DocumentCode :
3522034
Title :
On perfect channel identifiability of semiblind ML detection of orthogonal space-time block coded OFDM
Author :
Chang, Tsung-Hui ; Ma, Wing-Kin ; Huang, Chuan-Yuan ; Chi, Chong-Yung
Author_Institution :
Dept. of Elec. Eng., Nat. Tsing Hua Univ., Hsinchu
fYear :
2009
fDate :
19-24 April 2009
Firstpage :
2713
Lastpage :
2716
Abstract :
This paper considers maximum-likelihood (ML) detection of orthogonal space-time block coded OFDM (OSTBC-OFDM) systems without channel state information. Our previous work has shown an interesting identifiability result, that the whole time-domain channel can be uniquely identified by only having one subchannel to transmit pilots. However, this identifiability is in a probability-one sense, under some mild assumptions on the channel statistics. In this paper we establish a ldquoperfectrdquo channel identifiability (PCI) condition under which the channel is always uniquely identifiable. It is shown that PCI can be achieved by judiciously applying the so-called non-intersecting subspace OSTBCs. The resultant PCI achieving scheme has its number of pilots larger than that used in the previous probability-one identifiability achieving scheme, but smaller than that required in conventional pilot-aided channel estimation. Simulation results are presented to show that the proposed scheme can provide a better performance than the other schemes.
Keywords :
OFDM modulation; block codes; channel estimation; maximum likelihood detection; modulation coding; orthogonal codes; space-time codes; channel identifiability; channel state information; orthogonal space-time block coded OFDM; pilot-aided channel estimation; semiblind maximum-likelihood detection; AWGN; Channel estimation; Channel state information; Discrete Fourier transforms; MIMO; Maximum likelihood detection; Maximum likelihood estimation; OFDM; Space time codes; Time domain analysis; Channel identifiability; Maximum-likelihood detection; OSTBC-OFDM;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Acoustics, Speech and Signal Processing, 2009. ICASSP 2009. IEEE International Conference on
Conference_Location :
Taipei
ISSN :
1520-6149
Print_ISBN :
978-1-4244-2353-8
Electronic_ISBN :
1520-6149
Type :
conf
DOI :
10.1109/ICASSP.2009.4960183
Filename :
4960183
Link To Document :
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