## 2 Related Works  
Several research works have been conducted in the area of LPWANs for IoT applications. [PERSON] et al. focus on the performance of LPWAN technology, particularly in urban scenarios [17]. Simulation results demonstrate the scalability of LPWAN networks, achieving high packet success rates even with a significant number of endpoints. Another study by [PERSON] et al. explores the use of alternative frequency bands for LPWAN transmissions, emphasizing range and data rate considerations [18]. They present a path-loss model for long-range LPWAN communications. [PERSON] et al. propose an innovative public transport tracking system using wireless communication between bus stops and a central base station [19]. This system significantly reduces costs compared to conventional tracking methods and provides real-time monitoring with minimal power consumption. [PERSON] et al. explore the integration of LPWAN communications within the vehicle ecosystem [20]. Specifically, they apply LoRa technology to vehicular communications, demonstrating unprecedented ranges and opening avenues for novel services in the vehicular ecosystem. [PERSON] et al. delve into the experimental study of LPWAN for mobile IoT applications [21]. Their results show the impact of mobility on LPWAN performance and highlight the need for mobility-aware LPWAN protocols. [PERSON] et al. study the coverage of LoRa LPWAN through real-world measurements [22]. Their experiments show impressive communication ranges of over 15 km over land and nearly 30 km over water and present a channel attenuation model derived from measurement data for the 868 MHz ISM band. [PERSON] et al. present a two-tier LPWAN system based on Unmanned Aerial Vehicle (UAV) base stations designed for dynamic deployment in remote rural environments [23]. This innovative UAV-based LPWAN network adds a layer of mobile base stations (Tier 2) to the existing macrocellular LPWAN network (Tier 1), providing connectivity to LPWAN user devices in areas without direct Tier 1 network coverage. [PERSON] presents a lane-change decision aid and warning system utilizing LoRa-based Vehicle-to-Vehicle (V2V) communication technology [24]. The system aims to enhance driver decision-making during lane changes on highways, providing visual and audible warnings to both host and approaching vehicle drivers. Using LoRa for V2V communication, the system offers contextual information to support safe lane-changing decisions. [PERSON] focuses on LPWAN-based agricultural vehicle tracking using LoRa and NB-IoT technologies [25]. The study investigates coverage limits in urban, suburban, and rural environments, providing analytical expressions for maximum transmission range based on the data path-loss model. This research contributes to the development of LPWAN-based tracking systems for smart farms. The global adoption of LoRa networks for diverse IoT applications necessitates a closer look at dense environments and the robustness of LoRa transmissions. [PERSON] et al. focus on this concept, exploring the integration of a Carrier Sense mechanism to reduce collisions in both short and long LoRa messages [26]. Their work proposes a journey toward a Carrier Sense Multiple Access (CSMA) protocol tailored for LoRa networks, offering experimental validation through a low-cost IoT LoRa framework. The focus extends beyond theory, with practical implementation involving innovative long-range image sensor nodes. In their exploration, [PERSON] et al. delve into LoRa waveform theory, unveiling its intricacies and establishing a comprehensive understanding [27]. They quantify orthogonality, presenting expressions in continuous- and discrete-time domains. Cross-correlation functions reveal non-orthogonality across various LoRa spreading factors, emphasizing the impact of displacement and bandwidth variation. The key finding is that LoRa modulation is inherently non-orthogonal. [PERSON] et al. enhance LoRa-based networks by optimizing transmission configurations for improved performance [28].