Optimal Power Allocation Method for Integrated Sensing and Communications System Based on Quantum Crystal Structure Algorithm

Selecting optimal power allocation methods for integrated sensing and communications (ISAC) systems remains an active research frontier. This paper formulates a constrained minimization problem incorporating Cramér-Rao bound (CRB) metrics and communication requirements to optimize joint performance. A novel quantum crystal structure algorithm (QCryStAl) is proposed to solve this coupled optimization challenge, synergistically combining the strengths of the crystal structure algorithm (CryStAl) with quantum computation principles. Extensive simulations validate the efficacy of the QCryStAl-based power allocation scheme, demonstrating its superiority over existing methods through enhanced communication performance while maintaining precise target estimation capabilities.