In this paper, we propose denoising autoencoder (DAE)-assisted secret key generation (SKG), where channel noise reciprocity imperfections induced due to wireless channel measurements are suppressed, hence significantly enhancing the reliability and efficiency. More specifically, the DAE is capable of capturing the intrinsic structure of input distributions, reconstructing the original data structure, and removing additive noise while preserving the essential structure of signals. In our analysis, it is demonstrated that the proposed SKG scheme exhibits higher performance than the conventional schemes in terms of key disagreement rate (KDR), secret key capacity (SKC), and randomness of the generated keys.
Integrated sensing and communication (ISAC) enables the acquisition of environmental information by leveraging wireless signals transmitted for communication purposes. In this paper, we utilize this capability to reconstruct the layout of objects surrounding multiple receivers. R…
This paper presents a Multi-Map Dynamic-Entropy Intrusion-Aware Chaotic Modulation (MU-DE-IAEACM-MM) framework for adaptive physical-layer security in multi-user wireless systems. Unlike conventional chaos-based schemes that rely on static parameter secrecy, the proposed architec…
This article surveys spatial-domain-enhanced Physical-layer Authentication (PLA), with Dual-polarized Antennas (DPA), Massive Multiple-Input Multiple-Output (MIMO), and Reconfigurable Intelligent Surfaces (RIS) as the primary focus. With the rapid growth of wireless deployments,…
Physical layer authentication (PLA) allows to authenticate the user by comparing measurements over time, assuming their time consistency or by modeling their evolution. However, these assumptions become problematic when devices are in motion and in indoor environments due to mult…
Wireless physical neural networks (WPNNs) embed neural computation directly into analog hardware, offering lower energy consumption and latency than conventional digital implementations. In this paper, we propose a deep WPNN in which nonlinear activations are realized by a multi-…
Data-aided channel estimation enhances spectral efficiency by reusing detected symbols as virtual pilots. In this process, selecting only reliable symbols is crucial to prevent misdetected symbols from corrupting the channel estimate. However, conventional methods rely exclusivel…