This paper introduces an iterative space time soft estimator (ISSE) that performs joint channel estimation and soft data detection in time-varying multiple-input multiple-output channels.
The paper presents a method for constructing space-time block codes for multiple-input multiple-output channels by concatenating orthogonal designs with the so-called diversity transform.
For the Gaussian model, we develop two new outer bounds using recent results on the secrecy capacity of the Gaussian multiple-input multiple-output channels in the presence of a multiantenna eavesdropper (MIMOME) in [4 6].
For this special type of multiple-input multiple-output channels, we propose a practical Vandermonde precoding that projects the confidential messages in the null space of the channel seen by receiver 2 while superposing the common message.
The analysis presented here can easily be extended with respect to the modeling and simulation of frequency-selective single-input single-output (SISO) and multiple-input multiple-output channels.
R-dimensional (R-D) harmonic retrieval (HR) in colored noise, where R≥2, is required in numerous applications including radar, sonar, mobile communications, multiple-input multiple-output channel estimation and nuclear magnetic resonance spectroscopy.
The method introduced in [24], for example, finds an ML solution for a joint single-input multiple-output channel and sequence estimation problem using a two-step procedure: (1) channel estimates are obtained for every possible data sequence, and (2) the ML data sequence and corresponding channel estimate are selected.
Tools from game theory [6] have been widely applied to study the resource allocation and power control problems in fading MAC [7], as well as many other types of channels, such as orthogonal frequency division multiplexing (OFDM) [8], multiple input and multiple output (MIMO) channels [9, 10], and interference channels [11].
