Title :
Semi-Analytical Performance Prediction Method for Iterative MMSE-IC Detection and Semi-Blind Channel Estimation
Author :
Ning, Baozhu ; Visoz, Raphaël ; Berthet, Antoine O.
Author_Institution :
Orange Labs., Issy-les-Moulineaux, France
Abstract :
In this paper, a novel semi-analytical performance prediction method is proposed for iterative MMSE-IC detection and semi-blind channel estimation. It is examplified in the context of single-user MIMO-OFDM transmission which we model by a discrete-input MIMO P-block fading flat Rayleigh channel in the frequency domain. The proposed method extends existing symbolwise Mutual Information Effective SNR Metric (MIESM) link-to system approach to the context of imperfect channel state information and semi-blind channel estimation at the receiver side. It allows to compute the average Block Error Rate (BLER) conditional on an initial pilot-assisted channel estimation and long term channel distribution information. Thus, the proposed method takes advantage of all the available a priori information before actual data transmission and could be equally employed for slow and fast link adaptation.
Keywords :
MIMO communication; OFDM modulation; Rayleigh channels; channel estimation; error statistics; interference suppression; iterative methods; least mean squares methods; average block error rate; data transmission; discrete-input P-block fading flat Rayleigh channel; fast link adaptation; frequency domain; imperfect channel state information; initial pilot-assisted channel estimation; iterative MMSE-IC detection; link-to-system approach; long term channel distribution information; minimum-mean-square-error-interference cancellation; semi-analytical performance prediction method; semiblind channel estimation; single-user MIMO-OFDM transmission; slow link adaptation; symbolwise mutual information effective SNR metric; Channel estimation; Context; Interference; MIMO; Rayleigh channels; Signal to noise ratio;
Conference_Titel :
Vehicular Technology Conference (VTC Spring), 2011 IEEE 73rd
Conference_Location :
Yokohama
Print_ISBN :
978-1-4244-8332-7
DOI :
10.1109/VETECS.2011.5956353