In this paper, we consider power consumption reduction in extremely large antenna arrays (ELAAs) for integrated sensing and communication (ISAC) applications. Although ELAAs are critical for achieving high-resolution near-field sensing, fully activating all antenna elements in conventional digital architectures leads to prohibitive power demands. To address this, we propose an energy-efficient subarray activation framework that selects an optimal subset of subarrays to minimize the total power consumption, subject to quality-of-service (QoS) constraints for both sensing and communication. We formulate a novel optimization problem and solve it using a successive convex approximation (SCA)-based iterative algorithm. The simulation results confirm that the proposed method significantly reduces power consumption while maintaining dual-function performance.

翻译：本文研究了面向集成感知与通信应用的超大规模天线阵列的功耗降低问题。尽管超大规模天线阵列对于实现高分辨率近场感知至关重要，但在传统数字架构中完全激活所有天线单元会导致难以承受的功耗需求。为解决这一问题，我们提出了一种高能效的子阵列激活框架，该框架通过选择最优的子阵列子集，在满足感知与通信服务质量约束的前提下，实现总功耗的最小化。我们构建了一个新颖的优化问题，并采用基于逐次凸逼近的迭代算法进行求解。仿真结果证实，所提方法在保持双功能性能的同时，能够显著降低系统功耗。