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Space-time processing for wireless communications
Abstract
Space-time processing can improve network capacity, coverage, and quality by reducing co-channel interference (CCI) while enhancing diversity and array gain. This article focuses largely on the receive (mobile-to-base station) time-division multiple access (TDMA) (nonspread modulation) application for high-mobility networks. We describe a large (macro) cell propagation channel and discuss different physical effects such as path loss, fading delay spread, angle spread, and Doppler spread. We also develop a signal model incorporating channel effects. Both forward-link (transmit) and reverse-link (receive) channels are considered and the relationship between the two is discussed. Single- and multiuser models are treated for four important space-time processing problems, and the underlying spatial and temporal structure are discussed as are different algorithmic approaches to reverse link space-time professing with blind and nonblind methods for single- and multiple-user cases. We cover forward-link space-time algorithms and we outline methods for estimation of multipath parameters. We also discuss applications of space-time processing to CDMA, applications of space-time techniques to current cellular systems, and industry trends.
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Cited by
From theory to practice: an overview of MIMO space-time coded wireless systems
Gesbert, D., Shafi, M., Shiu, D.-S., Smith, P. J., & Naguib, A. (2003) · IEEE Journal on Selected Areas in Communications · doi:10.1109/jsac.2003.809458 · Cited by 2,295
Deconstructing multiantenna fading channels
Sayeed, A. M. (2002) · IEEE Transactions on Signal Processing · doi:10.1109/tsp.2002.803324 · Cited by 1,120
Detection, classification, and tracking of targets
Li, D., Wong, K. D., Hu, Y. H., & Sayeed, A. M. (2002) · IEEE Signal Processing Magazine · doi:10.1109/79.985674 · Cited by 932
Foundations of MIMO Communication
Heath Jr, R. W., & Lozano, A. (2018) · Cambridge University Press eBooks · doi:10.1017/9781139049276 · Cited by 426
Dictionary Learning-Based Sparse Channel Representation and Estimation for FDD Massive MIMO Systems
Ding, Y., & Rao, B. D. (2018) · IEEE Transactions on Wireless Communications · doi:10.1109/twc.2018.2843786 · Cited by 161
Metadata
- Authors
- Paulraj, A. J., & Papadias, C. B.
- Venue
- IEEE Signal Processing Magazine
- Published
- 1997
- Volume
- 14
- Issue
- 6
- Pages
- 49-83
- ISSN
- 1053-5888 (ISSN-L)
- OpenAlex
- W2143447102
- Cited by
- 1,030
- References
- 0
- FWCI
- 39.71
- Type
- journal article
- Language
- en
- Open access
- closed
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- Paulraj, A. J., & Papadias, C. B. (1997). Space-time processing for wireless communications. IEEE Signal Processing Magazine. https://doi.org/10.1109/79.637317
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