Low-Altitude Reflection via UAV-Mounted Rotatable IRS

Low-altitude network is a key enabler for extending coverage and recovering connectivity in 6G systems, especially when terrestrial infrastructure is unavailable. This paper studies a uncrewed aerial vehicle (UAV)-mounted rotatable intelligent reflecting surface (IRS) as a low-altitude reflector between a blocked base station (BS) and a ground terminal (GT). Unlike the conventional isotropic-element assumption, each IRS element is modeled with a hemispherical directive radiation pattern, whose boresight can be adjusted via element rotations. We formulate a new optimization problem that jointly designs IRS phase shifts, per-element rotation vectors, and UAV placement to maximize the received signal-to-noise ratio (SNR). Leveraging the problem structure, we derive closed-form solutions for phase alignment and element rotations, showing that the optimal boresight points are along the internal angular bisector between the BS-IRS and GT-IRS directions. With these closed forms, the design reduces to a placement optimization problem over a box-constrained airspace; we solve it using an efficient projected gradient algorithm with majorization-minimization update and a global Lipschitz constant. Numerical results demonstrate substantial SNR gains from directive elements and reveal a fundamental trade-off between directional gain and path loss, yielding useful insights into low-altitude deployment of UAV-mounted IRSs.

Movable Intelligent Surface (MIS) for Wireless Communications: Architecture, Modeling, Algorithm, and Prototyping

Reconfigurable intelligent surfaces enhance wireless systems by reshaping propagation environments. However, dynamic metasurfaces (MSs) with numerous phase-shift elements incur undesired control and hardware costs. In contrast, static MSs (SMSs), configured with static phase shifts pre-designed for specific communication demands, offer a cost-effective alternative by eliminating element-wise tuning. Nevertheless, SMSs typically support a single beam pattern with limited flexibility. In this paper, we propose a novel Movable Intelligent Surface (MIS) technology that enables dynamic beamforming while maintaining static phase shifts. Specifically, we design a MIS architecture comprising two closely stacked transmissive MSs: a larger fixed-position MS 1 and a smaller movable MS 2. By differentially shifting MS 2's position relative to MS 1, the MIS synthesizes distinct beam patterns. Then, we model the interaction between MS 2 and MS 1 using binary selection matrices and padding vectors and formulate a new optimization problem that jointly designs the MIS phase shifts and selects shifting positions for worst-case signal-to-noise ratio maximization. This position selection, equal to beam pattern scheduling, offers a new degree of freedom for RIS-aided systems. To solve the intractable problem, we develop an efficient algorithm that handles unit-modulus and binary constraints and employs manifold optimization methods. Finally, extensive validation results are provided. We implement a MIS prototype and perform proof-of-concept experiments, demonstrating the MIS's ability to synthesize desired beam patterns that achieve one-dimensional beam steering. Numerical results show that by introducing MS 2 with a few elements, MIS effectively offers beamforming flexibility for significantly improved performance. We also draw insights into the optimal MIS configuration and element allocation strategy.