This material is based upon work supported by the National Science Foundation under Grant Number (NSF Grant Number) CNS-1814748. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.

Free Space Optics as Backhaul and Energizer for Drone-assisted Networking

PI: Nirwan Ansari

Graduate Students: Qiang Fan, Abdullah Ridwan Hossain, Mohammad Arif Hossain, Weiqi Liu, Xilong Liu, Jingjing Yao, Liang Zhang, and Shuai Zhang

Project Summary:

SoarNet (free Space Optics as bAckhaul and energizeR for drone-assisted NETworking) aims to simultaneously and rapidly transmit data and energy from an access node to a Drone-mounted Base Station (DBS), which can be flexibly deployed to provision wireless broadband access. That is, the DBS can simultaneously receive high-speed data streams and energy via optical beams. The received energy is used to power the DBS to prolong its flight and received data streams are delivered to Mobile Users (MUs) via existing Radio Frequency (RF) channels. SoarNet will be a game changer for mobile access. By leveraging Free Space Optics (FSO) communications and the drone-assisted mobile networking framework, SoarNet will significantly enhance the throughput of the network and Quality of Service (QoS) of MUs and will advance the state of the art of wireless networking and wireless charging. Proposed research activities will advance the understanding of simultaneously charging the DBS and transmitting data at high speed.

Research Endeavors:

SoarNet, as shown in Figure 1, comprises three major research endeavors. 1) Actualizing the SoarNet architecture to construct a FSO transmitter at an access node and a FSO receiver at a DBS to provision simultaneous energy transfer and data transmission; meanwhile, two mathematical models will be derived to estimate the charging rate by applying FSO as a charger and the transmission rate by applying FSO communications as wireless backhauling. 2) 3D DBS placement in SoarNet, to determine the longitude, latitude, and altitude of the DBS to maximize the throughput of delivering data to MUs in the access network, while guaranteeing the requirement of the DBS's charging rate. 3) Dynamic access node association and MU association, to associate the DBS with an access node (i.e., the DBS receives the data streams and energy from the access node) and adjusts the MU association area of the DBS (i.e., more/less MUs are associated with the DBS to download their data) in order to balance the traffic loads among access nodes, thus further improving the quality of service (QoS) in terms of the average delay of downloading data to MUs.

netarch

Figure 1. Drone-assisted Access Networks

Products

Journals:

  1.  S. Zhang, W. Liu, and N. Ansari, “Completion Time Minimization for Data Collection in a UAV-enabled IoT Network: A Deep Reinforcement Learning Approach,” IEEE Trans. on Vehicular Technology , DOI: 10.1109/TVT.2023.3280848, vol. 72,2, no. 11, pp. 14734 - 14742, Nov. 2023.

  2.  A.R. Hossain, M.A. Hossain, and N. Ansari, “Dual-Band Aerial Networks for Priority-Based Traffic,” IEEE Trans. on Vehicular Technology , DOI: 10.1109/TVT.2023.3251320, vol. 72, no. 7, pp. 9500-9510, July 2023.

  3.  L. Zhang, B. Jabbari, and N. Ansari, “Deep Reinforcement Learning Driven UAV-Assisted Edge Computing,” IEEE Internet of Things, DOI: 10.1109/JIOT.2022.3196842, vol. 9 no. 24, pp. i25449-25459, Dec. 2022.

  4.  M.A. Hossain, A.R. Hossain, and N. Ansari, “Numerology-Capable UAV-MEC for Future Generation Massive IoT Networks,” IEEE Internet of Things, DOI: 10.1109/JIOT.2022.3189945, vol. 9 no. 23, pp. 23860-23868, Dec. 2022.

  5.  S. Zhang, W. Liu, and N. Ansari, “Joint Wireless Charging and Data Collection forUAV-Enabled Internet of Things Network,” IEEE Internet of Things Journal, DOI: 10.1109/JIOT.2022.3190813, vol. 9, no. 23, pp. 23852-23859, Dec. 2022.

  6.  J. Yao and N. Ansari, “Secure Federated Learning by Power Control for Internet of Drones,” IEEE Trans. Cognitive Communications and Networking, DOI: 10.1109/TCCN.2021.3076167, vol. 7 no. 4, pp. 1021-1031, Dec. 2021.

  7.  J. Zhang and N. Ansari, “Optimizing the Operation Cost for UAV-aided Mobile Edge Computing,” IEEE Transactions on Vehicular Technology, DOI: 10.1109/TVT.2021.3076980, vol. 70, no. 6, pp. 6085-6093, June 2021.

  8.  J. Yao and N. Ansari, “Wireless Power and Energy Harvesting Control in IoD by Deep Reinforcement Learning,” IEEE Trans. Green Communications and Networking, DOI: 10.1109/TGCN.2021.3049500,vol. 5, no. 2, pp. 980-989, June 2021.

  9.  L. Zhang and N. Ansari, “ Latency-aware IoT Service Provisioning in UAV-aided Mobile Edge Computing Networks,” IEEE Internet of Things Journal , DOI: 10.1109/JIOT.2020.3005117, vol. 7, no. 10, pp. 10573-10580, Oct. 2020.

  10.  D. Wu, X. Sun, and N. Ansari, “An FSO-based Drone Assisted Mobile Access Network for Emergency Communications,” IEEE Transactions on Network Science and Engineering, DOI: 10.1109/TNSE.2019.2942266, vol. 7, no. 3, pp. 1597-1606, Sep. 2020.

  11.  N. Ansari, D. Wu, and X. Sun, “FSO as backhaul and energizer for drone-assisted mobile access networks,” ICT Express, DOI: 10.1016/j.icte.2019.12.002, vol. 6, no. 2, pp. 139-144, Jun. 2020.

  12.  J. Zhang and N. Ansari, “Online Task Allocation and Flying Control in Fog-Aided Internet of Drones,” IEEE Transactions on Vehicular Technology, DOI: 10.1109/TVT.2020.2982172, vol. 69, no. 5, pp. 5562-5569, May 2020.

  13.  N. Ansari and L. Zhang, “Flexible Backhaul-aware DBS-aided HetNet with IBFD Communications,” ICT Express, DOI: 10.1016/j.icte.2019.08.003, vol. 6, no. 1, pp. 48-56, Mar. 2020.

  14.  N. Ansari and L. Zhang, “3D Drone Base Station Placement and Resource Allocation With FSO-Based Backhaul in Hotspots,” IEEE Transactions on Vehicular Technology, DOI: 10.1109/TVT.2020.2965920, vol. 6, no. 1, pp. 48-56, Mar. 2020.

  15.   X. Sun, N. Ansari, and R. Fierro, “Jointly Optimized 3D Drone Mounted Base Station Deployment and User Association in Drone Assisted Mobile Access Network,” IEEE Open Journal of Vehicular Technology (OJVT), DOI: 10.1109/TVT.2019.2961086, vol. 69, no. 2, pp. 2195-2203, Feb. 2020.

  16.  L. Zhang and N. Ansari, “Optimizing the Deployment and Throughput of DBSs for Uplink Communications,” IEEE Open Journal of Vehicular Technology (OJVT), DOI: 10.1109/OJVT.2019.2954390, vol. 1, pp. 18-28, Jan. 2020.

  17.   N. Ansari, Q. Fan, X. Sun and L. Zhang, “SoarNet,” IEEE Wireless Communications,, DOI: 10.1109/MWC.001.1900126, vol. 26, no. 6, pp. 37-43, Dec. 2019.

  18.  L. Zhang and N. Ansari, “A Framework for 5G Networks with In-band Full-duplex Enabled Drone-mounted Base-stations,” IEEE Wireless Communications,, DOI: 10.1109/MWC.2019.1800486, vol. 26, no. 5, pp. 121-127, Oct. 2019.

  19.  L. Zhang and N. Ansari, “Approximate Algorithms for 3-D Placement of IBFD Enabled Drone-mounted Base-Stations,” IEEE Trans. Vehicular Technology, DOI: 10.1109/TVT.2019.2923143, vol. 68, no. 8, pp. 7715-7722, Aug. 2019.

  20.  J. Yao and N. Ansari, “QoS-Aware Power Control in Internet of Drones for Data Collection Service,” IEEE Trans. Vehicular Technology, DOI: 10.1109/TVT.2019.2915270, vol. 68, no. 7, pp. 6649-6656, July 2019.

  21. Q. Fan and N. Ansari, “Towards Traffic Load Balancing in Drone-assisted Communications for IoT,” IEEE Internet of Things Journal, DOI: 10.1109/JIOT.2018.2889503, vol. 6, no. 2, pp. 3633-3640, Apr. 2019.

  22. X. Liu and N. Ansari, “Resource Allocation in UAV-assisted M2M Communications for Disaster Rescue,” IEEE Wireless Communications Letters, DOI: 10.1109/LWC.2018.2880467, vol. 8, no. 2, pp. 580-583, Apr. 2019.

  23. L. Zhang and N. Ansari, “On the Number and 3-D Placement of In-Band Full-Duplex Enabled Drone-mounted Base-stations,” IEEE Wireless Communications Letters, DOI: 10.1109/LWC.2018.2867501, vol. 8, no.1, pp. 221-224, Feb. 2019.

Conferences:

  1.  J. Yao and N. Ansari, “Power Control in Internet of Drones by Deep Reinforcement Learning,” Proc. 2020 International Conference on Communications (ICC 2020), Virtual Conference, DOI: 10.1109/ICC40277.2020.9148749, Jun. 7-11, 2020.

  2.  J. Yao and N. Ansari, “Joint Drone Association and Content Placement in Cache-Enabled Internet of Drones,” Proc. 2019 IEEE Global Communications Conference (GLOBECOM 2019), DOI: 10.1109/GLOBECOM38437.2019.9013274, Waikoloa, HI, USA, Dec. 9-13, 2019.

  3.   L. Zhang and N. Ansari, “Backhaul-aware Uplink Communications in Full-Duplex DBS-aided HetNets,” Proc. 2019 IEEE Global Communications Conference (GLOBECOM 2019), DOI: 10.1109/GLOBECOM38437.2019.9013471, Waikoloa, HI, USA, Dec. 9-13, 2019.

  4.  D. Wu, X. Sun, and N. Ansari, “A Cooperative Drone Assisted Mobile Access Network for Disaster Emergency Communication,” Proc. 2019 IEEE Global Communications Conference (GLOBECOM 2019), DOI: 10.1109/GLOBECOM38437.2019.9013813, Waikoloa, HI, USA, Dec. 9-13, 2019.

  5.   J. Yao and N. Ansari, “QoS-Aware Rechargeable UAV Trajectory Optimization for Sensing Service,” Proc. 2019 IEEE International Conference on Communications (ICC 2019), Shanghai, China, May 20-24, 2019.

 

Completed Doctoral Dissertations:

[1]   Liang Zhang. Communications with Spectrum Sharing in 5G Networks via Drone-Mounted Base Stations. (2020). Electrical Engineering. New Jersey Institute of Technology.

[2]   Jingjing Yao. Intelligent and Secure Fog-aided Internet of Drones. (2021). Computer Engineering. New Jersey Institute of Technology.

[3]   Shuai Zhang. Resource Allocation, User Association and Placement for UAV-assisted Communications. (2022). Electrical Engineering. New Jersey Institute of Technology.

[4]   Abdullah Ridwan Hossain. 5G New Radio Access and Core Network Slicing for Next-Generation Network Services and Management. (2023). Electrical Engineering. New Jersey Institute of Technology.