Title :
A New ML Detector for SIMO Systems with Imperfect Channel and Carrier Frequency Offset Estimation
Author :
Sinha, S. ; Shahrrava, Behnam ; Deep, Garima
Author_Institution :
Dept. of Electr. & Comput. Eng., Univ. of Windsor, Windsor, ON, Canada
Abstract :
The objective of this paper is to develop a new detection algorithm for single input multiple output (SIMO) systems, using maximum likelihood (ML) scheme. The proposed method takes into account both channel and carrier frequency offset (CFO) estimation errors for detection of the transmitted data. Simulation results show that the new algorithm improve performance in the presence of multiple estimation error variances as compared to the conventional method for different modulation schemes.
Keywords :
MIMO communication; channel estimation; frequency estimation; maximum likelihood detection; CFO estimation error; ML detector; ML scheme; SIMO system; carrier frequency offset estimation; detection algorithm; imperfect channel estimation; maximum likelihood scheme; single input multiple output system; Bit error rate; Channel estimation; Estimation error; Measurement; OFDM; Receiving antennas;
Conference_Titel :
Vehicular Technology Conference (VTC Fall), 2013 IEEE 78th
Conference_Location :
Las Vegas, NV
DOI :
10.1109/VTCFall.2013.6692045
