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Zero-Forcing Methods for Downlink Spatial Multiplexing in Multiuser MIMO Channels
Abstract
The use of space-division multiple access (SDMA) in the downlink of a multiuser multiple-input, multiple-output (MIMO) wireless communications network can provide a substantial gain in system throughput. The challenge in such multiuser systems is designing transmit vectors while considering the co-channel interference of other users. Typical optimization problems of interest include the capacity problem - maximizing the sum information rate subject to a power constraint-or the power control problem-minimizing transmitted power such that a certain quality-of-service metric for each user is met. Neither of these problems possess closed-form solutions for the general multiuser MIMO channel, but the imposition of certain constraints can lead to closed-form solutions. This paper presents two such constrained solutions. The first, referred to as "block-diagonalization," is a generalization of channel inversion when there are multiple antennas at each receiver. It is easily adapted to optimize for either maximum transmission rate or minimum power and approaches the optimal solution at high SNR. The second, known as "successive optimization," is an alternative method for solving the power minimization problem one user at a time, and it yields superior results in some (e.g., low SNR) situations. Both of these algorithms are limited to cases where the transmitter has more antennas than all receive antennas combined. In order to accommodate more general scenarios, we also propose a framework for coordinated transmitter-receiver processing that generalizes the two algorithms to cases involving more receive than transmit antennas. While the proposed algorithms are suboptimal, they lead to simpler transmitter and receiver structures and allow for a reasonable tradeoff between performance and complexity.
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Citations
Cited by
Gesbert, D., Kountouris, M., Heath, R. W., Chae, C.-B., & Salzer, T. (2007) · IEEE Signal Processing Magazine · doi:10.1109/msp.2007.904815 · Cited by 1,083
Interference alignment via alternating minimization
Peters, S. W., & Heath, R. W. (2009) · 2009 IEEE International Conference on Acoustics, Speech and Signal Processing · doi:10.1109/icassp.2009.4960116 · Cited by 438
Foundations of MIMO Communication
Heath Jr, R. W., & Lozano, A. (2018) · Cambridge University Press eBooks · doi:10.1017/9781139049276 · Cited by 426
Peng, M., Sun, Y., Li, X., Mao, Z., & Wang, C. (2016) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2016.2548658 · Cited by 386
A Deep Learning Framework for Optimization of MISO Downlink Beamforming
Xia, W., Zheng, G., Zhu, Y., Zhang, J., Wang, J., & Petropulu, A. P. (2020) · IEEE Transactions on Communications · doi:10.1109/tcomm.2019.2960361 · Cited by 345
“To evaluate the performance of the proposed BNNs, we carry out numerical simulations to compare the BNNs with several benchmark solutions (when available), including the optimal beamforming, the ZF beamforming [58], the RZF beamforming [59], and the WMMSE algorithm.”
Method
Metadata
- Authors
- Spencer, Q. H., Swindlehurst, A. L., & Haardt, M.
- Venue
- IEEE Transactions on Signal Processing
- Published
- 2004-02
- Volume
- 52
- Issue
- 2
- Pages
- 461-471
- ISSN
- 1053-587X (ISSN-L)
- OpenAlex
- W2098126478
- Cited by
- 3,148
- References
- 0
- FWCI
- 77.82
- Type
- journal article
- Language
- en
- Open access
- closed
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- Spencer, Q. H., Swindlehurst, A. L., & Haardt, M. (2004). Zero-Forcing Methods for Downlink Spatial Multiplexing in Multiuser MIMO Channels. IEEE Transactions on Signal Processing. https://doi.org/10.1109/tsp.2003.821107
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