COURSE
Emerging Wireless Technologies for IoT
Information Hub / Internet of Things · 3 Credits
With the proliferation of IoT devices and applications, successful delivery of latency-critical and energy-constrained services pose new challenges for the next-generation wireless communications. In this course, basic knowledge of wireless communications will first be introduced, and optimization/AI assisted techniques to combat these challenges will also be briefly covered, following introduction to the state-of-the-art beyond-5G (B5G) technologies, in which we will investigate sustainable, scalable and AI endogenous wireless solutions for IoT.
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难度 · 从难到易
工作量 · 从劳累到轻松
评分 · 从苛刻到宽松
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3 Credits
官方数据更新时间: 2026-08-28 05:35:00
背景: General knowledge of linear algebra, probabilities, and basic concepts in machine learning (ML) are essential, while exposure to communications, networking, and signal processing as well as experiences in ML implementations are desirable.
3 Credits
官方数据更新时间: 2026-08-06 14:55:26
背景: General knowledge of linear algebra, probabilities, and basic concepts in machine learning (ML) are essential, while exposure to communications, networking, and signal processing as well as experiences in ML implementations are desirable.
3 Credits
官方数据更新时间: 2026-08-06 14:55:26
背景: General knowledge of linear algebra, probabilities, and basic concepts in machine learning (ML) are essential, while exposure to communications, networking, and signal processing as well as experiences in ML implementations are desirable.
3 Credits
官方数据更新时间: 2026-08-06 14:55:26
背景: General knowledge of linear algebra, probabilities, and basic concepts in machine learning (ML) are essential, while exposure to communications, networking, and signal processing as well as experiences in ML implementations are desirable.
3 Credits
官方数据更新时间: 2026-08-06 14:55:26
背景: General knowledge of linear algebra, probabilities, and basic concepts in machine learning (ML) are essential, while exposure to communications, networking, and signal processing as well as experiences in ML implementations are desirable.
3 Credits
官方数据更新时间: 2026-08-06 14:55:26
背景: General knowledge of linear algebra, probabilities, and basic concepts in machine learning (ML) are essential, while exposure to communications, networking, and signal processing as well as experiences in ML implementations are desirable.
3 Credits
官方数据更新时间: 2026-08-06 14:55:26
背景: General knowledge of linear algebra, probabilities, and basic concepts in machine learning (ML) are essential, while exposure to communications, networking, and signal processing as well as experiences in ML implementations are desirable.
3 Credits
官方数据更新时间: 2026-08-06 14:55:26
背景: General knowledge of linear algebra, probabilities, and basic concepts in machine learning (ML) are essential, while exposure to communications, networking, and signal processing as well as experiences in ML implementations are desirable.