Energy-Efficient Target-Aware Hybrid Beamforming for THz Near-Field ISAC with Sparse Connectivity

Integrated sensing and communication (ISAC) at terahertz (THz) frequencies enables ultra-high-resolution perception while facing a key limitation: highly directional THz beams cannot illuminate extended targets within a single beam. Conventional solutions rely on sequential beam scanning, reducing sensing accuracy and increasing energy consumption. Moreover, in conventional sparse-array, grating lobes are generally treated as undesirable artifacts that should be suppressed to avoid ambiguity and interference. In contrast, this paper adopts a reverse design philosophy by intentionally engineering sparsity-induced grating lobes as controllable auxiliary illumination beams for extended-target sensing. This paper exploits grating lobes and proposes a sparse-connected hybrid beamforming architecture that intentionally engineers and exploits grating lobes to enable single-shot, full-aperture illumination of extended targets while supporting multi-user downlink communication. A switch-controlled sparse RF network preserves the array aperture and generates a dominant main lobe with structured secondary lobes covering the entire target extent. A covariance-driven alternating-minimization framework jointly optimizes digital precoders, quantized phase shifters, and antenna-RF switching. Simulations at 140 GHz demonstrate near fully-digital Cramer-Rao sensing accuracy, competitive communication performance in low-rank THz channels, rapid convergence, and significant hardware and energy savings, establishing structured sparse connectivity as a scalable and energy-efficient solution for extended-target THz ISAC.

Posterior-Confidence Driven Beamforming for Energy-Efficient Integrated Sensing and Communication

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.