A5044682367- Advanced MIMO Systems Optimization
- Energy Harvesting in Wireless Networks
- Advanced Wireless Communication Techniques
- Advanced Wireless Network Optimization
- Wireless Communication Networks Research
- Radio Frequency Integrated Circuit Design
- Cooperative Communication and Network Coding
- Complex Network Analysis Techniques
- Software-Defined Networks and 5G
- Human Mobility and Location-Based Analysis
- Wireless Networks and Protocols
- Transportation Planning and Optimization
- Full-Duplex Wireless Communications
Rice University
2023-2024
Nvidia (United States)
2023
University of Science and Technology
2013
The large number of antennas in massive MIMO systems allows the base station to communicate with multiple users at same time and frequency resource multi-user beamforming. However, highly correlated user channels could drastically impede spectral efficiency that beamforming can achieve. As such, it is critical for schedule a suitable group each block achieve maximum while adhering fairness constraints among users. In this paper, we consider scheduling problem its optimal solution known be...
The large number of antennas in massive MIMO systems allows the base station to communicate with multiple users at same time and frequency resource multi-user beamforming. However, highly correlated user channels could drastically impede spectral efficiency that beamforming can achieve. As such, it is critical for schedule a suitable group each block achieve maximum while adhering fairness constraints among users. In this paper, we consider scheduling problem its optimal solution known be...
As wireless communication systems strive to improve spectral efficiency, there has been a growing interest in employing machine learning (ML)-based approaches for adaptive modulation and coding scheme (MCS) selection. In this paper, we introduce new MCS selection framework massive MIMO that operates without any feedback from users <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">by solely relying on instantaneous uplink channel estimates.Ou</sup>...
An important aspect of 5G networks is the development Radio Access Network (RAN) slicing, a concept wherein virtualized infrastructure wireless subdivided into slices (or enterprises), tailored to fulfill specific use-cases. A key focus in this context efficient radio resource allocation meet various enterprises' service-level agreements (SLAs). In work, we introduce channel-aware and SLA-aware RAN slicing framework for massive multiple input output (MIMO) where extends incorporate spatial...
An important aspect of 5G networks is the development Radio Access Network (RAN) slicing, a concept wherein virtualized infrastructure wireless subdivided into slices (or enterprises), tailored to fulfill specific use-cases. A key focus in this context efficient radio resource allocation meet various enterprises' service-level agreements (SLAs). In work, we introduce Helix: channel-aware and SLA-aware RAN slicing framework for massive multiple input output (MIMO) where extends incorporate...
In the rapidly evolving field of wireless communication, Multiple Input Output (MIMO) networks have emerged as a pivotal technology, offering enhanced data rates and spectral efficiency by leveraging multiple antennas at both transmitter receiver. The introduction Open Radio Access Network (O-RAN) architecture has further revolutionized this domain, enabling greater flexibility, scalability, interoperability through its open interfaces software-defined approach. This paper presents DRAGON,...
As wireless communication systems strive to improve spectral efficiency, there has been a growing interest in employing machine learning (ML)-based approaches for adaptive modulation and coding scheme (MCS) selection. In this paper, we introduce new MCS selection framework massive MIMO that operates without any feedback from users by solely relying on instantaneous uplink channel estimates. Our proposed method can effectively operate multi-user scenarios where user imposes excessive delay...
This paper uses genetic algorithm to optimize public transportation network by extracting the topology of a local as an instance. An optimization model is formulated and characteristics optimal are analyzed. A simulation using multi-agent software NetLogo successfully implemented verify results. Results show validity in proposed algorithm. From study, it also found that great advantage for verification complex networks.