This paper provides a tutorial introduction to the constant modulus (CM) criterion for blind
fractionally spaced equalizer (FSE) design via a (stochastic) gradient descent algorithm …

Blind system identification (BSI) is a fundamental signal processing technology aimed at
retrieving a system's unknown information from its output only. This technology has a wide …

The field of Digital Signal Processing has developed so fast in the last five decades that it
can be found in the graduate and undergraduate programs of most universities. This …

With solid theoretical foundations and numerous potential applications, Blind Signal
Processing (BSP) is one of the hottest emerging areas in Signal Processing. This volume …

Spectrum sensing is a fundamental component in a cognitive radio. In this paper, we
propose new sensing methods based on the eigenvalues of the covariance matrix of signals …

This second edition of Adaptive Filters: Theory and Applications has been updated
throughout to reflect the latest developments in this field; notably an increased coverage …

Conventional blind channel identification algorithms are based on channel outputs and
knowledge of the probabilistic model of channel input. In some practical applications …

Space-time processing can improve network capacity, coverage, and quality by reducing co-
channel interference (CCI) while enhancing diversity and array gain. This article focuses …

As the growing demand for mobile communications is constantly increasing, the need for
better coverage, improved capacity, and higher transmission quality rises. Thus, a more …

This survey provides a brief introduction to compressed sensing as well as several major
algorithms to solve it and its various applications to communications systems. We firstly …