Search Results for author: Charlie Zhang

Found 5 papers, 0 papers with code

Nested Construction of Polar Codes via Transformers

no code implementations30 Jan 2024 Sravan Kumar Ankireddy, S Ashwin Hebbar, Heping Wan, Joonyoung Cho, Charlie Zhang

Tailoring polar code construction for decoding algorithms beyond successive cancellation has remained a topic of significant interest in the field.

Towards Intelligent Network Management: Leveraging AI for Network Service Detection

no code implementations14 Oct 2023 Khuong N. Nguyen, Abhishek Sehgal, Yuming Zhu, Junsu Choi, Guanbo Chen, Hao Chen, Boon Loong Ng, Charlie Zhang

As the complexity and scale of modern computer networks continue to increase, there has emerged an urgent need for precise traffic analysis, which plays a pivotal role in cutting-edge wireless connectivity technologies.

Management Traffic Classification

THz Band Channel Measurements and Statistical Modeling for Urban Microcellular Environments

no code implementations3 Dec 2021 Naveed A. Abbasi, Jorge Gomez-Ponce, Revanth Kondaveti, Ashish Kumar, Eshan Bhagat, Rakesh N S Rao, Shadi Abu-Surra, Gary Xu, Charlie Zhang, Andreas F. Molisch

The THz band (0. 1-10 THz) has attracted considerable attention for next-generation wireless communications, due to the large amount of available bandwidth that may be key to meet the rapidly increasing data rate requirements.

THz Band Channel Measurements and Statistical Modeling for Urban D2D Environments

no code implementations28 Sep 2021 Naveed A. Abbasi, Jorge Gomez-Ponce, Revanth Kondaveti, Shahid M. Shaikbepari, Shreyas Rao, Shadi Abu-Surra, Gary Xu, Charlie Zhang, Andreas F. Molisch

In this paper, we present a first extensive set of channel measurements for urban outdoor environments that are ultra-wideband (1 GHz 3dB bandwidth), and double-directional where both the transmitter and receiver are at the same height.

Pareto Deterministic Policy Gradients and Its Application in 5G Massive MIMO Networks

no code implementations2 Dec 2020 Zhou Zhou, Yan Xin, Hao Chen, Charlie Zhang, Lingjia Liu

In this paper, we consider jointly optimizing cell load balance and network throughput via a reinforcement learning (RL) approach, where inter-cell handover (i. e., user association assignment) and massive MIMO antenna tilting are configured as the RL policy to learn.

Reinforcement Learning (RL)

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