## 1 Introduction
IEEE 802.11 was recommended for UAV communications by researchers since it can handle higher bandwidth, has fast data rates, and has long-range coverage. Due to fluctuating distances among nodes and high mobility in the UANET, connection reliability fluctuations occur. Packet delays, efficient channel use, high mobility, and varying link quality are among the difficulties that the UANET must overcome during real-time communication. Routing protocols are one of the essential components of a UANET. In a UANET, a single node may serve as a transmitting, receiving, and forwarding node simultaneously. The transmission path is typically multi-hop, and routing greatly influences network performance. A significant amount of effort must be invested in performance analysis to select the optimal routing protocol. The simulation-based performance study for MANET is demonstrated in paper [16]. The paper explains how, by lowering the RREQ RETRIES and MAX RREQ TIMEOUT parameters, the AODV protocol performs better than the OLSR protocol. When a sender wants to transfer data to a receiver, the network responds with a route request (RREQ). The sender awaits the network's route response, and the sender resends an RREQ a defined number of times if it is not received within a specific period of time, which is known as RREQ RETRIES. The MAX RREQ TIMEOUT is the maximum amount of time a sender node can wait before sending RREQ RETRIES. A significant amount of effort must be invested in performance analysis to select optimal RREQ RETRIES and MAX RREQ TIMEOUT values. In another paper [17], the authors compare the performance of the AODV and OLSR routing protocols by using the NS2 simulator in FANET for search and rescue (SAR). The Gauss-Markov mobility model is used to describe the motions of multi-rotor mini-UAVs used for monitoring in SAR. Similarly, in [18], the performance comparison of a UAV communication network for AODV, OLSR, DSR, and GRP routing protocols is presented. Depending on functionality, routing protocols are classified into three categories [19; 20]:  
* Swarm-based routing;
* Position-based routing;
* Topology-based routing. The characteristics of natural insects are used to inspire swarm-based routing. These traits are thought to be self-oriented, self-adaptive, and unified to choose the optimal route. However, due to the high mobility of UAVs, excessive latency is the fundamental flaw of swarm-based routing for the UANET network. Likewise, packet forwarding is performed depending on the geographic location of UAVs in position-based routing protocols [21]. However, the major downside of position-based routing is that it transmits obsolete route information due to the UAVs' constantly changing locations. On the other hand, internet protocol (IP) addresses are used by topology-based routing protocols to leverage existing network information to transmit data packets in the most efficient manner possible [22]. In order to construct and manage the optimal route, these protocols require topological information from communicating UAVs. A topology-based routing protocol for UAVs is evaluated in the paper [23]. This article provides a brief overview of the most significant topology-based routing protocols suitable for FANETs. Furthermore, the authors focus on topology-based routing protocols to enhance network performance in terms of throughput, latency, and network load. However, the previously mentioned article solely used the existing protocol for performance analysis with no improvements. In this study, a review of several routing protocols for UAV communication is provided, and an enhanced OLSR, named E-OLSR, is proposed for the UANET network.