Abstract:Specific emitter identification leverages hardware-induced impairments to uniquely determine a specific transmitter. However, existing approaches fail to address scenarios where signals from multiple emitters overlap. In this paper, we propose a specific multi-emitter identification (SMEI) method via multi-label learning to determine multiple transmitters. Specifically, the multi-emitter fingerprint extractor is designed to mitigate the mutual interference among overlapping signals. Then, the multi-emitter decision maker is proposed to assign the all emitter identification using the previous extracted fingerprint. Experimental results demonstrate that, compared with baseline approach, the proposed SMEI scheme achieves comparable identification accuracy under various overlapping conditions, while operating at significantly lower complexity. The significance of this paper is to identify multiple emitters from overlapped signal with a low complexity.
Abstract:For autonomous aerial vehicle (AAV) secure communications, traditional designs based on fixed position antenna (FPA) lack sufficient spatial degrees of freedom (DoF), which leaves the line-of-sight-dominated AAV links vulnerable to eavesdropping. To overcome this problem, this paper proposes a framework that effectively incorporates the fluid antenna (FA) and the artificial noise (AN) techniques. Specifically, the minimum secrecy rate (MSR) among multiple eavesdroppers is maximized by jointly optimizing AAV deployment, signal and AN precoders, and FA positions. In particular, the worst-case MSR is considered by taking the channel uncertainties due to the uncertainty about eavesdropping locations into account. To tackle the highly coupled optimization variables and the channel uncertainties in the formulated problem, an efficient and robust algorithm is proposed. Particularly, the uncertain regions of eavesdroppers, whose shapes can be arbitrary, are disposed by constructing convex hull. In addition, two movement modes of FAs are considered, namely, free movement mode and zonal movement mode, for which different optimization techniques are applied, respectively. Numerical results show that, the proposed FA schemes boost security by exploiting additional spatial DoF rather than transmit power, while AN provides remarkable gains under high transmit power. Furthermore, the synergy between FA and AN results in a secure advantage that exceeds the sum of their individual contributions, achieving a balance between security and reliability under limited resources.