Advancements in wireless communication : AI-driven error correcting code design and multiuser system optimization
Abstract/Contents
- Abstract
- The rapid expansion of wireless technology in recent years has ushered in an era where an increasing number of devices are interconnected. These devices, from the Internet of Things sensors to industrial automation systems, place stringent demands on wireless networks in terms of data rates and latency. As the wireless landscape evolves towards 5G and next-generation networks, the need for efficient and reliable communication systems becomes paramount. This dissertation presents a comprehensive exploration of advancements in wireless communication design, focusing on two pivotal areas: AI-based polar code design and multi-user system optimization. The first part of the dissertation ventures into the realm of AI-based polar code design. Polar codes, known for their error correction capabilities, play a pivotal role in ensuring reliable data transmission. This part introduces two novel techniques that harness the power of reinforcement learning, transforming polar code design into maze-traversing game and graph evolution process, respectively. Both learning-based approaches successfully find polar codes that outperform the existing ones, and the graph-based method offers scalability and adaptability that breaks through bottlenecks seen in other learning-based methods for code design. The dissertation's second part turns its focus to multi-user system optimization within next-generation networks, particularly in cases where the number of users exceeds the wireless environment's capacity. This part conducts an in-depth analysis of optimization algorithms meticulously crafted to maximize system capacity. Additionally, it highlights the practical implementation of newly-developed, readily-available software solutions. In an age characterized by the intricate interplay of connected devices and users, these optimization techniques assume a central role in shaping the seamless, interconnected experiences that next-generation networks are expected to deliver. This dissertation's findings underscore the transformative potential of interdisciplinary research in wireless communication. By addressing the complex challenges posed by evolving wireless technologies, it paves the way for innovative solutions that can push network capacities to their limits.
Description
| Type of resource | text |
|---|---|
| Form | electronic resource; remote; computer; online resource |
| Extent | 1 online resource. |
| Place | California |
| Place | [Stanford, California] |
| Publisher | [Stanford University] |
| Copyright date | 2023; ©2023 |
| Publication date | 2023; 2023 |
| Issuance | monographic |
| Language | English |
Creators/Contributors
| Author | Liao, Yun |
|---|---|
| Degree supervisor | Cioffi, John |
| Degree supervisor | Wootters, Mary |
| Thesis advisor | Cioffi, John |
| Thesis advisor | Wootters, Mary |
| Thesis advisor | Mondelli,Marco |
| Degree committee member | Mondelli,Marco |
| Associated with | Stanford University, School of Engineering |
| Associated with | Stanford University, Department of Electrical Engineering |
Subjects
| Genre | Theses |
|---|---|
| Genre | Text |
Bibliographic information
| Statement of responsibility | Yun Liao. |
|---|---|
| Note | Submitted to the Department of Electrical Engineering. |
| Thesis | Thesis Ph.D. Stanford University 2023. |
| Location | https://purl.stanford.edu/hh850qx7256 |
Access conditions
- Copyright
- © 2023 by Yun Liao
- License
- This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).
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