The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Unsupervised Learning for Passive Beamforming
Open accessAbstract
Reconfigurable intelligent surface (RIS) has recently emerged as a promising candidate to improve the energy and spectral efficiency of wireless communication systems. However, the unit modulus constraint on the phase shift of reflecting elements makes the design of optimal passive beamforming solution a challenging issue. The conventional approach is to find a suboptimal solution using the semi-definite relaxation (SDR) technique, yet the resultant suboptimal iterative algorithm usually incurs high complexity, hence is not amenable for real-time implementation. Motivated by this, we propose a deep learning approach for passive beamforming design in RIS-assisted systems. In particular, a customized deep neural network is trained offline using the unsupervised learning mechanism, which is able to make real-time prediction when deployed online. Simulation results show that the proposed approach maintains most of the performance while significantly reduces computation complexity when compared with SDR-based approach.
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Fundamentals of Wireless Communication
Tse, D., & Viswanath, P. (2005) · doi:10.1017/cbo9780511807213 · Cited by 13,162
Cited by
Toward Smart Wireless Communications via Intelligent Reflecting Surfaces: A Contemporary Survey
Gong, S., Lu, X., Hoang, D. T., Niyato, D., Shu, L., Kim, D. I., & Liang, Y.-C. (2020) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2020.3004197 · Cited by 1,035
Jiang, T., Cheng, H. V., & Yu, W. (2021) · IEEE Journal on Selected Areas in Communications · doi:10.1109/jsac.2021.3078502 · Cited by 290
Di Renzo, M., Zappone, A., Debbah, M., Alouini, M.-S., Yuen, C., de Rosny, J., & Tretyakov, S. (2020) · IEEE Journal on Selected Areas in Communications · doi:10.1109/jsac.2020.3007211 · Cited by 112
Metadata
- Authors
- Gao, J., Zhong, C., Chen, X., Lin, H., & Zhang, Z.
- Venue
- IEEE Communications Letters
- Published
- 2020-05
- Volume
- 24
- Issue
- 5
- Pages
- 1052-1056
- ISSN
- 1089-7798 (ISSN-L)
- 1558-2558
- 2373-7891
- OpenAlex
- W3000522337
- Cited by
- 211
- References
- 1
- FWCI
- 11.73
- Type
- journal article
- Language
- en
- Open access
- green
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- Gao, J., Zhong, C., Chen, X., Lin, H., & Zhang, Z. (2020). Unsupervised Learning for Passive Beamforming. IEEE Communications Letters. https://doi.org/10.1109/lcomm.2020.2965532
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