Joint Jamming Avoidance and Suppression with Intelligent Detection Threshold Adaptation for Emergency Wireless Communications

As wireless communication technologies continue to evolve, malicious jamming becomes a major factor that limits system performance and communication quality, especially in emergency communication scenarios where reliable links are essential for timely information delivery and rescue coordination. Conventional anti-jamming transmission methods often suffer from two issues. In the detection stage, the jamming threshold is difficult to determine. In the data transmission stage, spectrum resources are not efficiently utilized. To address these limitations, this paper jointly considers jamming detection and data transmission, and proposes a joint jamming avoidance and suppression method based on intelligent detection threshold adaptation. Specifically, reinforcement learning is first used to iteratively optimize the detection threshold according to transmission outcomes, which improves the accuracy and robustness of jamming detection. Then, based on the detection results, the jamming status is dynamically evaluated, then jamming avoidance and jamming suppression are jointly employed during data transmission, which effectively improves spectrum utilization. Simulation results show that, under both continuous-band jamming and comb-spectrum jamming, the proposed scheme nearly doubles the system sum rate and also achieves significantly higher detection accuracy than conventional methods, which demonstrates strong robustness and adaptability for emergency communication systems.