The DOI matches its Crossref record; 7 of the 7 references it cites were found in a registry or an index.
Emerging technologies and research challenges for 5G wireless networks
Open accessAbstract
As the take-up of Long Term Evolution (LTE)/4G cellular accelerates, there is increasing interest in technologies that will define the next generation (5G) telecommunication standard. This article identifies several emerging technologies which will change and define the future generations of telecommunication standards. Some of these technologies are already making their way into standards such as 3GPP LTE, while others are still in development. Additionally, we will look at some of the research problems that these new technologies pose.
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McKeown (2008) · doi:10.1145/1355734.1355746 · Cited by 8,513
Millimeter Wave Mobile Communications for 5G Cellular: It Will Work!
Rappaport, T. S., Sun, S., Mayzus, R., Zhao, H., Azar, Y., Wang, K., Wong, G. N., Schulz, J. K., Samimi, M., & Gutierrez, F. (2013) · IEEE Access · doi:10.1109/access.2013.2260813 · Cited by 7,351
Massive MIMO for next generation wireless systems
Larsson, E. G., Edfors, O., Tufvesson, F., & Marzetta, T. L. (2014) · IEEE Communications Magazine · doi:10.1109/mcom.2014.6736761 · Cited by 6,779
Noncooperative Cellular Wireless with Unlimited Numbers of Base Station Antennas
Marzetta, T. L. (2010) · IEEE Transactions on Wireless Communications · doi:10.1109/twc.2010.092810.091092 · Cited by 6,302
Trends in small cell enhancements in LTE advanced
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Blueprint for introducing innovation into wireless mobile networks
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A Comprehensive Survey on Internet of Things (IoT) Toward 5G Wireless Systems
Chettri, L., & Bera, R. (2020) · IEEE Internet of Things Journal · doi:10.1109/jiot.2019.2948888 · Cited by 1,737
On Global Electricity Usage of Communication Technology: Trends to 2030
Andrae, A., & Edler, T. (2015) · Challenges · doi:10.3390/challe6010117 · Cited by 1,334
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Akpakwu, G. A., Silva, B. J., Hancke, G. P., & Abu-Mahfouz, A. M. (2018) · IEEE Access · doi:10.1109/access.2017.2779844 · Cited by 1,293
Application of Machine Learning in Wireless Networks: Key Techniques and Open Issues
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Metadata
- Authors
- Chin, W., Fan, Z., & Haines, R.
- Venue
- IEEE Wireless Communications
- Published
- 2014-04
- Volume
- 21
- Issue
- 2
- Pages
- 106-112
- ISSN
- 1536-1284 (ISSN-L)
- OpenAlex
- W2141077315
- Cited by
- 470
- References
- 7
- FWCI
- 29.89
- Type
- journal article
- Language
- en
- Open access
- green
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.