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Adaptive wireless communications : MIMO channels and networks / Daniel W. Bliss, Arizona State University ; Siddhartan Govindasamy, Franklin W. Olin College of Engineering, Massachusetts.

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Adopting a balanced mix of theory, algorithms and practical design issues, this comprehensive volume explores cutting-edge applications in adaptive wireless communications and the implications these techniques have for future wireless network performance. Presenting practical concerns in the context...

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Bibliographic Details
Online Access: Full Text (via Cambridge)
Main Authors: Bliss, Daniel W., 1966- (Author), Govindasamy, Siddhartan (Author)
Format: eBook
Language:English
Published: Cambridge : Cambridge University Press, 2013.
Subjects:
MIMO systems.
Wireless communication systems.
Adaptive signal processing.
Adaptive signal processing
MIMO systems
Wireless communication systems
Table of Contents:
  • History
  • Notational and mathematical preliminaries
  • Probability and statistics
  • Wireless communications fundamentals
  • Simple channels
  • Antenna arrays
  • Angle-of-arrival estimation
  • MIMO channel
  • Spatially adaptive receivers
  • Dispersive and doubly dispersive channels
  • Space-time coding
  • 2 x 2 network
  • Cellular networks
  • Ad hoc networks
  • Medium-access-control protocols
  • Cognitive radios
  • Multiple-antenna acquisition and synchronization
  • Practical issues.
  • 2.14.4 Lambert W function
  • 2.14.5 Bessel functions
  • 2.14.6 Error function
  • 2.14.7 Gaussian Q-function
  • 2.14.8 Marcum Q-function
  • Problems
  • 3 Probability and statistics
  • 3.1 Probability
  • 3.1.1 Bayes' theorem
  • 3.1.2 Change of variables
  • 3.1.3 Central moments of a distribution
  • 3.1.4 Noncentral moments of a distribution
  • 3.1.5 Characteristic function
  • 3.1.6 Cumulants of distributions
  • 3.1.7 Multivariate probability distributions
  • 3.1.8 Gaussian distribution
  • 3.1.9 Rayleigh distribution
  • 3.1.10 Exponential distribution
  • 3.1.11 Central χ2 distribution
  • 3.1.12 Noncentral χ2 distribution
  • 3.1.13 F distribution
  • 3.1.14 Rician distribution
  • 3.1.15 Nakagami distribution
  • 3.1.16 Poisson distribution
  • 3.1.17 Beta distribution
  • 3.1.18 Logarithmically normal distribution
  • 3.1.19 Sum of random variables
  • 3.1.20 Product of Gaussians
  • 3.2 Convergence of random variables
  • 3.2.1 Convergence modes of random variables
  • 3.2.2 Relationship between modes of convergence
  • 3.3 Random processes
  • 3.3.1 Wide-sense stationary random processes
  • 3.3.2 Action of linear-time-invariant systems on wide-sense stationary random processes
  • 3.3.3 White-noise processes
  • 3.4 Poisson processes
  • 3.5 Eigenvalue distributions of finite Wishart matrices
  • 3.6 Asymptotic eigenvalue distributions of Wishart matrices
  • 3.6.1 Marcenko-Pastur theorem
  • 3.7 Estimation and detection in additive Gaussian noise
  • 3.7.1 Estimation in additive Gaussian noise
  • 3.7.2 Detection in additive Gaussian noise
  • 3.7.3 Receiver operating characteristics
  • 3.8 Cramer-Rao parameter estimation bound
  • 3.8.1 Real parameter formulation
  • 3.8.2 Real multivariate Cramer-Rao bound
  • 3.8.3 Cramer-Rao bound for complex parameters
  • Problems
  • 4 Wireless communications fundamentals
  • 4.1 Communication stack
  • 4.2 Reference digital radio link.

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