The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
Power Control in Wireless Cellular Networks
Abstract
Transmit power in wireless cellular networks is a key degree of freedom in the management of interference, energy, and connectivity. Power control in both the uplink and downlink of a cellular network has been extensively studied, especially over the last 15 years, and some of the results have enabled the continuous evolution and significant impact of the digital cellular technology. This survey provides a comprehensive discussion of the models, algorithms, analysis, and methodologies in this vast and growing literature. It starts with a taxonomy of the wide range of power control problem formulations, and progresses from the basic formulation to more sophisticated ones. When transmit power is the only set of optimization variables, algorithms for fixed SIR are presented first, before turning to their robust versions and joint SIR and power optimization. This is followed by opportunistic and non-cooperative power control. Then joint control of power together with beamforming pattern, base station assignment, spectrum allocation, and transmit schedule is surveyed one-by-one. Throughout the survey, we highlight the use of mathematical language and tools in the study of power control, including optimization theory, control theory, game theory, and linear algebra. Practical implementations of some of the algorithms in operational networks are discussed in the concluding section. As illustrated by the open problems presented at the end of most chapters, in the area of power control in cellular networks, there are still many under-explored directions and unresolved issues that remain theoretically challenging and practically important.
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Cites
Boyd, S., & Vandenberghe, L. (2004) · doi:10.1017/cbo9780511804441 · Cited by 56,601
Fundamentals of Wireless Communication
Tse, D., & Viswanath, P. (2005) · doi:10.1017/cbo9780511807213 · Cited by 13,162
Power Control of Cellular Radio Systems Via Robust Smith Prediction Filter
Lee, B.-K., Chen, H.-W., & Chen, B.-S. (2004) · IEEE Transactions on Wireless Communications · doi:10.1109/twc.2004.834705 · Cited by 51
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Multi-Agent Deep Reinforcement Learning for Dynamic Power Allocation in Wireless Networks
Nasir, Y. S., & Guo, D. (2019) · IEEE Journal on Selected Areas in Communications · doi:10.1109/jsac.2019.2933973 · Cited by 660
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Enabling AI in Future Wireless Networks: A Data Life Cycle Perspective
Nguyen, D. C., Cheng, P., Ding, M., Lopez-Perez, D., Pathirana, P. N., Li, J., Seneviratne, A., Li, Y., & Poor, H. V. (2021) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2020.3024783 · Cited by 160
Distributed Non-Autonomous Power Control through Distributed Convex Optimization
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Metadata
- Authors
- Chiang, M., Hande, P., Lan, T., & Tan, C. W.
- Venue
- Foundations and Trends in Networking
- Publisher
- Emerald
- Published
- 2008-06-19
- Volume
- 2
- Issue
- 4
- Pages
- 381-533
- ISSN
- 1554-057X (ISSN-L)
- 1554-0588
- OpenAlex
- W4211091685
- Cited by
- 304
- References
- 3
- FWCI
- 12.85
- Type
- journal article
- Language
- en
- Open access
- closed
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