Unmanned Aerial Vehicles (UAVs) communications encounter jamming challenges due to a high level of interference that impacts their reliability and performance. This paper considers the semantic interference cancellation (SemanticIC) technique to enhance the UAVs dependability and communication quality when the UAV is operated at noisy jamming signal environment. Our framework is structured by extending semanticIC with Principal Component Analysis (PCA)-base compression to reduce jamming noise sensitivity, and attention blocks to prioritize critical semantic features for selecting relevant information. Also, enhanced Low-Density Parity-Check (LDPC) decoding with Log-Likelihood Ratio (LLR) damping and clipping is employed in the framework to improve stability during iterative decoding. The performance of the integrated UAV with semanticIC system is evaluated in terms of Peak Signal-to-Noise Ratio (PSNR), Bit Error Rate (BER) and Euclidean Distance (ED) metrics for more insight analysis. The results show that the framework significantly improves the system performance particularly under low SNR and high-interference conditions, offering a practical and scalable solution for anti-jamming attacks................ Keywords: ..........UAV, Semantic, Jamming Noise.