| Description |
1 online resource (164 pages) |
| Contents |
Intro -- Preface -- Acknowledgements -- Contents -- Mathematical Notations -- 1 Introduction -- 1.1 Low-Overhead Communications in IoT Networks -- 1.1.1 Grant-Free Random Access -- 1.1.2 Pilot-Free Communications -- 1.1.3 Identification-Free Communications -- 1.2 Structured Signal Processing -- 1.2.1 Example: Compressed Sensing -- 1.2.2 General Structured Signal Processing -- 1.3 Outline -- References -- 2 Sparse Linear Model -- 2.1 Joint Activity Detection and Channel Estimation -- 2.2 Problem Formulation -- 2.2.1 Single-Antenna Scenario -- 2.2.2 Multiple-Antenna Scenario |
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2.3 Convex Relaxation Approach -- 2.3.1 Method: p-Norm Minimization -- 2.3.2 Algorithm: Smoothed Primal-Dual First-Order Methods -- 2.3.3 Analysis: Conic Integral Geometry -- 2.3.3.1 Conic Integral Geometry for the Sparse Linear Model -- 2.3.3.2 Computation and Estimation Trade-Offs -- 2.3.3.3 Simulation Results -- 2.4 Iterative Thresholding Algorithm -- 2.4.1 Algorithm: Approximate Message Passing -- 2.4.2 Analysis: State Evolution -- 2.4.2.1 State Evolution -- 2.4.2.2 Denoiser Designs -- 2.4.2.3 Asymptotic Performance of Device Activity Detection -- 2.4.2.4 Simulation Results -- 2.5 Summary |
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3.4.4 Simulation Results -- 3.5 Summary -- References -- 4 Sparse Blind Demixing -- 4.1 Joint Device Activity Detection, Data Decoding, and Channel Estimation -- 4.2 Problem Formulation -- 4.2.1 Single-Antenna Scenario -- 4.2.2 Multiple-Antenna Scenario -- 4.3 Convex Relaxation Approach -- 4.4 Difference-of-Convex-Functions (DC) Programming Approach -- 4.4.1 Sparse and Low-Rank Optimization -- 4.4.2 A DC Formulation for Rank Constraint -- 4.4.3 DC Algorithm for Minimizing a DC Objective -- 4.4.4 Simulations -- 4.5 Smoothed Riemannian Optimization on Product Manifolds |
| Summary |
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 discusses their applications in enabling low-overhead communications in IoT networks. Further, it presents practical algorithms based on both convex and nonconvex optimization approaches, as well as theoretical analyses that use various mathematical tools |
| Bibliography |
References-3 Blind Demixing-3.1 Joint Data Decoding and Channel Estimation-3.2 Problem Formulation-3.2.1 Cyclic Convolution-3.2.2 System Model-3.2.3 Representation in the Fourier Domain-3.3 Convex Relaxation Approach-3.3.1 Method: Nuclear Norm Minimization-3.3.2 Theoretical Analysis-3.4 Nonconvex Approaches-3.4.1 Regularized Wirtinger Flow-3.4.2 Regularization-Free Wirtinger Flow-3.4.3 Riemannian Optimization Algorithm-3.4.3.1 An Example on Riemannian Optimization-3.4.3.2 Riemannian Optimization on Product Manifolds for Blind Demixing |
| Notes |
5.4.4 Simulation Results |
| Bibliography |
Includes bibliographical references |
| Notes |
Print version record |
| Subject |
Signal processing -- Digital techniques.
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Internet of things.
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Computer networking & communications.
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Machine learning.
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Engineering: general.
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Computers -- Networking -- General.
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Computers -- Intelligence (AI) & Semantics.
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Technology & Engineering -- General.
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Internet of things
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Signal processing -- Digital techniques
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| Form |
Electronic book
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| Author |
Dong, Jialin
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Zhang, Jun
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| ISBN |
9789811538704 |
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9811538700 |
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