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Deconstructing multiantenna fading channels
Open accessAbstract
Accurate and tractable channel modeling is critical to realizing the full potential of antenna arrays in wireless communications. Current approaches represent two extremes: idealized statistical models representing a rich scattering environment and parameterized physical models that describe realistic scattering environments via the angles and gains associated with different propagation paths. However, simple rules that capture the effects of scattering characteristics on channel capacity and diversity are difficult to infer from existing models. We propose an intermediate virtual channel representation that captures the essence of physical modeling and provides a simple geometric interpretation of the scattering environment. The virtual representation corresponds to a fixed coordinate transformation via spatial basis functions defined by fixed virtual angles. We show that in an uncorrelated scattering environment, the elements of the channel matrix form a segment of a stationary process and that the virtual channel coefficients are approximately uncorrelated samples of the underlying spectral representation. For any scattering environment, the virtual channel matrix clearly reveals the two key factors affecting capacity: the number of parallel channels and the level of diversity. The concepts of spatial zooming and aliasing are introduced to provide a transparent interpretation of the effect of antenna spacing on channel statistics and capacity. Numerical results are presented to illustrate various aspects of the virtual framework.
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Cited by
Prospective Multiple Antenna Technologies for Beyond 5G
Zhang, J., Bjornson, E., Matthaiou, M., Ng, D. W. K., Yang, H., & Love, D. J. (2020) · IEEE Journal on Selected Areas in Communications · doi:10.1109/jsac.2020.3000826 · Cited by 877
Foundations of MIMO Communication
Heath Jr, R. W., & Lozano, A. (2018) · Cambridge University Press eBooks · doi:10.1017/9781139049276 · Cited by 426
Channel Estimation in Broadband Millimeter Wave MIMO Systems With Few-Bit ADCs
Mo, J., Schniter, P., & Heath, R. W. (2018) · IEEE Transactions on Signal Processing · doi:10.1109/tsp.2017.2781644 · Cited by 348
Beamforming Technologies for Ultra-Massive MIMO in Terahertz Communications
Ning, B., Tian, Z., Mei, W., Chen, Z., Han, C., Li, S., Yuan, J., & Zhang, R. (2023) · IEEE Open Journal of the Communications Society · doi:10.1109/ojcoms.2023.3245669 · Cited by 270
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
- Sayeed, A. M.
- Venue
- IEEE Transactions on Signal Processing
- Published
- 2002-10
- Volume
- 50
- Issue
- 10
- Pages
- 2563-2579
- ISSN
- 1053-587X (ISSN-L)
- OpenAlex
- W2128865660
- Cited by
- 1,120
- References
- 0
- FWCI
- 25.24
- Type
- journal article
- Language
- en
- Open access
- green
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