IRS-Assisted Communication Performance Optimization Method for Shipborne DFRC System
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Elsevier BV
Abstract
Dual-functional radar-communication (DFRC) has emerged as an effective solution in recent years to address spectrum scarcity in maritime environments, enabling efficient integrated communication and sensing. To mitigate path loss over complex sea surfaces, the intelligent reflecting surface (IRS) is introduced into DFRC systems, enhancing signal quality by providing an additional propagation path. To address the impact of sea wave fluctuations on the communication channel of maritime vessels, an alternating optimization (AO) algorithm based on semidefinite relaxation and fractional programming (SDR-FP) is proposed. First, the non-ideal channel state information (CSI) is modeled using a bounded channel uncertainty model via the S-procedure. Second, under constraints on radar detection performance and transmit power, the problem is formulated to maximize the communication sum-rate. Next, the proposed AO algorithm decomposes the original high-dimensional problem into two low-complexity subproblems. Finally, a minimization algorithm is applied to reformulate the non-convex subproblem into a tractable quadratically constrained quadratic program (QCQP). Simulation results demonstrate that the proposed method significantly enhances the communication sum-rate while achieving faster convergence compared to benchmarks.Description
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Signal Processing, ISSN: 0165-1684 (Print), Elsevier BV, 110377-110377. doi: 10.1016/j.sigpro.2025.110377
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This is the Author's Accepted Manuscript of a journal article published as a Pre-Proof In Press at DOI: 10.1016/j.sigpro.2025.110377 in Signal Processing. This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. © 2025 Published by Elsevier B.V.