## 1 Introduction  
In recent years, the rapid advancements in Reconfigurable Intelligent Surfaces (RISs) have significantly transformed wireless communication systems, enhancing their capacity and efficiency by intelligently reconfiguring the wireless propagation environment [1, 2]. The RIS, developed from metamaterial technology, is an artificial electromagnetic surface structure with real-time programmable electromagnetic characteristics, which are composed of a wide range of passive reflecting elements and can intelligently manipulate electromagnetic waves, thereby enhancing signal propagation and coverage [1, 3]. By smartly adjusting the phase shifts of the signals reflected from their surfaces, RISscan markedly enhance the performance of communication channels [4; 5] because of their light weight, low cost, and programmable and easy deployment, which makes them a highly attractive solution for modern RF communication systems [6]. Extensive studies have demonstrated the potential of RISs to mitigate interference, boost signal strength, and improve overall network efficiency [7; 8; 9]. Researchers have explored the capacity of proactively adjustable intelligent surfaces to boost wireless energy-enabled communication networks, catering to the growing connectivity demands of IoT devices [10]. An innovative method for optimizing the beamwidth of RISs to alleviate intra-beam interference has been introduced [11]. An examination of the communication frameworks pertaining to Reconfigurable Intelligent Surfaces, traversing from the electromagnetic properties of the surfaces to the enhancement of wireless network performance, has been reviewed [12]. The dynamic adaptability of RISs to different communication environments represents a significant advancement in wireless technology, and it is expected to serve as a notable part of sixth-generation (6G) wireless communication networks [13; 14; 15; 9; 16]. A significant quantity of research has been concentrated on RIS-aided wireless communication systems. Channel characterization and modeling matters have been dealt with in [17], and sparsity-aware channel estimations for fully passive RIS-aided systems were attained in [18]. Further, channel modeling for RIS-aided 6G communications was analyzed in [19]. In the realm of interference in RIS-aided wireless communication systems, most existing research concentrates on managing interference between legitimate users. For instance, [PERSON] et al. analyzed the joint impact of mobile jamming on RIS-aided systems using the \(\kappa\)-\(\mu\) fading model in [20]. A statistical characterization of cascaded channels with evaluations of outage probability (OP) and Average Bit Error Rate (ABER) was proposed in [21]. Closed-form expressions for an active STAR-RIS-aided two-user downlink communication system are achieved for the OP in both the coupled and independent phase-shift circumstances [22]. This study was conducted on the robust transmission design for an RIS-assisted secure communication system when there are transceiver hardware impairments [23]. The study in reference [24] scrutinized the operational effectiveness of multi-hop systems that integrate Free Space Optics (FSO) with Radio Frequency (RF) communications, aided by RISs. The above research mainly focuses on how to utilize RISs to improve the performance of wireless communication while not involving the interference issues of RIS-assisted wireless communication. Current research primarily focuses on jamming between legitimate users in RIS-aided systems. Although [24] analyzed malicious jamming, the proposed use of a fixed RIS as a relay is impractical in harsh environments, such as military scenarios. The study of Unmanned Aerial Vehicle (UAV)-assisted wireless communication is evolving rapidly, driven by the unique capabilities of UAVs to provide flexible and dynamic support across various scenarios. UAVs enhance connectivity, extend coverage, and improve overall network performance, especially in challenging environments [25; 26; 27; 28].