# Adaptive Jamming Mitigation for Clustered Energy-Efficient LoRa-BLE Hybrid Wireless Sensor Networks
## 1 Introduction  
The increasing deployment of WSNs in critical applications such as smart cities, industrial automation, and environmental monitoring has raised concerns about their security and resilience against external threats. Among these threats, jamming attacks pose a significant challenge, disrupting wireless communication by overwhelming the network with interference, leading to increased retransmissions and energy depletion [1]. Recent studies [2, 3] emphasized the need for adaptive mitigation techniques to maintain network integrity and performance, particularly in heterogeneous networks that integrate multiple communication technologies such as LoRaWAN and Bluetooth Low Energy (BLE) [4]. Addressing this challenge, this work proposes a multi-protocol jamming detection and mitigation strategy that leverages an energy-aware cluster-based architecture to ensure reliablecommunication in university campus environments, where varying interference conditions exist. Unlike existing solutions, which primarily focus on single-protocol networks or static countermeasures, our approach dynamically adapts to heterogeneous wireless technologies, including LoRaWAN and BLE, to optimize resilience against diverse jamming threats [4]. While previous studies have explored frequency hopping and spread spectrum techniques as countermeasures, these methods often require significant energy overhead or are limited in their applicability across multi-protocol environments. In contrast, our strategy integrates real-time energy-aware cluster formation, where nodes autonomously elect a cluster head (CH) based on energy availability, signal quality, and retransmission rates, allowing for adaptive protocol switching and intelligent interference mitigation. This approach not only enhances network longevity and communication reliability but also provides a scalable and low-energy alternative to traditional anti-jamming methods, making it particularly suitable for dynamic and resource-constrained IoT applications. Heterogeneous wireless sensor networks (HWSNs) integrate multiple wireless communication technologies to enhance network adaptability, scalability, and energy efficiency in complex IoT environments [5]. Unlike traditional homogeneous networks that rely on a single communication protocol, HWSNs leverage the complementary strengths of different technologies, such as BLE for low-power short-range communication, LoRa for long-range low-data-rate transmission, and Wi-Fi or 5G for high-speed connectivity. This multi-technology approach enables dynamic network optimization, allowing nodes to switch between protocols based on energy availability, data transmission requirements, and environmental conditions [6]. The integration of multiple wireless technologies not only improves coverage and reliability but also mitigates the limitations of individual protocols, such as BLE's short range or LoRa's limited bandwidth. However, managing the coexistence of diverse wireless standards requires intelligent network coordination, efficient routing mechanisms, and adaptive energy management strategies to ensure seamless interoperability. Advances in software-defined networking (SDN) and artificial intelligence (AI)-driven optimization further contribute to the efficient orchestration of HWSNs, enabling robust and energy-efficient communication in applications ranging from industrial automation to smart cities and environmental monitoring [7]. Jamming attacks pose a critical threat to the reliability and security of heterogeneous wireless sensor networks by intentionally disrupting communication through interference. These attacks can take various forms, each exploiting different network vulnerabilities depending on the wireless technologies in use [8]. Constant jamming continuously emits high-power signals to block legitimate transmissions, making it particularly effective against energy-constrained IoT nodes.