AI 中文总结
针对6G集成感知与通信系统能效受限问题，提出基于扩展卡尔曼滤波器互补统计量的后验置信度驱动波束成形框架，可降低发射功率，保障通信性能与多目标跟踪，优于其他基线方法。
AI 中文摘要
鉴于持续感知带来的高功耗，尽管通信需求稳定，但能效仍将对第六代（6G）集成感知与通信（ISAC）系统构成重大限制。本文提出了一种高能效多输入多输出（MIMO）双功能雷达通信（DFRC）波束成形框架，在保证用户信干噪比（SINR）和可靠多目标跟踪的同时，使发射功率最小化。关键创新在于一种跟踪感知、可跳过的感知策略，它不同于传统的始终开启探测模式。根据扩展卡尔曼滤波器（EKF）导出的两个互补统计量——后验置信度度量和归一化新息平方（NIS），有选择地触发感知。数值结果表明，与其他基线相比，所提框架显著降低了发射功率，且不影响通信系统性能，对感知过程影响也不过大。
英文摘要
Energy efficiency will pose an essential limitation for sixth-generation (6G) integrated sensing and communication (ISAC) systems, given the high sensing power consumption associated with persistent sensing, despite stable communication requirements. This paper proposes an energy-efficient multiple-input multiple-output (MIMO) dual-functional radar-communication (DFRC) beamforming framework that minimizes transmit power while guaranteeing per-user signal-to-interference-plus-noise ratio (SINR) and reliable multi-target tracking. The key innovation is a tracking-aware, skip-enabled sensing policy that departs from the conventional always-on probing paradigm. Instead of enforcing sensing at every epoch, sensing is selectively triggered according to two complementary statistics derived from an extended Kalman filter (EKF): a posterior confidence metric and the normalized innovation squared (NIS). While the former ensures accurate estimation, the latter guarantees reliable measurements, and thus sensing can only be activated when additional information is required. To ensure robustness under intermittent sensing, sector-based beampattern constraints are combined with a nonzero safety illumination floor imposed to guarantee reliable target tracking when skipping occurs. Numerical results show that the proposed framework achieves a significant reduction in transmit power compared to other baselines, without any deterioration in the communication system's performance or excessive impact on the sensing process.
Comments11 pages, 12 figures, Journal
