Exploiting Continuous-Aperture Arrays in Integrated Sensing and Communication Systems

A continuous-aperture array (CAPA)-based integrated sensing and communication (ISAC) framework is proposed in this paper, where CAPA transceivers are optimized to enhance both target sensing and user communication performance. Novel expressions for achievable communication and sensing rates are derived and CAPA-oriented beamforming is designed to balance the dual-functional Pareto-optimal tradeoff in two scenarios: i) For the single-user single-target case, closed-form continuous beamformers are derived based on communication-, sensing-, and Pareto-optimal criteria to reveal the interrelation of the ISAC rate region with the antenna aperture and channel gains; ii) For the multi-user multi-target case, a general CAPA-ISAC beamforming design algorithm is developed to achieve the Pareto optimality. Beamformer design in the continuous spatial domain is transformed into weight design in the discrete wavenumber domain using Fourier series expansions. Furthermore, alternating optimization, successive convex approximation, and difference of convex techniques are employed to tackle the coupling and non-convexity issues. Numerical results demonstrate that: i) The proposed CAPA-ISAC framework significantly improves both sensing and communication performance and expands the ISAC Pareto rate region; ii) CAPAs exhibit superior beamforming capabilities and reach the ultimate performance limits of spatially discrete arrays (SPDAs).