## 1 Introduction
According to the International Telecommunication Union Radiocommunication Sector, the THz range is 300 GHz to 10 THz and is closely linked to the very high frequency band (300 GHz to 3 THz). THz communications will thus allow for very high bandwidth as well as ultra-low latency communication. Over distances comparable to other applications, 100 Gbps THz networks have previously been demonstrated [9; 10; 11]. However, providing mobile communications at the device level and the access level from the perspective of UAV-to-UAV [12], medium-range indoor, vehicular, and device-to-device communications is the pinnacle of THz communications. THz communications may allow for the wireless remoting of human cognition, resulting in pervasive wireless intelligence when paired with other THz-band applications, including precise location sensing and imaging [13]. Fading, which weakens the signal energy and prevents the system from achieving optimum results, is one of the major problems in wireless communication. Since the fading effect of wireless communication channels is caused by unpredictable and random reflection, refraction, attenuation, and scattering events depending on time, statistical models developed on the long-term status of the fading coefficients are used. In the literature, there are many statistical models proposed to model random variables and random processes. Many existing studies suggest that UAVs experience multiple types of fading. The most common models used to model the fading effect of wireless channels are the log-normal, Rayleigh, Rician, Nakagami-m, and Weibull distributions. When there is no line-of-sight (LoS) connection between the receiver and transmitter, Rayleigh fading is utilized to mimic the amplitude of the carrier wave. In transmission routes with high LoS, Nak-agami-m fading is employed. Rician distribution is used in cases of direct transmission between the receiver and transmitter in the wireless communication system or if there is a more dominant transmission path compared with other transmission paths. The shadowing effect on wireless circumstances, when there is a tall building or a high mountain, is mostly modeled using the log-normal distribution. A simple statistical fading model used in wireless communications is called Weibull fading. It has been shown via empirical investigations to be a successful paradigm in both indoor and outdoor settings. Onemay establish the bit error rate (BER) based on a certain signal-to-noise ratio (SNR) and channel capacity and finally which channel model best suits the real-time communication situations [14]. UAVs are essential in a wide range of possible wireless applications, such as aerial base stations, to improve energy efficiency, coverage, dependability, and the capacity of wireless networks [15]. One of the many applications of UAVs is UAV relaying, which involves embedding a UAV in a network to create a wireless connection between several nodes despite the lack of a direct communication link between them. This specific application is regarded as an effective method to boost throughput, boost reliability, and expand base station coverage [16]. The utilization of UAVs to assist THz communications is thus a highly advantageous strategy since it increases the likelihood of LoS with ground-user equipment when THz and UAVs are combined [17]. In order to deal with the intense demand on cellular networks with limited spectrum resources, UAV-to-UAV communication is implemented in cellular networks. This enables mobile devices to interact directly with each other under the management of a base station. It is also important to note that the utilization of THz band UAV-to-UAV communication allows for almost real-time processing, uploading, and downloading between two close-proximity user devices [18]. UAV-to-UAV communications in the THz frequency range are taken into consideration in a number of research papers in the literature [19; 20].