We study uplink orthogonal frequency-division multiplexing (OFDM) pilot distortion to deliberately obfuscate time-of-arrival (ToA) estimation at a single base station while preserving communication performance. We design a complex persubcarrier distortion vector that increases sidelobes of the mismatched ambiguity function (MAF) relative to its mainlobe, using two objectives: the sidelobe-to-peak level ratio and the integrated sidelobe level. The design is subject to a transmit-power budget and a proximity (dissimilarity) constraint around the communication-optimal pilot. Communication impact is quantified by a capacity-motivated lower bound obtained from the linear minimum mean-squared error error covariance with a mismatched channel estimate. The resulting generalized fractional program is solved with Dinkelbach's transform and a difference-of-convex update that yields a closed-form Karush-Kuhn-Tucker step. Simulations on a single-input single-output OFDM link show that the optimized distortions raise MAF sidelobes and degrade delay estimation, as validated by a mismatched maximumlikelihood ToA estimator, while incurring only marginal capacity loss over a broad signal-to-noise ratio range. The method requires no protocol changes or artificial path injection and provides a signal-level mechanism to control ToA observability under communication constraints.

Integrated sensing and communication (ISAC) is a key technology for enabling a wide range of applications in future wireless systems. However, the sensing performance is often degraded by model mismatches caused by geometric errors (e.g., position and orientation) and hardware impairments (e.g., mutual coupling and amplifier non-linearity). This paper focuses on the angle estimation performance with antenna arrays and tackles the critical challenge of array beam pattern calibration for ISAC systems. To assess calibration quality from a sensing perspective, a novel performance metric that accounts for angle estimation error, rather than beam pattern similarity, is proposed and incorporated into a differentiable loss function. Additionally, a cooperative calibration framework is introduced, allowing multiple user equipments to iteratively optimize the beam pattern based on the proposed loss functions and local data, and collaboratively update global calibration parameters. The proposed models and algorithms are validated using real-world beam pattern measurements collected in an anechoic chamber. Experimental results show that the angle estimation error can be reduced from 1.01◦ to 0.11◦ in 2D calibration scenarios, and from 5.19◦ to 0.86◦ in 3D calibration scenarios.

Positioning technology, which aims to determine the geometric state of a device in a global coordinate system, is a key component in integrated sensing and communication systems. In addition to traditional active anchor-based positioning systems, reconfigurable intelligent surfaces (RISs) have shown great potential for enhancing system performance. However, their ability to manipulate electromagnetic waves and ease of deployment pose potential risks, as unauthorized RIS may be intentionally introduced to jeopardize the positioning service. Such an unauthorized RIS can introduce unexpected interference into the legitimate positioning system, distorting the transmitted signals, and leading to degraded positioning accuracy. In this work, we investigate the scenario of RIS-aided positioning in the presence of interference from an unauthorized RIS. Theoretical lower bounds are derived to analyze the impact of unauthorized RIS on channel parameter estimation and positioning accuracy. Several codebook design strategies for unauthorized RIS are evaluated, and various system arrangements are discussed. Simulation results show that unauthorized RIS paths with high power or delay values close to those of legitimate RIS paths significantly degrade positioning accuracy. Furthermore, an unauthorized RIS generates more effective interference when using directional beamforming codebooks compared with a random phase codebook.

We investigate cooperative impersonation jamming on angle-based physical layer authentication (PLA) within 6G systems using hybrid antenna arrays. PLA leverages angle-ofarrival (AoA) information to authenticate user equipment, but remains vulnerable to sophisticated jamming where multiple adversaries cooperate. We extend previous research by formulating a comprehensive model of PLA that integrates hybrid arrays and by developing optimized jamming strategies that consider energy and information constraints. Our results show that analog arrays are more vulnerable to cooperative jamming than hybrid arrays. Additionally, the combiner design in the hybrid array, along with the energy and information constraints on jamming strategies, significantly influences the success of jamming. By identifying vulnerabilities in PLA and studying effective countermeasures, this work contributes to advancing physical layer authentication in 6G systems.