## 8 Energy Optimization Techniques in UAV-Based Cellular Networks
### Conventional Approaches
A gradient descent algorithm was then proposed to find the optimal altitude of the UAV-BSs. The authors of [182] considered the importance of the on-board circuit power consumption of the UAVs while addressing the problem of their optimal 3D placement in order to maximize the network lifetime. Then, using an analytical approach, the optimal hovering altitude of the UAV-BSs with respect to their coverage radius was derived to determine the coverage and on-board circuit power parameters that result in minimum power consumption. The work in [183] considered the energy efficient placement of UAV-BSs for data collection from ground users based on NOMA. A heuristic algorithm was proposed to determine the optimal hovering height of the UAV-BS that maximizes the EE of the network. The authors in [184] proposed a joint 3D location and transmit power optimization scheme for UAV-based relay networks to maximize the sum rate of users. A heuristic algorithm based on alternating descent and SCA was developed to solve the optimization problem. The authors in [185] proposed a joint optimization scheme for both the 3D placement and pathloss factor with the aim of achieving maximum energy-efficient coverage. A heuristic algorithm was developed to find the optimal UAV placement and compensation factor that maximizes the energy efficient coverage. An optimal UAV placement framework that aims to find the optimal UAV locations that is required to minimize the total energy consumption of the network while providing a target coverage was introduced in [186]. Both centralized and localized heuristic algorithms were developed to determine the optimal UAV locations for both static and mobile users. The authors of [187] considered the joint optimization of the transmission power and location of UAV-BS in a relay NOMA network to minimize the power consumption of the network. A double loop iterative algorithm was developed to solve the joint optimization problem. In [188], the optimal 3D placement for UAVs serving as relays in IoT communications was considered in order to minimize the transmission power of the UAVs while considering the outage probability of the IoT devices. A 3D placement algorithm based on PSO was developed to minimize the transmitted power in both air-to-ground and ground-to-air links. The case of energy efficient UAV placements in indoor environments for emergency wireless coverage was considered in [189]. Both iterative and exhaustive search algorithms were developed to determine the optimal position of the UAV in order to minimize the transmission power. Similarly, the authors in [190] investigated the optimal positioning of a UAV-BS for seamless IoT connectivity in an indoor environment comprising multiple users at random locations in order to minimize the transmit power of the UAV-BS. An energy-efficient low-complexity heuristic algorithm was developed to solve the optimal UAV placement problem. The authors in [191] proposed a UAV-BS deployment and scheduling mechanism to ensure optimal placement and effective management of UAV-BS operations while minimizing energy consumption and ensuring maximum coverage. To achieve these objectives, heuristic algorithms were proposed to ensure the UAVs are placed in the right locations as well as manage their battery recharging cycle. The authors of [192] investigated EE maximization in UAV-assisted NOMA based network via a joint optimization of UAV placement and power allocation while considering QoS constraints. The joint optimization problem was modeled as a non-linear fractional problem, then an alternating algorithm based on a nested Dinkelbach structure was proposed to find the optimal solution. The work in [193] studied the joint optimization of the UAV location and transmit power in a NOMA-based UAV network while considering the decoding order. The joint optimization problem was first divided into two sub-problems, after which an iterative algorithm was proposed to solve the optimization problem alternately.