相關主題
商品描述
Comprehensive reference covering signal detection for random access in IoT systems from the beginner to expert level
With a carefully balanced blend of theoretical elements and applications, IoT Signal Detection is an easy-to-follow presentation on signal detection for IoT in terms of device activity detection, sparse signal detection, collided signal detection, round-trip delay estimation, and backscatter signal division, building progressively from basic concepts and important background material up to an advanced understanding of the subject. Various signal detection and estimation techniques are explained, e.g., variational inference algorithm and compressive sensing reconstruction algorithm, and a number of recent research outcomes are included to provide a review of the state of the art in the field.
Written by four highly qualified academics, IoT Signal Detection discusses sample topics such as:
- ML, ZF, and MMSE detection, Markov chain Monte Carlo-based detection, variational inference-based detection, compressive sensing-based detection
- Sparse signal detection for multiple access, covering Bayesian compressive sensing algorithm and structured subspace pursuit algorithm
- Collided signal detection for multiple access using automatic modulation classification algorithm, round-trip delay estimation for collided signals
- Signal detection for backscatter signals, covering central limited theorem-based detection including detection algorithms, performance analysis, and simulation results
- Signal design for multi-cluster coordination, covering successive interference cancellation design, device grouping and power control, and constructive interference-aided multi-cluster coordination
With seamless coverage of the subject presented in a linear and easy-to-understand way, IoT Signal Detection is an ideal reference for both graduate students and practicing engineers in wireless communications.
商品描述(中文翻譯)
綜合參考資料，涵蓋從初學者到專家級的物聯網系統隨機存取信號檢測
《IoT Signal Detection》以理論元素與應用的精心平衡，提供了一個易於理解的物聯網信號檢測介紹，內容包括設備活動檢測、稀疏信號檢測、碰撞信號檢測、往返延遲估計及反向散射信號分割，逐步從基本概念和重要背景材料建構到對該主題的深入理解。書中解釋了各種信號檢測和估計技術，例如變分推斷算法和壓縮感知重建算法，並包含了一些近期的研究成果，以提供該領域的最新進展回顧。
本書由四位高素質的學者撰寫，討論的主題包括：
- ML、ZF 和 MMSE 檢測、基於馬可夫鏈蒙特卡羅的檢測、基於變分推斷的檢測、基於壓縮感知的檢測
- 多重存取的稀疏信號檢測，涵蓋貝葉斯壓縮感知算法和結構化子空間追尋算法
- 使用自動調變分類算法的多重存取碰撞信號檢測，碰撞信號的往返延遲估計
- 反向散射信號的檢測，涵蓋基於中心極限定理的檢測，包括檢測算法、性能分析和模擬結果
- 多集群協調的信號設計，涵蓋連續干擾消除設計、設備分組和功率控制，以及建設性干擾輔助的多集群協調
《IoT Signal Detection》以線性且易於理解的方式無縫覆蓋該主題，是無線通信領域研究生和實務工程師的理想參考資料。
作者簡介
Rui Han, PhD, is an Associate Professor at the School of Cyber Science and Technology, Beihang University. Jingjing Wang, PhD, is a Professor at the School of Cyber Science and Technology, Beihang University. Lin Bai, PhD, is a Professor at the School of Cyber Science and Technology, Beihang University. Jianwei Liu, PhD, is a Professor the School of Cyber Science and Technology, Beihang University.
作者簡介(中文翻譯)
Rui Han, PhD，是北京航空航天大學網絡科學與技術學院的副教授。Jingjing Wang, PhD，是北京航空航天大學網絡科學與技術學院的教授。Lin Bai, PhD，是北京航空航天大學網絡科學與技術學院的教授。Jianwei Liu, PhD，是北京航空航天大學網絡科學與技術學院的教授。
