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This tutorial presents radiation locations as configurable network resources and provides a framework for understanding how pinching antennas may reshape future wireless network.
The deployment of integrated sensing and communication (ISAC) systems poses new challenges to physical-layer security (PLS), as sensing waveforms directed toward targets may be exploited by eavesdroppers (Eves), causing information leakage. Meanwhile, security enhancement must jointly consider multi-user quality-of-service (QoS) and radar sensing performance, resulting in coupled and conflicting objectives. The intrinsic limitation arises from the rigid spatial constraints of conventional fixed-position antennas (FPAs) and the restricted stream-level interference management of non-rate-splitting frameworks, which collectively provide insufficient degrees of freedom (DoFs) to reconcile these competing requirements, especially under imperfect channel state information (CSI). To address these gaps, we propose a robust secure transmission framework that synergistically integrates the reconfigurable spatial DoFs enabled by fluid antennas (FAs) and the flexible stream-level DoFs provided by rate-splitting multiple access (RSMA). In this architecture, the RSMA common stream is repurposed to serve a dual role: it is decoded by legitimate users (LUs) for information delivery while also acting as a controlled jamming component to impair an Eve. We formulate a secure sum-rate maximization problem by jointly optimizing the base station beamformers and the FA positions at the LUs, subject to power budget, RSMA decoding, and minimum sensing requirements. An alternating-optimization (AO) framework is developed to address the coupled design under both perfect and imperfect CSI scenarios. In the imperfect-CSI case, semi-infinite constraints induced by bounded estimation errors are converted into linear matrix inequalities (LMIs) via the S-procedure. Simulation results show that the proposed FA-RSMA design achieves significant secure sum-rate gains and improved robustness over FPA and non-rate-splitting baselines.
Terahertz (THz) communications are envisioned as a promising technology to meet the ultra-high-speed data transmission requirements of future wireless networks. However, severe molecular absorption and misalignment fading can significantly degrade system performance. To address these challenges, this paper investigates distributed reconfigurable intelligent surface (RIS)-assisted THz communication systems. To evaluate network performance, we first derive closed-form expressions for the cumulative distribution function (CDF) and probability density function (PDF) of the cascaded channel under both exact-case and worst-case conditions. Subsequently, we obtain accurate approximate expressions for the ergodic capacity and outage probability for both scenarios. To deepen the theoretical understanding, we further derive the corresponding diversity orders in the high signal-to-noise ratio (SNR) regime. Moreover, leveraging the derived theoretical results, we propose a low-complexity determinantal point process learning (DPPL)-based algorithm to optimize the RIS-destination (RIS-D) association and maximize the system utility. Extensive simulation results demonstrate that: i) expressions remain accurate for a wide range of system parameters, including the number of distributed RISs and reflecting elements; ii) cooperation among distributed RISs can effectively mitigate the performance loss caused by misalignment fading in THz systems; and iii) the proposed RIS-D association strategy significantly outperforms existing benchmark schemes while maintaining low computational complexity.
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