Multiple Drone-Cell Deployment Analyses and Optimization in Drone Assisted Radio Access Networks

Shi, Weisen; Li, Junling; Xu, Wenchao; Zhou, Haibo; Zhang, Ning; Zhang, Shan; Shen, Xuemin

doi:10.1109/access.2018.2803788

Cited by 121 publications

(62 citation statements)

References 24 publications

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“…By allocating different carrier frequencies, the interference between D2U and D2B communication can be prevented. Initial height h 0 is set to 80 m within the working-zone of DBS over the whole BS radio coverage area [34]. We treat δ t as the minimal time unit to calculate related variables including V max , H max , etc.…”

Section: Numerical Resultsmentioning

confidence: 99%

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Multi-Drone 3-D Trajectory Planning and Scheduling in Drone-Assisted Radio Access Networks

Shi

Cheng

et al. 2019

IEEE Trans. Veh. Technol.

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Drone base station (DBS) is a promising technique to extend wireless connections for uncovered users of terrestrial radio access networks (RAN). To improve user fairness and network performance, in this paper, we design 3D trajectories of multiple DBSs in the drone assisted radio access networks (DA-RAN) where DBSs fly over associated areas of interests (AoIs) and relay communications between the base station (BS) and users in AoIs. We formulate the multi-DBS 3D trajectory planning and scheduling as a mixed integer non-linear programming (MINLP) problem with the objective of minimizing the average DBS-to-user (D2U) pathloss. The 3D trajectory variations in both horizontal and vertical directions, as well as the stateof-the-art DBS-related channel models are considered in the formulation. To address the non-convexity and NP-hardness of the MINLP problem, we first decouple it into multiple integer linear programming (ILP) and quasi-convex sub-problems in which AoI association, D2U communication scheduling, horizontal trajectories and flying heights of DBSs are respectively optimized. Then, we design a multi-DBS 3D trajectory planning and scheduling algorithm to solve the sub-problems iteratively based on the block coordinate descent (BCD) method. A k-meansbased initial trajectory generation and a search-based start slot scheduling are considered in the proposed algorithm to improve trajectory design performance and ensure inter-DBS distance constraint, respectively. Extensive simulations are conducted to investigate the impacts of DBS quantity, horizontal speed and initial trajectory on the trajectory planning results. Compared with the static DBS deployment, the proposed trajectory planning can achieve 10-15 dB reduction on average D2U pathloss, and reduce the D2U pathloss standard deviation by 68%, which indicate the improvements of network performance and user fairness.

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Section: Numerical Resultsmentioning

confidence: 99%

“…It is worth noting that the feasible region of l d [n] constrained by (8m) can form a convex set in any X-Y plane by ignoring the working-zone burst close to the BS antenna [34].…”

Section: Dbs Horizontal Trajectory Optimizationmentioning

confidence: 99%

Multi-Drone 3-D Trajectory Planning and Scheduling in Drone-Assisted Radio Access Networks

Shi

Cheng

et al. 2019

IEEE Trans. Veh. Technol.

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“…The optimal 3D deployment of drones for extending the coverage area and enhancing the QoS is discussed in [56]. The idea is supported by a study [57] that discusses the 3D deployment of a multiple drone base station to maximize the coverage area and maintain the link quality between drones and the ground station by using the practical swarm optimization technique. Furthermore, drones' 3D deployment represents a key technology that can assess drones to deliver network services for public safety and disaster management.…”

Section: Drones For Public Safetymentioning

confidence: 99%

Collaboration of Drone and Internet of Public Safety Things in Smart Cities: An Overview of QoS and Network Performance Optimization

Alsamhi

Ansari

et al. 2019

Drones

113

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This paper studies the network performance of collaboration between the Internet of public safety things (IoPST) and drones. Drones play a vital role in delivering timely and essential wireless communication services for the recovery of services right after a disaster by increasing surge capacity for the purposes of public safety, exploring areas that are difficult to reach, and providing an area of rapid coverage and connectivity. To provide such critical facilities in the case of disasters and for the purposes of public safety, collaboration between drones and IoPST is able to support public safety requirements such as real-time analytics, real-time monitoring, and enhanced decision-making to help smart cities meet their public safety requirements. Therefore, the deployment of drone-based wireless communication can save people and ecosystems by helping public safety organizations face threats and manage crises in an efficient manner. The contribution of this work lies in improving the level of public safety in smart cities through collaborating between smart wearable devices and drone technology. Thus, the collaboration between drones and IoPST devices establishes a public safety network that shows satisfying results in terms of enhancing efficiency and information accuracy.

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“…Since (7a) can reach its minimal value when r u,d [n] = min r u,d [n] for any r u,d [n] within its available range, the objective of minimizing (7a) equals minimizing r u,d [n] 2 , which is a quadratic convex function for R d [n]. On the other hand, [18] proves that the available range of R d [n] for constraint (7k) forms a convex set in X-Y plane. Therefore, the sub-problem to find optimal R d [n] can be formulated as…”

Section: D Multi-dc Trajectory Design Algorithmmentioning

confidence: 99%

“…Since most existing trajectory planning results are based on different D2G channel models with fixed-height (i.e. [13]), we choose one static DC deployment algorithm, the per-drone iterated particle swarm optimization (DI-PSO) algorithm [18], as the benchmark to highlight the efficiency of our proposed algorithm. The average U2D pathloss performance achieved by the proposed 3D multi-DC trajectory design algorithm, as well as the static DC deployment scheme are compared in Fig.…”

mentioning

confidence: 99%

3D Multi-Drone-Cell Trajectory Design for Efficient IoT Data Collection

Shi¹,

Li²,

Cheng³

et al. 2019

ICC 2019 - 2019 IEEE International Conference on Communications (ICC)

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Drone cell (DC) is an emerging technique to offer flexible and cost-effective wireless connections to collect Internetof-things (IoT) data in uncovered areas of terrestrial networks. The flying trajectory of DC significantly impacts the data collection performance. However, designing the trajectory is a challenging issue due to the complicated 3D mobility of DC, unique DC-to-ground (D2G) channel features, limited DC-to-BS (D2B) backhaul link quality, etc. In this paper, we propose a 3D DC trajectory design for the DC-assisted IoT data collection where multiple DCs periodically fly over IoT devices and relay the IoT data to the base stations (BSs). The trajectory design is formulated as a mixed integer non-linear programming (MINLP) problem to minimize the average user-to-DC (U2D) pathloss, considering the state-of-the-art practical D2G channel model. We decouple the MINLP problem into multiple quasi-convex or integer linear programming (ILP) sub-problems, which optimizes the user association, user scheduling, horizontal trajectories and DC flying altitudes of DCs, respectively. Then, a 3D multi-DC trajectory design algorithm is developed to solve the MINLP problem, in which the sub-problems are optimized iteratively through the block coordinate descent (BCD) method. Compared with the static DC deployment, the proposed trajectory design can lower the average U2D pathloss by 10-15 dB, and reduce the standard deviation of U2D pathloss by 56%, which indicates the improvements in both link quality and user fairness.

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Multiple Drone-Cell Deployment Analyses and Optimization in Drone Assisted Radio Access Networks

Cited by 121 publications

References 24 publications

Multi-Drone 3-D Trajectory Planning and Scheduling in Drone-Assisted Radio Access Networks

Multi-Drone 3-D Trajectory Planning and Scheduling in Drone-Assisted Radio Access Networks

Collaboration of Drone and Internet of Public Safety Things in Smart Cities: An Overview of QoS and Network Performance Optimization

3D Multi-Drone-Cell Trajectory Design for Efficient IoT Data Collection

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