Efficient Deployment of Small Cell Base Stations Mounted on Unmanned Aerial Vehicles for the Internet of Things Infrastructure

In the Internet of Things networks deploying fixed infrastructure is not always the best and most economical solution. Advances in efficiency and durability of Unmanned Aerial Vehicles (UAV) made flying small cell base stations (BS) a promising approach by providing coverage and capacity in environments where using fixed infrastructure is not economically justified. A key challenge in covering an area with UAV-based small cell BSs is optimal positioning the UAVs to maximize the coverage and minimize the number of required UAVs. In this paper, we propose an optimization problem that helps to determine the number and position of the UAVs. Moreover, to have efficient results in a reasonable time, we propose complementary heuristic methods that effectively reduce the search space. The simulation results show that our proposed method performs better than genetic algorithms.

[1]  Navi Mumbai,et al.  Implementing Genetic Algorithm to solve Facility Location Problem , 2015 .

[2]  Mohsen Guizani,et al.  Internet of Things: A Survey on Enabling Technologies, Protocols, and Applications , 2015, IEEE Communications Surveys & Tutorials.

[3]  Miao Pan,et al.  Efficient data collection for wireless rechargeable sensor clusters in Harsh terrains using UAVs , 2014, 2014 IEEE Global Communications Conference.

[4]  Halim Yanikomeroglu,et al.  Efficient 3-D placement of an aerial base station in next generation cellular networks , 2016, 2016 IEEE International Conference on Communications (ICC).

[5]  Kandeepan Sithamparanathan,et al.  Optimal LAP Altitude for Maximum Coverage , 2014, IEEE Wireless Communications Letters.

[6]  Janne J. Lehtomäki,et al.  Placement of 5G Drone Base Stations by Data Field Clustering , 2017, 2017 IEEE 85th Vehicular Technology Conference (VTC Spring).

[7]  Sanaa Sharafeddine,et al.  Optimized 3D Deployment of UAV-Mounted Cloudlets to Support Latency-Sensitive Services in IoT Networks , 2019, IEEE Access.

[8]  Walid Saad,et al.  Efficient Deployment of Multiple Unmanned Aerial Vehicles for Optimal Wireless Coverage , 2016, IEEE Communications Letters.

[9]  Walid Saad,et al.  Optimal transport theory for power-efficient deployment of unmanned aerial vehicles , 2016, 2016 IEEE International Conference on Communications (ICC).

[10]  Walid Saad,et al.  Mobile Internet of Things: Can UAVs Provide an Energy-Efficient Mobile Architecture? , 2016, 2016 IEEE Global Communications Conference (GLOBECOM).

[11]  Rui Zhang,et al.  Wireless communications with unmanned aerial vehicles: opportunities and challenges , 2016, IEEE Communications Magazine.

[12]  Walid Saad,et al.  Learning How to Communicate in the Internet of Things: Finite Resources and Heterogeneity , 2016, IEEE Access.

[13]  Evsen Yanmaz,et al.  Survey on Unmanned Aerial Vehicle Networks for Civil Applications: A Communications Viewpoint , 2016, IEEE Communications Surveys & Tutorials.

[14]  Walid Saad,et al.  Caching in the Sky: Proactive Deployment of Cache-Enabled Unmanned Aerial Vehicles for Optimized Quality-of-Experience , 2016, IEEE Journal on Selected Areas in Communications.

[15]  Rui Zhang,et al.  Placement Optimization of UAV-Mounted Mobile Base Stations , 2016, IEEE Communications Letters.

[16]  Walid Saad,et al.  Resource Allocation for Machine-to-Machine Communications with Unmanned Aerial Vehicles , 2016, 2016 IEEE Globecom Workshops (GC Wkshps).

[17]  Halim Yanikomeroglu,et al.  On the Number and 3D Placement of Drone Base Stations in Wireless Cellular Networks , 2016, 2016 IEEE 84th Vehicular Technology Conference (VTC-Fall).

[18]  Xianbin Cao,et al.  Proactive Drone-Cell Deployment: Overload Relief for a Cellular Network Under Flash Crowd Traffic , 2017, IEEE Transactions on Intelligent Transportation Systems.

[19]  Yang Sun,et al.  Location Optimization and User Association For Unmanned Aerial Vehicles Assisted Mobile Networks , 2019, IEEE Transactions on Vehicular Technology.

[20]  Mehdi Bennis,et al.  UAV-Assisted Heterogeneous Networks for Capacity Enhancement , 2016, IEEE Communications Letters.

[21]  Ismail Güvenç,et al.  UAV assisted heterogeneous networks for public safety communications , 2015, 2015 IEEE Wireless Communications and Networking Conference Workshops (WCNCW).

[22]  Halim Yanikomeroglu,et al.  Backhaul-aware robust 3D drone placement in 5G+ wireless networks , 2017, 2017 IEEE International Conference on Communications Workshops (ICC Workshops).

[23]  Walid Saad,et al.  Mobile Unmanned Aerial Vehicles (UAVs) for Energy-Efficient Internet of Things Communications , 2017, IEEE Transactions on Wireless Communications.

[24]  Halim Yanikomeroglu,et al.  3-D Placement of an Unmanned Aerial Vehicle Base Station (UAV-BS) for Energy-Efficient Maximal Coverage , 2017, IEEE Wireless Communications Letters.

[25]  Ilker Bekmezci,et al.  Flying Ad-Hoc Networks (FANETs): A survey , 2013, Ad Hoc Networks.

[26]  Walid Saad,et al.  Drone Small Cells in the Clouds: Design, Deployment and Performance Analysis , 2014, 2015 IEEE Global Communications Conference (GLOBECOM).

[27]  Halim Yanikomeroglu,et al.  Backhaul-Aware Optimization of UAV Base Station Location and Bandwidth Allocation for Profit Maximization , 2018, IEEE Access.

[28]  Said Salhi,et al.  Discrete Location Theory , 1991 .

[29]  Bülent Tavli,et al.  UAV Base Station Location Optimization for Next Generation Wireless Networks: Overview and Future Research Directions , 2018, 2019 1st International Conference on Unmanned Vehicle Systems-Oman (UVS).