Analyze exploitability of evolutionary algorithms for positioning of drones acting as base stations (flying base stations) in mobile networks.

Analyze exploitability of evolutionary algorithms for positioning of drones acting as base stations (flying base stations) in mobile networks. Define a solution based on evolutionary algorithm enabling dynamic positioning of the flying base stations according to the actual position of mobile users and their requirements on communication. By means of simulations in Matlab, investigate network throughput in scenario with several flying base stations serving the mobile users . Compare the performance with a conventional scenario encompassing densely deployed conventional static small cells (without flying base stations). Scenario: 1)Static small BSs deployed in optimum position for initial drop of users (step 1, static) 2)FlyBSs deployed in optimum position for Step 1 (static) and then continuously updated according to mobility of users (in each step, new position of FlyBSs is derived) 3)The number of Static and Flying BSs [login to view URL] number of both – compare network performance [login to view URL] how many BSs can be saved if FlyBS concept is adopted Performance metrics: 1)Network capacity (sum of capacities of individual UEs) 2)UE’s energy consumption 3)FlyBS energy consumption for flying 4)Convergence time (number of iterations) Work plan: [login to view URL] architecture and concept of radio access network with drones [login to view URL] genetic algorithms (GA) and its application to positioning of drones -Fundamental idea, adaptive GA -Applications of GA -GA in mobile networks -GA for positioning of drones acting as a flying base station [login to view URL] MATLAB code with GA for positioning of the flying base stations -Understand code -Define a set of parameters potentially impacting on the performance [login to view URL] analysis -Scenario: --a street with N users walking along the street -Performance metrics: --max capacity (UL/DL), satisfaction with required capacity (Cue>Creq) 5. Figures ALL NECESSARY FILES ARE IN ZIP FILE. MAIN FILE: GA_MODIFIED