Paper
24 June 1999 Subbanding approach to blind space-time equalization for wideband TDMA based on the SIMO cross-relation
Michael D. Zoltowski, Der-Feng Tseng
Author Affiliations +
Abstract
Transmission of multimedia data is the goal of third generation (3G) cellular radio systems necessitating high- speed data links where the multipath delay spread generally encompasses many symbol intervals. A blind multichannel identification scheme is presented along with an attendant space-time equalization algorithm, based on subbanding and the Cross-Relation method (CRM) of Xu, Liu, Tong, and Kailath. The basic approach is to apply the CRM in each subband, using basis functions derived from the symbol waveform and the bandpass filter, to blindly identify the frequency response of each channel in the given subband. A method is presented for proper phasing of each blind subband channel estimate to reconstruct the full channel impulse response associated with each antenna. In the practical case where a small number of training symbols are available, a semi-blind approach is presented that follows the blind procedure by a fractionally-spaced decision feedback equalizer (DFE). The advantage of this semi-blind approach is that the number of taps needed for the DFE need only span the duration of the original symbol waveform, which in the wideband case is much less than the number of taps needed to span the delay spread as required in a conventional DFE. Simulations are presented using parameters drawn from proposed 3G Wideband TDMA standards.
© (1999) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Michael D. Zoltowski and Der-Feng Tseng "Subbanding approach to blind space-time equalization for wideband TDMA based on the SIMO cross-relation", Proc. SPIE 3708, Digital Wireless Communication, (24 June 1999); https://doi.org/10.1117/12.351234
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Cited by 1 scholarly publication.
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KEYWORDS
Antennas

Electronic filtering

Analog electronics

Bandpass filters

Convolution

Linear filtering

Niobium

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