Joint Optimization of Communication Enhancement and Location Privacy Protection in RIS-Assisted Underwater Communication System

TL;DR

This paper introduces a novel RIS-assisted underwater acoustic communication system that simultaneously enhances data transmission and protects source location privacy by optimizing beamforming, precoding, and artificial noise through a multi-objective approach.

Contribution

It proposes a new architecture integrating artificial noise with RIS in underwater communication, and develops an iterative algorithm for joint optimization of communication and privacy.

Findings

Significant improvement in data transmission rates.

Effective interference with eavesdroppers' localization efforts.

Validated through simulations demonstrating enhanced privacy and performance.

Abstract

As the demand for underwater communication continues to grow, underwater acoustic RIS (UARIS), as an emerging paradigm in underwater acoustic communication (UAC), can significantly improve the communication rate of underwater acoustic systems. However, in open underwater environments, the location of the source node is highly susceptible to being obtained by eavesdropping nodes through correlation analysis, leading to the issue of location privacy in underwater communication systems, which has been overlooked by many studies. To enhance underwater communication and protect location privacy, we propose a novel UARIS architecture integrated with an artificial noise (AN) module. This architecture not only improves communication quality but also introduces noise to interfere with the eavesdroppers' attempts to locate the source node. We derive the Cram\'er-Rao Lower Bound (CRLB) for the localization method deployed by the eavesdroppers and, based on this, model the UARIS-assisted communication scenario as a multi-objective optimization problem. This problem optimizes transmission beamforming, reflective precoding, and noise factors to maximize communication performance and location privacy protection. To efficiently solve this non-convex optimization problem, we develop an iterative algorithm based on fractional programming. Simulation results validate that the proposed system significantly enhances data transmission rates while effectively maintaining the location privacy of the source node in UAC systems.