DocumentCode
378923
Title
Reduced-complexity training schemes for multiple-antenna broadband transmissions
Author
Fragouli, C. ; Al-Dhahir, N. ; Turin, W.
Author_Institution
AT& T Shannon Labs., Florham Park, NJ, USA
Volume
1
fYear
2002
fDate
17-21 Mar 2002
Firstpage
78
Abstract
This paper addresses the problem of training sequence design for multiple-antenna transmissions over quasi-static frequency-selective channels. As performance metric for channel estimation, mean square error is adopted. To achieve the minimum mean square error, the training sequences transmitted from the multiple antennas must have impulse-like autocorrelation and zero crosscorrelation. We reduce the problem of designing multiple training sequences to the much easier and well-understood problem of designing a single training sequence with impulse-like auto-correlation. To this end, we propose to encode the training sequences with a space-time code, that may be the same or different from the space-time code that encodes the information symbols. Designing one instead of multiple training sequences reduces the search space significantly and simplifies the construction of optimal or suboptimal training sequences.
Keywords
cellular radio; channel coding; correlation methods; identification; least mean squares methods; modulation coding; optimisation; time-varying channels; transmitting antennas; trellis codes; autocorrelation; channel estimation; crosscorrelation; frequency-selective channels; mean square error; minimum mean square error; multiple-antenna transmissions; optimality; performance metric; quasi-static channels; space-time code; training sequence design; AWGN; Autocorrelation; Binary phase shift keying; Channel estimation; Frequency estimation; Laboratories; Mean square error methods; Measurement; Receiving antennas; Space time codes;
fLanguage
English
Publisher
ieee
Conference_Titel
Wireless Communications and Networking Conference, 2002. WCNC2002. 2002 IEEE
Print_ISBN
0-7803-7376-6
Type
conf
DOI
10.1109/WCNC.2002.993467
Filename
993467
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