Integrated sensing and secure communication improved by movable intelligent surfaces
Secure Integrated Sensing and Communications with Movable Beyond-Diagonal RIS
Information Theory
Summary
When a device tries to both sense objects and send messages securely, it can be tricky if the target being sensed could also eavesdrop on the messages. The authors show how a new type of intelligent surface with movable parts can separate the sensing signals from the communication signals, so that sensing doesn't compromise security. Their method uses mathematical properties of the surface to steer signals exactly where needed, reducing the usual tradeoff between sensing quality and secrecy. The design does not require complex repeated adjustments and works efficiently for different placements.
What this means in practice
- •For wireless network engineers: Design secure communication systems that sense targets without leaking information through reflected signals.
- •For defense communication teams: Deploy sensing setups that prevent targets from intercepting data by physically moving and configuring intelligent surfaces.
Authors
Chandan Kumar Sheemar, Symeon Chatzinotas
Abstract
In integrated sensing and communication (ISAC), when the sensed target is itself an eavesdropper, the illumination required for sensing coincides with the leakage that secrecy must suppress. This paper shows how a beyond-diagonal reconfigurable intelligent surface (BD-RIS) with movable elements decouples the two tasks in a monostatic setting, where the echo returns to the base station through the surface. We prove that a lossless reciprocal BD-RIS maps $K$ incident fields onto $K$ prescribed fields if and only if the two sets share the same Gram matrix and their bilinear Gram matrix is symmetric; unlike a diagonal RIS, it can thus steer a two-dimensional incident subspace onto any prescribed subspace. With a single stream, sensing incurs an unavoidable rate loss, whereas a closed-form zero-forcing design with a confidential and a Gaussian sensing stream nulls the data at the target and the sensing at the user, so that sensing costs only an SNR offset. Since all variables follow in closed form for any placement, the joint design reduces to a monotone search over the element positions, without alternating optimization. Simulations show that the dual-stream design loses only $1.1$ bit/s/Hz when the sensing requirement grows by $30$ dB, against $8.3$ bit/s/Hz for a single stream, while movement, interconnection, and the robust derivative-null design add up to $1.9$, $0.9$, and $2.6$ bit/s/Hz, respectively.