arXiv subjects

Huiyun Xia

Publications and source records attributed to Huiyun Xia.

5 recordsLinked to original sources

arXiv2026

Security-Spectral Efficiency Tradeoff in STAR-RIS RSMA: A Max-Min Fairness Framework

Simultaneously transmitting and reflecting reconfigurable intelligent surfaces (STAR-RISs) enable full-space coverage but also expose wireless transmissions to security from multiple spatial directions. This paper investigates a STAR-RIS-assisted secure RSMA system where both internal and external eavesdroppers may coexist in the transmission and reflection regions. In such a scenario, the RSMA common stream simultaneously serves legitimate users, impairs external eavesdroppers, and avoids assisting internal eavesdroppers, leading to a challenging trade-off between spectral efficiency and confidentiality. To address this issue, we formulate a max-min fairness problem under secrecy constraints and develop an iterative algorithm to jointly optimize transmit beamforming and STAR-RIS phase shifts. Simulation results demonstrate that the proposed scheme improves spectral efficiency while maintaining confidentiality.

cs.IT↗

arXiv2025

Hybrid Beamfocusing Design for RSMA-Enhanced Near-Field Secure Communications

Near-field spherical wavefronts enable spotlight-like beam focusing to mitigate unintended energy leakage, creating new opportunities for physical-layer security (PLS). However, under hybrid analog-digital (HAD) antenna architectures, beamfocusing alone may not provide foolproof privacy protection due to reduced focusing precision. To address this issue, this paper proposes a rate-splitting multiple access (RSMA)-enhanced secure transmit scheme for near-field communications with fully-connected or sub-connected HAD architectures. In the proposed scheme, the common stream is designed for dual purposes, delivering the desired message for legitimate users while acting as artificial noise to disrupt eavesdropping. The primary objective is to maximize the minimum secrecy rate by jointly optimizing the analog beamfocuser, digital beamfocuser, and common secrecy rate allocation. To solve the formulated non-convex problem, we develop a penalty-based alternating optimization algorithm. Specifically, the variables are partitioned into three blocks, where one block is solved via a surrogate optimization method, while the others are updated in closed form. Simulation results reveal that our transmit scheme: (1) approaches fully digital beamfocusing with substantially fewer radio frequency chains, (2) outperforms conventional beamfocusing-only and far-field security schemes, and (3) preserves secrecy without significantly compromising communication rates.

cs.IT↗

arXiv2023

Weighted Sum-Rate Maximization for Rate-Splitting Multiple Access Based Multi-antenna Broadcast Channel with Confidential Messages

In this paper, we take all users' secrecy rate requirements into consideration and propose a rate-splitting multiple access (RSMA)-based secure beamforming approach to maximize the weighted sum-rate (WSR), where multi-user interference (MUI) is partially decoded and partially treated as noise. User messages are split and encoded into common and private streams. Each user not only decodes the common stream and the intended private stream, but also eavesdrops other users' private streams. To solve the introduced non-convex security constraints in the formulated problem, a successive convex approximation (SCA)-based approach is first proposed to maximize the instantaneous WSR under perfect channel state information at the transmitter (CSIT). When only imperfect CSIT is available, to ensure robustness, a weighted ergodic sum-rate maximization problem is formulated. Then, a joint weighted minimum mean square error and SCA-based alternating optimization algorithm is proposed to optimize the precoder. Numerical results demonstrate that, compared with baseline schemes, the performance advantage of the proposed RSMA-based secure beamforming design has been shown in terms of WSR and robustness to channel errors while ensuring all users' security requirements thanks to its powerful interference management capability.

cs.IT↗

arXiv2022

Time-triggered Federated Learning over Wireless Networks

The newly emerging federated learning (FL) framework offers a new way to train machine learning models in a privacy-preserving manner. However, traditional FL algorithms are based on an event-triggered aggregation, which suffers from stragglers and communication overhead issues. To address these issues, in this paper, we present a time-triggered FL algorithm (TT-Fed) over wireless networks, which is a generalized form of classic synchronous and asynchronous FL. Taking the constrained resource and unreliable nature of wireless communication into account, we jointly study the user selection and bandwidth optimization problem to minimize the FL training loss. To solve this joint optimization problem, we provide a thorough convergence analysis for TT-Fed. Based on the obtained analytical convergence upper bound, the optimization problem is decomposed into tractable sub-problems with respect to each global aggregation round, and finally solved by our proposed online search algorithm. Simulation results show that compared to asynchronous FL (FedAsync) and FL with asynchronous user tiers (FedAT) benchmarks, our proposed TT-Fed algorithm improves the converged test accuracy by up to 12.5% and 5%, respectively, under highly imbalanced and non-IID data, while substantially reducing the communication overhead.

cs.LG↗

arXiv2022

Weighted Sum-Rate Maximization for Rate-Splitting Multiple Access Based Secure Communication

As investigations on physical layer security evolve from point-to-point systems to multi-user scenarios, multi-user interference (MUI) is introduced and becomes an unavoidable issue. Different from treating MUI totally as noise in conventional secure communications, in this paper, we propose a rate-splitting multiple access (RSMA)-based secure beamforming design, where user messages are split and encoded into common and private streams. Each user not only decodes the common stream and the intended private stream, but also tries to eavesdrop the private streams of other users. We formulate a weighted sum-rate (WSR) maximization problem subject to the secrecy rate requirements of all users. To tackle the non-convexity of the formulated problem, a successive convex approximation (SCA)-based approach is adopted to convert the original non-convex and intractable problem into a low-complexity suboptimal iterative algorithm. Numerical results demonstrate that the proposed secure beamforming scheme outperforms the conventional multi-user linear precoding (MULP) technique in terms of the WSR performance while ensuring user secrecy rate requirements.

cs.IT↗