Cognitive Networked Sensing and Big Data

Wireless Distributed Computing and Cognitive Sensing defines high-dimensional data processing in the context of wireless distributed computing and cognitive sensing. This book presents the challenges that are unique to this area such as synchronization caused by the high mobility of the nodes. The author will discuss the integration of software defined radio implementation and testbed development. The book will also bridge new research results and contextual reviews. Also the author provides an examination of large cognitive radio network; hardware testbed; distributed sensing; and distributed computing.

Table of Contents

Part I Theory
Chapter 1: Mathematical Foundation
Chapter 2: Sums of Matrix-Valued Random Variables
Chapter 3: Concentration of Measure
Chapter 4: Concentration of Eigenvalues and Their Functionals
Chapter 5: Non-asymptotic, Local Theory of Random Matrices
Chapter 6: Asymptotic, Global Theory of Random Matrices

Part II Applications
Chapter 7: Compressed Sensing and Sparse Recovery
Chapter 8: Matrix Completion and Low-Rank Matrix Recovery
Chapter 9: Covariance Matrix Estimation in High Dimensions
Chapter 10: Detection in High Dimensions
Chapter 11: Probability Constrained Optimization
Chapter 12: Database Friendly Data Processing
Chapter 13: From Network to Big Data