Performance Analysis for Heterogeneous Air-Ground ISAC in Coordinated Multipoint Networks
For researchers and engineers designing scalable ISAC networks for low-altitude economy scenarios, this work provides a network-level cooperative framework and performance insights, though it is incremental as it extends existing ISAC concepts to a specific architecture.
The paper proposes a heterogeneous air-ground ISAC network architecture using coordinated multipoint (CoMP) with a hybrid mono/bi-static sensing scheme, and develops a performance analysis framework revealing trade-offs between communication and sensing under multi-BS cooperation and varying network density.
The emergence of the \textit{low-altitude economy} (LAE) calls for highly integrated and reliable wireless systems that can simultaneously support \textit{communication and sensing} (C\&S) functions. Although \textit{integrated sensing and communication} (ISAC) has been widely studied, most existing works focused on link-level or single-cell architectures in terrestrial environments, leaving the potential of network-level cooperative air-ground ISAC largely unexplored. To bridge this gap, a heterogeneous air-ground ISAC network architecture based on \textit{coordinated multipoint} (CoMP) is proposed, which incorporates a cooperative hybrid mono/bi-static sensing scheme to enhance spatial diversity and sensing capability. In the proposed architecture, a two-tier \textit{base station} (BS) deployment is adopted: master BSs are arranged in a hexagonal lattice, while slave BSs follow a Poisson point process distribution. This structure concurrently supports communication for terrestrial users and sensing for aerial targets. A holistic performance analysis framework for both C\&S is further developed, accounting for key channel and network parameters. Simulation results reveal inherent trade-offs between C\&S performance, especially under multi-BS cooperation and varying network density. These findings provide practical guidance for the deployment of scalable and efficient ISAC networks in LAE scenarios.