arXiv subjects

Monir Abughalwa

Publications and source records attributed to Monir Abughalwa.

3 recordsLinked to original sources

arXiv2026

Secrecy Sum-Rate Maximization in Finite Blocklength IRS-aided Systems With Perfect and Imperfect CSI

The rapid growth of the Internet of Things (IoT) requires efficient and secure communication technologies to enable ultra-reliable low-latency (URLLC) communication applications. Intelligent reflecting surfaces (IRS) have emerged as a promising solution to enhance IoT network secrecy performance by improving signal quality for legitimate devices (Bob), while thwarting the eavesdropper (Eve) interception. However, ensuring secrecy across multiple users, given their diverse channels and locations, is challenging, especially under finite blocklength (FBR) constraints, which are common in IoT networks. This paper investigates the secrecy performance of IRS-aided URLLC systems under three channel state information (CSI) scenarios: perfect CSI, imperfect CSI, and unknown eavesdropper's CSI. We first formulate a non-convex optimization problem to maximize the system's sum secrecy rate (SSR) by jointly optimizing the transmitter's beamforming and the IRS's passive reflective elements, while maintaining FBR-related latency and transmission duration constraints. For imperfect CSI, the semi-infinite uncertainty constraints are transformed into finite linear matrix inequalities (LMIs) via a successive convex approximation (SCA)-based approach, and the proposed algorithm is proven to converge to a locally optimal solution with low computational complexity.

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arXiv2025

Secure Communications for All Users in Low-Resolution IRS-aided Systems Under Imperfect and Unknown CSI

Provisioning secrecy for all users, given the heterogeneity and uncertainty of their channel conditions, locations, and the unknown location of the attacker/eavesdropper, is challenging and not always feasible. This work takes the first step to guarantee secrecy for all users where a low resolution intelligent reflecting surfaces (IRS) is used to enhance legitimate users' reception and thwart the potential eavesdropper (Eve) from intercepting. In real-life scenarios, due to hardware limitations of the IRS' passive reflective elements (PREs), the use of a full-resolution (continuous) phase shift (CPS) is impractical. In this paper, we thus consider a more practical case where the phase shift (PS) is modeled by a low-resolution (quantized) phase shift (QPS) while addressing the phase shift error (PSE) induced by the imperfect channel state information (CSI). To that end, we aim to maximize the minimum secrecy rate (SR) among all users by jointly optimizing the transmitter's beamforming vector and the IRS's passive reflective elements (PREs) under perfect/imperfect/unknown CSI. The resulting optimization problem is non-convex and even more complicated under imperfect/unknown CSI. The resulting optimization problem is non-convex and even more complicated under imperfect/unknown CSI. To tackle it, we linearize the objective function and decompose the problem into sequential subproblems. When the perfect CSI is not available, we use the successive convex approximation (SCA) approach to transform imperfect CSI related semi-infinite constraints into finite linear matrix inequalities (LMI). We prove that our proposed algorithm converges to a locally optimal solution with low computational complexity. Extensive simulations with practical settings show that our approach can ensure secure communication for all users while the IRS's PREs are quantized and are affected by the PSE.

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arXiv2025

"Security for Everyone" in Finite Blocklength IRS-aided Systems With Perfect and Imperfect CSI

Provisioning secrecy for all users, given the heterogeneity in their channel conditions, locations, and the unknown location of the attacker/eavesdropper, is challenging and not always feasible. The problem is even more difficult under finite blocklength constraints that are popular in ultra-reliable low-latency communication (URLLC) and massive machine-type communications (mMTC). This work takes the first step to guarantee secrecy for all URLLC/mMTC users in the finite blocklength regime (FBR) where intelligent reflecting surfaces (IRS) are used to enhance legitimate users' reception and thwart the potential eavesdropper (Eve) from intercepting. To that end, we aim to maximize the minimum secrecy rate (SR) among all users by jointly optimizing the transmitter's beamforming and IRS's passive reflective elements (PREs) under the FBR latency constraints. The resulting optimization problem is non-convex and even more complicated under imperfect channel state information (CSI). To tackle it, we linearize the objective function, and decompose the problem into sequential subproblems. When perfect CSI is not available, we use the successive convex approximation (SCA) approach to transform imperfect CSI-related semi-infinite constraints into finite linear matrix inequalities (LMI). We prove that our proposed algorithm converges to a locally optimal solution with low computational complexity thanks to our closed-form linearization approach. This makes the solution scalable for large IRS deployments. Extensive simulations with practical settings show that our approach can ensure secure communication for all users while satisfying FBR constraints even with only imperfect CSI.

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