An allocation strategy integrated power, bandwidth, and subchannel in a RCC network
Haowei Zhang, Weijian Liu, Zhang Lin, Youwei Meng, Weihang Han, Tao Song, Rennong Yang
Abstract
Owing to the portability, cheapness and flexible deployment, the unmanned aerial vehicle-based radar and communication coexistence (RCC) systems are widely adopted in Internet of Things applications. A joint power, bandwidth, and subchannel allocation (JPBSA) strategy is proposed for a RCC network, aiming to optimize resource utilization under mutual spectrum interference. The Cramér-Rao lower bound (CRLB) is employed to assess the target localization accuracy. The optimization model is formulated as minimizing the sum of weighted predicted CRLBs while satisfying the communication data rate requirements and constraints of power and bandwidth budget. It is shown that the JPBSA problem falls into the mixed-integer programming problem. Even worse, the three variables are coherent in the objective function and constraints. A four-phase alternating optimization framework (FPAOF) is developed to address this issue. The FPAOF incorporates the joint convexification of radar and communication power allocation via Taylor approximation, bandwidth upper bound adaptation, and the opportunistic spectrum access-based method for subchannel allocation. Numerical evaluations demonstrate the proposed strategy’s superiority in terms of localization accuracy improvement and computational tractability in comparison to state-of-the-art methods. The findings also indicate the superiority of using CRLB as the optimization metric than the signal-to-interference-plus-noise and mutual information.