Antenna Topology Optimization for Distributed Integrated Sensing and Communication

We propose a cooperative integrated sensing and communication (ISAC) architecture that integrates coordinated multi-point (CoMP) communication with multi-static sensing. This study investigates how the allocation of a fixed total number of antennas among base stations (BSs) affects sensing and communication performance, and optimizes both the antenna topology and the number of BSs. To this end, we formulate an antenna topology optimization problem to balance the advantages of centralized and distributed antennas. Specifically, centralized antennas enhance beamforming and coherent processing in massive multiple-input and multiple-output (MIMO) systems, while distributed antennas improve spatial diversity and reduce access distances in cell-free setups. For sensing, we evaluate two localization methods, angle-of-arrival (AOA)-based and time-of-flight (TOF)-based localizations, to analyze how their scaling laws affect overall network performance. We analyze and demonstrate that the synchronization errors in our proposed architecture are negligible, thereby providing theoretical support for system implementation. In terms of communication, our results indicate that higher path loss exponents favour distributed configurations, while lower exponents benefit centralized setups. Simulations confirm that our cooperative scheme outperforms non-cooperative approaches, surpassing purely centralized or distributed strategies.