that serve each user by JT; (iii) caching the most popular content in UAVs may lead to a low transmission rate due to the limited resource offered by the low-density UAVs. Simulation results are presented to validate the theoretical results and the performance gain achieved by the optimal caching strategy.

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Spectrum allocation and performance analysis for backhauling of UAV assisted cellular network

Cited by 10 publications

References 18 publications

Modeling and Performance Analysis in UAV-Assisted Cellular Networks with Clustered Edge Users

Modeling and Performance Analysis in UAV-Assisted Cellular Networks with Clustered Edge Users

Resource optimization in UAV‐assisted wireless networks—A comprehensive survey

On the Performance of UAV-Aided Content Caching in Small-Cell Networks with Joint Transmission

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