# Handover Management for Drones in Future Mobile Networks--A Survey
## 6 Related Works
### Classical Based Techniques for Handover Management
The assessed parameters included the RSRP, the Physical Cell Identity (PCI), and the RSP quality of the radio and sensor data. To establish an efficient handover algorithm, one must consider the outcomes of this algorithm. In 2015 [108], the authors conducted research on optimal coverage control for net-drone handover. The authors in this paper proposed a coverage decision algorithm, which aims to offer seamless handover and complete coverage for the connected drones' network. The authors presented an algorithm based on the RSS. The algorithm adjusts the drone's altitude and separation distance. The proposed coverage decision algorithm is evaluated in terms of success and false handover probabilities. The work was conducted by a simulation study in order to assess the performance of the proposed algorithm. The presented simulation results illustrated that the proposed algorithm is capable for drone networks. Regarding simulations, the algorithm performs admirably. However, a more accurate scenario must also be considered, considering the drone's payload, BS radio range, etc. Furthermore, the coverage algorithm considers each drone's RSS the same, which may not be readily applicable. In 2015 [26], the authors highlighted the different technologies and protocols that can be applied in the drone network, and their corresponding performance. In VANETs, for instance, no field experimental works are available concerning the mobility issue by implementing the Wireless Access in Vehicular Environments (WAVE) system. WAVE communication includes both IEEE 1609.x and IEEE802.11p standards. Nonetheless, these technologies do not provide any solution to mobility challenges. VANET schemes are characterized with high dynamism due to the constantly changing system topology and mobile nodes. Since VANET is a subordinate group of MANET, the latter's standards can also be applied to a VANET system [36]. In the RWP structure, the node's motion is assumed to be random. Due to the constantly separating or merging topology elements, it is not possible to maintain existing paths or predetermine the best path. It is therefore necessary to reconfigure the system, which causes frequent handovers. The model's performance and QoS deteriorate due to the delay and errors caused by the handoffs. Therefore, RWP is rarely used for mobile users or BS scenarios. The implemented network must eliminate the topographical limitations of nodes. Manhattan and Street Random Waypoint (STRAW) are two commonly employed systems. An additional challenge is that the density of VANET nodes must be equal to the number of nodes needed for the corresponding application. These obstacles hinder researchers from implementing a seamless handover scheme to provide reliable communication and enhance packet delay [109; 110]. Unfortunately, there is a lack of research regarding handover schemes in VANETs and Wireless Mesh Networks (WMNs) that apply IEEE 802.11 standards [106]. In 2016 [111], the authors investigated a suitable orientation-based fast handover method to overcome the ping-pong effect for LTE-Advanced systems. They selected the T-BS based on the current load and Received Signal Strength (RSS). In [77], a Reduced Early Handover (REHO) technique was suggested to minimize both the ping-pongs and RLFs, achieving high energy efficiency while maintaining other performance parameters within appropriate limits. The finding in [55] also led to the outcomes of [56] where a fuzzy multiple criteria cell selection technique was used. This scheme considers the UE uplink conditions, resource block allocation, and selection criteria of the LTE's conventional cell selection approach. This provides high reliability and minimizes both the HOF and ping-pong effect, thereby increasing throughput. The authors in [112] proposed a Handover Detection Self-Organizing Handover Parameter (HD-SOHP) scheme that relies on the reinforcement learning (RL) principle. This approach enhances the performance of UE mobility by maintaining low HOFs, ping-pong, and call drops.