Efficient Resource Allocation for Multi-User and Multi-Target MIMO-OFDM Underwater ISAC

2025-12-14

AI Summary

In complex underwater acoustic (UWA) environments, MIMO-OFDM integrated sensing and communication (ISAC) systems face significant challenges in jointly supporting multi-user communications and omnidirectional multi-target sensing. Method: This paper proposes an interleaved-OFDM-based MIMO-UWA-ISAC architecture. It introduces a novel multi-objective resource allocation framework jointly optimizing the product of communication rate and sensing range (PRR), and designs a two-dimensional grouped random search algorithm to solve the resulting mixed-integer non-convex problem. Furthermore, it incorporates peak-to-average power ratio (PAPR)-constrained subcarrier grouping and adaptive horizontal array transmission. Contribution/Results: Compared with exhaustive search, the proposed algorithm achieves a 90% faster convergence while incurring only a marginal PRR degradation of 0.5 kbps·km. Under stringent PRR and PAPR constraints, it significantly outperforms existing baseline schemes, demonstrating superior efficiency and practicality for UWA-ISAC.

Technology Category

• Search and Optimization: Mixed Discrete/Continuous Search
• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Constraint Satisfaction and Optimization: Mixed Discrete/Continuous Optimization

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Experiences and lessons learnt from Web-based algorithms and system deployments
• Search and Retrieval-Augmented AI: Efficiency and scalability of Web search engines
• User Modeling, Personalization and Recommendation: User modeling and simulation for interactive and conversational systems

Abstract

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.

Problem

• Optimizes resource allocation for multi-user multi-target underwater ISAC systems
• Balances communication and sensing performance in complex acoustic environments
• Solves mixed-integer nonconvex optimization with efficient search algorithms

Innovation

• Interleaved OFDM-based MIMO system for underwater ISAC
• Multi-objective optimization maximizes communication-sensing product
• Two-dimensional grouped random search algorithm for resource allocation