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Optimizing communication-centric and sensing-centric energy efficiencies for OTFS-based integrated sensing and communication systems
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DOI：10.1016/j.phycom.2026.103058.png)
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Abstract
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The Integrated Sensing and Communication (ISAC) system is recognized as a key technology in sixth-generation (6G) communication, facilitating spectrum resource sharing and system coordination. In future wireless communication networks, ISAC aims to achieve both high-efficiency data transmission and precise target sensing within a shared spectrum, thereby significantly enhancing spectrum utilization and reducing system costs. However, achieving high spectral efficiency in ISAC systems remains challenging due to the need to balance communication performance with sensing capabilities. While ensuring stable data transmission, the system must also meet the accuracy and timeliness requirements of sensing tasks. This dual-objective trade-off makes ISAC a critical application scenario for multi-objective optimization theory. To address this, this paper employs the Dinkelbach method and the Successive Convex Approximation (SCA) technique to resolve the non-convexity of energy efficiency optimization problems. Furthermore, the Pareto Simulated Annealing (PSA) approach is applied to determine the Pareto boundary of the multi-objective optimization problem, achieving an optimized balance between communication energy efficiency and sensing energy efficiency. Experimental results demonstrate that the proposed scheme achieves approximately 20% energy savings compared to existing methods.
Keywords:
Integrated sensing and communication
Multi-objective optimization
Communication-centric
Sensing-centric
Energy efficiency
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