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2026

Learning to Place: Transformer-Based Movable Antenna Array Design for Region-Oriented Wireless Sensing

Movable antennas (MAs) boost sensing capabilities by exploiting the extra degrees of freedom (DoFs) through flexible positioning. The design of MA arrays is typically challenged by directional uncertainty, where the target’s precise angle is unknown. To address this, we propose a region-oriented design framework focusi...

Yang Xia, Chen Sun, Xi-Qi Gao · 0 citations
Preprint Sep 2026

Blockchain-based Proportional Fair Scheduling for Multi-Operator O-RAN

The openness and disaggregation of Open radio access network (O-RAN) facilitate resource sharing and coordination across networks, creating new demands for efficient and trustworthy cross-operator scheduling. However, such scheduling is beyond the scope and capability of conventional proportional fair scheduling (PFS),...

Kun Huang, Xintong Ling, Mei-Ning Wu et al. · 0 citations
2026

Leveraging Channel Charting for Localization With Weakly Supervised Learning

Channel charting (CC) is a self-supervised learning technique which aims to construct a lower-dimensional representation of the channel measurements, while preserving the neighboring relationship of users. In this letter, we propose a machine learning approach for radio-based localization task with the aid of CC, which...

Tian-Xiang Xu, Li You, Jue Wang et al. · 0 citations
2026

Precoding Design for PAPR Reduction in Mixed-Numerology MU-MIMO OFDM Systems

Orthogonal frequency division multiplexing (OFDM) is widely adopted in modern wireless systems for high spectral efficiency, yet its high peak-to-average power ratio (PAPR) limits power amplifier efficiency. Mixed-numerology transmission, which enables flexible subcarrier spacing for diverse services, further aggravate...

Shuai Cui, Ruiding Hou, Jia-Heng Wang et al. · 0 citations

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