## 6 Types of Energy Optimization in UAV-Based Cellular Networks  
The energy consumption of UAVs is one of the major challenges that limit their applications in many areas including in wireless communications networks [18; 111]. As 5G and beyond networks target drastic improvement in network EE, the use of UAV-BSs, though very promising, could be a hindrance to the actualization of this objective if the issue of increased energy consumption is not carefully considered [19]. Since UAVs are designed to fly from one location to another, their application in cellular networks brings a lot of flexibility and adaptability to the network as they can be deployed on demand to various parts of the network to handle different challenges ranging from network restoration, coverage and capacity enhancement, traffic offloading, load balancing, backhauling, etc., as mentioned in Section 2. However, the large amount of energy consumption involved in flying or hovering the UAV to or over the service area makes their use very challenging. Although various UAV power supply and charging mechanisms were discussed in Section 3, it is still very important to optimize the energy consumption of the UAV-BSs because of the limitations of these methods including low energy storage capacity, need for frequent recharging, low energy conversion efficiency, unpredictability of renewable energy sources, etc., which can negatively impact the performance of UAVs in wireless networks [46]. In addition, most energy optimization techniques are easier and less expensive to implement compared with the various power supply and recharging techniques discussed in Section 3. Therefore, in this section, we highlight the major areas of energy optimization, while in subsequent sections, we review the various algorithms that have been proposed for tackling the energy optimization problems identified in this section. There are four major aspects of energy optimization in UAV-based cellular networks:  
1. _Optimization of the Propulsion Energy_ The propulsion energy is the energy consumption associated with flying or hovering the UAV-BSs over the service area. This is the most significant energy consumption of the UAV-BS [19]. Hence, energy optimization strategies proposed in this direction aim at reducing the energy consumption due to the movement of the UAV-BS. In this regard, a few models to quantify the energy consumption of the UAV due to propulsion were developed in [25; 113; 114]. In addition, various approaches to minimize the propulsion energy consumption have been introduced, including regulating UAV altitude and planning the trajectory, etc. [70; 113; 115]. 2. _Optimization of the Communication Energy_ Communication energy is the energy consumption associated with signal processing and data transmission during the UAV operation in wireless communication networks. This is usually less significant compared with the energy consumption due to propulsion [19], therefore, energy optimization approaches proposed in this area are targeted at reducing the energy consumed while processing and transmitting user information. The techniques proposed in this area include transmission power allocation and control, scheduling the transmission of UAV-BSs--particularly for the cases where they need to fly over a predefined trajectory, and optimally positioning UAVs in a service area [116; 117; 118; 119]. 3. _Joint Optimization of the Communication and Propulsion Energy_ Unlike the first and second cases that consider optimizing either the communication or propulsion energy consumption, the works conducted in this direction consider the simultaneous optimization of both the communication and propulsion energy consumption of UAV-BSs. These approaches result in the most energy conservation as both components of the UAV-BS energy consumption are considered together. The strategies considered in this area involve a combination of the approaches proposed in propulsion energy optimization as well as that of communication energy optimization [25; 120]. 4.