## 8 Energy Optimization Techniques in UAV-Based Cellular Networks
### Conventional Approaches  
In [201], the authors proposed a flight and communication protocol where the UAV-BS's speed, height, and beamwidth are jointly designed to minimize the flight time and energy consumption while serving ground users. The authors in [113] investigated energy-efficient UAV-BS's communication with ground users based on trajectory optimization by considering both the throughput and energy consumption of the UAV-BS. A propulsion power consumption model for fixed-wing UAVs was first introduced, then both unconstrained and constrained trajectory optimization was considered for energy efficient UAV-assisted communications. The former trajectory optimization was proven to be energy inefficient while, for the latter, an energy efficient algorithm based on both linear state space and sequential convex optimization was developed to optimize the communication of the UAV-BS. The work in [25] considered energy-efficient UAV communication of rotary-wing UAV-BSs. A theoretical model of the mobility power consumption was first derived, followed by formulating the UAV energy minimization problem, which jointly optimizes its trajectory, time spent communicating with ground users, and mission completion time. To solve this optimization problem, two solution approaches were considered. In the first approach, a flight-hover communication design was considered where the UAV-BS only visits the optimal hovering location and communicates with the user in that location. As such, the energy minimization problem becomes that of finding the optimal hovering location, duration, visiting order, and speed; additionally, a convex optimization with traveling salesman algorithm was developed to tackle this problem. For the second solution approach, the energy minimization problem was modeled as a path selection problem, then an iterative algorithm based on SCA was developed to update both the trajectory and time allocated to the UAV-BS for communication. EE of UAV communication based on trajectory design was studied in [145]. The optimization problem comprises both the throughput and propulsion energy consumption of the UAV-BS. A heuristic algorithm based on SCA and the classical Dinkelbach approach was developed to find the optimal energy efficient strategy for the UAV-BS. The authors of [26] considered a joint optimization of the 3D trajectory and transmission power of a multi-UAV based relaying system in order to maximize user throughput. A heuristic algorithm based on the block coordinate ascent (BCA) technique was proposed to solve the developed problem. In [202], the authors considered energy minimization problem in UAV-based networks by jointly optimizing the trajectory and velocity of the UAV while respecting latency constraints. First, both heuristic and dynamic programming algorithms were proposed to determine the optimal set of trajectories, after which the UAV velocity of each trajectory was also optimized to ensure that the total energy consumption of the network is minimized. The authors in [203] investigated energy-aware trajectory optimization that minimizes the on-board energy consumption in the UAV-BS while satisfying the data requirement of ground users. A double loop iterative algorithm was proposed to determine the optimal trajectory of the UAV that would maximize user coverage. A combined optimization of both the trajectory and transmit power of a UAV relay network was carried out in [204]. They first derived an analytic expression for the outage probability, after which a heuristic algorithm was developed for power control and trajectory optimization. The work in [70] investigated the application of UAV-BSs for backhaul connection to terrestrial BSs during post-disaster scenarios. An energy-efficient trajectory design based on GA was proposed to select the optimal trajectory that results in the least energy consumption in the UAV. The trade-off in energy consumption between ground terminals and UAV-BSs was studied using the trajectory design in [205].