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

TL;DR

This paper introduces an efficient resource allocation method for a multi-user, multi-target underwater MIMO-OFDM ISAC system, balancing sensing and communication performance in complex environments.

Contribution

It proposes a novel interleaved OFDM-based MIMO UWA-ISAC system with a multi-objective optimization framework and a two-dimensional grouped random search algorithm for resource allocation.

Findings

Achieves 90% faster convergence than exhaustive search.

Maintains robustness under PRR and PAPR constraints.

Demonstrates effectiveness in real-world UWA channels.

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.