Green ISAC: A Design Framework for Resilient TDD Communication and High-Resolution Sensing in Asymmetric Systems
IEEE Open Journal of the Communications Society, cilt.7, ss.1523-1536, 2026 (ESCI, Scopus)
- Yayın Türü: Makale / Tam Makale
- Cilt numarası: 7
- Basım Tarihi: 2026
- Doi Numarası: 10.1109/ojcoms.2026.3661562
- Dergi Adı: IEEE Open Journal of the Communications Society
- Derginin Tarandığı İndeksler: Emerging Sources Citation Index (ESCI), Scopus, Compendex, INSPEC, Directory of Open Access Journals
- Sayfa Sayıları: ss.1523-1536
- Anahtar Kelimeler: Channel reciprocity, energy saving, integrated sensing and communication, sparse antenna array, TDD
- İstanbul Medipol Üniversitesi Adresli: Evet
Özet
The design of future 6G networks is driven by the dual requirements of supporting new integrated sensing and communication (ISAC) functionalities while drastically improving energy efficiency. A common strategy for this is spatial power saving, where the radio frequency chains are dynamically scaled based on network load. Conventionally, this is performed by switching off antennas in a uniform manner, resulting in a smaller, compact sub-array. While this method saves power and preserves the channel reciprocity for time division duplex (TDD), the resulting small aperture array suffers from poor sensing resolution. In contrast, this paper proposes a novel adaptive antenna selection framework that intelligently configures the active elements during low-load mode to form a genetically optimized sparse array. A multi-objective co-design methodology is developed to find the Pareto front of optimal layouts that balance two conflicting goals: enhancing sensing accuracy by synthesizing a large, hole-free virtual sum co-array, and ensuring resilient TDD communication by mitigating channel estimation errors. This framework enables two operational modes: a power-saving asymmetric mode for ISAC, and a high-performance fully sparse mode for dedicated sensing. Simulation results demonstrate that the intelligent sparse array selection significantly outperforms the conventional uniform deactivation strategy, providing a clear pathway to adaptive systems that achieve substantial energy savings without compromising on high-performance sensing and communication.