In this paper, we discuss a semi-blind channel estimation algorithm for rapidly time-varying channels, relying on a complex exponen-tial basis expansion model (CE-BEM) for the channel. However, whereas the original CE-BEM approach models a rectangularly windowed version of the channel, the proposed CE-BEM approach models a smoothly windowed version of the channel. This allows for a much better fit, and leads to better channel estimates. The obtained semi-blind channel estimates are subsequently used to construct a recently developed CE-BEM serial decision-feedback equalizer for CE-BEM channels. Simulation results are carried out to validate the proposed ideas. 1
Adaptive channel equalization without resorting to a training sequence is often referred to as blind...
In this thesis, we propose and investigate novel adaptive semi-blind channel estimation algorithms f...
Abstract—For turbo reception of coded transmissions over unknown doubly selective channels, such as ...
In this paper, we discuss a semi-blind channel estimation algorithm for rapidly time-varying channel...
In this paper, we propose an estimation technique for rapidly time-varying channels. We approximate ...
Abstract—This paper deals with pilot-based channel estimation for fast varying channels in Orthogona...
International audienceA channel estimation algorithm for MIMO-OFDM systems in Fast Time-Varying Envi...
We propose channel estimation and direct equalization techniques for transmission over doubly select...
In the fast time-varying channel scenario,a linear minimum mean square error (LMMSE) channel estimat...
We propose channel estimation and direct equalization techniques for transmission over doubly select...
It is known that the constant modulus (CM) property of the source signal can be exploited to blindly...
The complex exponential basis expansion model (CE-BEM) provides an accurate description for the time...
Channel state information (CSI) is indispensable for coherent detection in a wireless communication ...
Transmission of multimedia data is the goal of third generation (3G) cellular radio systems necessit...
Abstract — The task of channel estimation in a frequency-selective multi-input multi-output (MIMO) s...
Adaptive channel equalization without resorting to a training sequence is often referred to as blind...
In this thesis, we propose and investigate novel adaptive semi-blind channel estimation algorithms f...
Abstract—For turbo reception of coded transmissions over unknown doubly selective channels, such as ...
In this paper, we discuss a semi-blind channel estimation algorithm for rapidly time-varying channel...
In this paper, we propose an estimation technique for rapidly time-varying channels. We approximate ...
Abstract—This paper deals with pilot-based channel estimation for fast varying channels in Orthogona...
International audienceA channel estimation algorithm for MIMO-OFDM systems in Fast Time-Varying Envi...
We propose channel estimation and direct equalization techniques for transmission over doubly select...
In the fast time-varying channel scenario,a linear minimum mean square error (LMMSE) channel estimat...
We propose channel estimation and direct equalization techniques for transmission over doubly select...
It is known that the constant modulus (CM) property of the source signal can be exploited to blindly...
The complex exponential basis expansion model (CE-BEM) provides an accurate description for the time...
Channel state information (CSI) is indispensable for coherent detection in a wireless communication ...
Transmission of multimedia data is the goal of third generation (3G) cellular radio systems necessit...
Abstract — The task of channel estimation in a frequency-selective multi-input multi-output (MIMO) s...
Adaptive channel equalization without resorting to a training sequence is often referred to as blind...
In this thesis, we propose and investigate novel adaptive semi-blind channel estimation algorithms f...
Abstract—For turbo reception of coded transmissions over unknown doubly selective channels, such as ...