| 書目名稱 | Low-overhead Communications in IoT Networks | | 副標題 | Structured Signal Pr | | 編輯 | Yuanming Shi,Jialin Dong,Jun Zhang | | 視頻video | http://file.papertrans.cn/589/588917/588917.mp4 | | 概述 | Presents structured signal processing technologies for wireless communications.Describes low-overhead communications in IoT networks.Provides mathematical models and algorithms with theoretical guaran | | 圖書封面 |  | | 描述 | .The recent developments in wireless communications, networking, and embedded systems have driven various innovative Internet of Things (IoT) applications, e.g., smart cities, mobile healthcare, autonomous driving and drones. A common feature of these applications is the stringent requirements for low-latency communications. Considering the typical small payload size of IoT applications, it is of critical importance to reduce the size of the overhead message, e.g., identification information, pilot symbols for channel estimation, and control data. Such low-overhead communications also help to improve the energy efficiency of IoT devices. Recently, structured signal processing techniques have been introduced and developed to reduce the overheads for key design problems in IoT networks, such as channel estimation, device identification, and message decoding. By utilizing underlying system structures, including sparsity and low rank, these methods can achieve significant performance gains..This book provides an overview of four general structured signal processing models: a sparse linear model, a blind demixing model, a sparse blind demixing model, and a shuffled linear model, and dis | | 出版日期 | Book 2020 | | 關鍵詞 | Wireless communications; Internet of Things; convex optimization; nonconvex optimization; digital signal | | 版次 | 1 | | doi | https://doi.org/10.1007/978-981-15-3870-4 | | isbn_softcover | 978-981-15-3872-8 | | isbn_ebook | 978-981-15-3870-4 | | copyright | Springer Nature Singapore Pte Ltd. 2020 |
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