1. DOWNLINKS THROUGHPUT OPTIMIZATION IN UNMANNED AERIAL NETWORKS PhD candidate: Saadullah kalwar Principal Supervisor: A/Prof. Kwan-Wu Chin Co-supervisor: Dr. Raad Raad

2. Applications of Multi-UAV Networks Aerial Imaging Inspection & Monitoring Precision Agriculture Surveillance Mobile Base Stations Goods Delivery Computer Vision 2

3. Communication Requirements for UAVs Remote Piloting, Platform Safety and Sensor Data Quick Access Guarantee due to an UAV’s Mobility Strict Quality of Service Requirements Delay and Collisions 3

4. Problem Statement A number of UAVs communicating with a single ground station... DELAY & COLLISIONS 4

5. Research Goals Downlink Throughput Maximization for Multi-UAV Networks 5 Investigate the use of Successive Interference Cancellation in a Multi-UAV Network Investigate the effects of positioning of UAVs on downlink throughput Develop Methods that are Adaptive to Random Channel Gains Develop Distributed Algorithms for Multi-hop UAV Networks

6. Literature Review 6 No works have considered MACs for UAVs with SIC MAC for UAVs Focus on placement optimization rather than medium access Placement Optimization Papers focusing on traditional networks rather than UAVs MAC for WLANs Using MPR capabilities in traditional Wi-Fi environments MAC with Multiple Packet Reception

7. The Project 7 To devise a transmission schedule A schedule is the fewest number of time slots required for all UAVs to transmit at least once Aim Determine the position and orientation of UAVs Problem Transmission power, orientation and height of UAV Constraints

8. SIC Decoding Mechanism Enables a receiver to receive simultaneous transmissions 8 DATA 1DATA 2 COMPOSITE SIGNAL

9. 9 User 01 User 02 User 03 SIC Decoding Mechanism – How it works User 04 Step 01 Step 02 User 01 data decoded! User 02 data decoded! Received Power:

10. The Solution 10 Only two UAVs can transmit together! 0.727 0.992 1.76 2.8 SINR at the Ground Station (Suppose β=1 ) SIC capable ground station

11. The Solution 10 Three UAVs can transmit together after changing the orientation 0.727 1.09 1.76 2.8 SINR at the Ground Station (Suppose β=1 ) SIC capable ground station

12. An Example Transmission Schedule The example considers four (4) UAVs Each UAV has two (2) possible orientations 12 Time slot Active UAVs and their Orientation {A,B} 13A, 4A 22B, 3A, 4A 31A, 2B, 3A Aim Minimize Schedule Length

13. Problem 01 and 02 To devise a minimum length schedule by modifying the orientation of UAVs Objective Searching through all possible placements For example if number of UAVs is 20 and each UAV has three (3) orientations, total combinations = 20 3 Challenge To devise a minimum length schedule by modifying the altitude along with orientation of UAVs Hence, even bigger search space Problem 02 13

14. Problem 03 To consider imperfect channel state information To develop learning algorithms that allow UAVs to learn the best orientation while dealing with dynamic environment 14

15. Problem 04 To consider multi-hop UAV networks Challenge is to maintain list of neighbors for each UAV in a dynamic environment 15

16. Project timeline 16

17. 17 Thank you! questions ?

18. 18 Transmit Power (W) Channel gain Resulting SINR after Decoding UAV 1 24 0.800.727 UAV 20.500.992 UAV 30.351.76 UAV 40.202.8 Transmit Power (W) Channel gain Resulting SINR after Decoding UAV 1 24 0.800.727 UAV 20.601.09 UAV 30.351.76 UAV 40.202.8