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Hyundung Shin

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2026

Joint Trajectory and Fluid Antenna Design for Secure UAV-Enabled ISAC

This letter investigates a secure UAV-enabled integrated sensing and communication (ISAC) system, where fluid antennas (FAs) are exploited to reconfigure the spatial response of the aerial transmitter. A joint optimization problem is formulated to maximize the average weighted sensing gain (AWSG) by jointly optimizing...

Jun-Yuan Fan, Xiao-Kai Song, Jie Tang et al. · 0 citations
2026

Quantum Fusion Learning for 6G Networks With Kolmogorov–Arnold Networks

Driven by the vision of intelligent and adaptive connectivity in the sixth-generation (6G) networks, future wireless systems are expected to support advanced applications such as cognitive resource allocation, semantic communication (SC), and low-latency integrated sensing and communication (ISAC) or digital twins. How...

Usama Inam Paracha, Uman Khalid, Syed Muhammad Abuzar Rizvi et al. · 0 citations
Review 2026

A Survey on Energy-Efficient Next-Generation Wireless Terahertz Communications

The emergence of sixth-generation (6G) wireless networks demands unprecedented improvements in data rates, connectivity, and energy-efficiency (EE), making the terahertz (THz) band a key enabler due to its vast, underutilized spectrum and high spatial resolution. This survey stands apart from previous studies by provid...

Shikha Maurya, Soumen Mondal, Rahul Pal et al. · 0 citations
Open access 2026

From Sensing to Secrecy: Active Eavesdropper Localization in Massive MIMO ISAC

Numerical results demonstrate that the proposed joint uplink and downlink ISAC framework achieves substantially improved localization accuracy in multipath scenarios and significantly enhances secrecy performance, compared to conventional secure ISAC systems.

Zong-Han Wang, Jia-Jun He, Z. Mobini et al. · 0 citations
2026

Distribution Deviation-Aware Split Federated Learning in Resource-Limited Wireless Networks

The escalating complexity of deep neural networks introduces substantial challenges to deploying federated learning (FL) in resource-limited edge environments. To address these limitations, split federated learning (SFL) has emerged as a promising paradigm, alleviating client-side computational and communication burden...

Chunfeng Xie, Zhixiong Chen, Wenqiang Yi et al. · 1 citation

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