Integrated sensing and communication (ISAC) technology is crucial for next-generation underwater networks. However, covering multiple users and targets and balancing sensing and communication performance in complex underwater acoustic (UWA) environments remains challenging. This paper proposes an interleaved orthogonal frequency division multiplexing-based MIMO UWA-ISAC system, which employs a horizontal array to simultaneously transmit adaptive waveforms for downlink multi-user communication and omnidirectional target sensing. A multi-objective optimization framework is formulated to maximize the product of communication rate and range (PRR) while ensuring sensing performance and peak-to-average power ratio (PAPR) constraints. To solve this mixed-integer nonconvex problem, a two-dimensional grouped random search algorithm is developed, efficiently exploring subcarrier interleaved patterns and resource allocation schemes. Numerical simulations under real-world UWA channels demonstrate the designed system's superiority and effectiveness: our algorithm achieves 90% faster convergence than conventional exhaustive search with only a marginal 0.5 kbps km PRR degradation. Furthermore, the proposed resource allocation scheme maintains robustness beyond the baseline allocation schemes under stringent PRR and PAPR constraints.

翻译：集成感知与通信（ISAC）技术对下一代水下网络至关重要。然而，在复杂的水声（UWA）环境中覆盖多用户与多目标，并平衡感知与通信性能仍具挑战性。本文提出一种基于交错正交频分复用的MIMO UWA-ISAC系统，该系统采用水平阵列同时发射自适应波形，以实现下行多用户通信与全向目标感知。研究构建了一个多目标优化框架，在确保感知性能与峰均功率比（PAPR）约束的同时，最大化通信速率与距离的乘积（PRR）。为求解这一混合整数非凸问题，开发了一种二维分组随机搜索算法，高效探索子载波交错模式与资源分配方案。基于真实UWA信道的数值仿真验证了所设计系统的优越性与有效性：本算法相比传统穷举搜索收敛速度快90%，且PRR仅轻微下降0.5 kbps·km。此外，在严格的PRR与PAPR约束下，所提出的资源分配方案较基线分配方案展现出更强的鲁棒性。