{"title":"Multi-Armed-Bandit-Based Spectrum Scheduling Algorithms in Wireless Networks: A Survey","_id":"16280","department":[{"_id":"75"}],"publication_identifier":{"issn":["1536-1284","1558-0687"]},"date_created":"2020-03-10T16:02:30Z","user_id":"126","citation":{"bibtex":"@article{Li_Yu_Yang_Yu_Karl_Cheng_2020, title={Multi-Armed-Bandit-Based Spectrum Scheduling Algorithms in Wireless Networks: A Survey}, DOI={<a href=\"https://doi.org/10.1109/mwc.001.1900280\">10.1109/mwc.001.1900280</a>}, journal={IEEE Wireless Communications}, author={Li, Feng and Yu, Dongxiao and Yang, Huan and Yu, Jiguo and Karl, Holger and Cheng, Xiuzhen}, year={2020}, pages={24–30} }","short":"F. Li, D. Yu, H. Yang, J. Yu, H. Karl, X. Cheng, IEEE Wireless Communications (2020) 24–30.","chicago":"Li, Feng, Dongxiao Yu, Huan Yang, Jiguo Yu, Holger Karl, and Xiuzhen Cheng. “Multi-Armed-Bandit-Based Spectrum Scheduling Algorithms in Wireless Networks: A Survey.” <i>IEEE Wireless Communications</i>, 2020, 24–30. <a href=\"https://doi.org/10.1109/mwc.001.1900280\">https://doi.org/10.1109/mwc.001.1900280</a>.","mla":"Li, Feng, et al. “Multi-Armed-Bandit-Based Spectrum Scheduling Algorithms in Wireless Networks: A Survey.” <i>IEEE Wireless Communications</i>, 2020, pp. 24–30, doi:<a href=\"https://doi.org/10.1109/mwc.001.1900280\">10.1109/mwc.001.1900280</a>.","ama":"Li F, Yu D, Yang H, Yu J, Karl H, Cheng X. Multi-Armed-Bandit-Based Spectrum Scheduling Algorithms in Wireless Networks: A Survey. <i>IEEE Wireless Communications</i>. 2020:24-30. doi:<a href=\"https://doi.org/10.1109/mwc.001.1900280\">10.1109/mwc.001.1900280</a>","ieee":"F. Li, D. Yu, H. Yang, J. Yu, H. Karl, and X. Cheng, “Multi-Armed-Bandit-Based Spectrum Scheduling Algorithms in Wireless Networks: A Survey,” <i>IEEE Wireless Communications</i>, pp. 24–30, 2020.","apa":"Li, F., Yu, D., Yang, H., Yu, J., Karl, H., &#38; Cheng, X. (2020). Multi-Armed-Bandit-Based Spectrum Scheduling Algorithms in Wireless Networks: A Survey. <i>IEEE Wireless Communications</i>, 24–30. <a href=\"https://doi.org/10.1109/mwc.001.1900280\">https://doi.org/10.1109/mwc.001.1900280</a>"},"year":"2020","status":"public","author":[{"first_name":"Feng","last_name":"Li","full_name":"Li, Feng"},{"full_name":"Yu, Dongxiao","last_name":"Yu","first_name":"Dongxiao"},{"full_name":"Yang, Huan","last_name":"Yang","first_name":"Huan"},{"first_name":"Jiguo","last_name":"Yu","full_name":"Yu, Jiguo"},{"first_name":"Holger","full_name":"Karl, Holger","id":"126","last_name":"Karl"},{"full_name":"Cheng, Xiuzhen","last_name":"Cheng","first_name":"Xiuzhen"}],"abstract":[{"text":"Assigning bands of the wireless spectrum as resources to users is a common problem in wireless networks. Typically, frequency bands were assumed to be available in a stable manner. Nevertheless, in recent scenarios where wireless networks may be deployed in unknown environments, spectrum competition is considered, making it uncertain whether a frequency band is available at all or at what quality. To fully exploit such resources with uncertain availability, the multi-armed bandit (MAB) method, a representative online learning technique, has been applied to design spectrum scheduling algorithms. This article surveys such proposals. We describe the following three aspects: how to model spectrum scheduling problems within the MAB framework, what the main thread is following which prevalent algorithms are designed, and how to evaluate algorithm performance and complexity. We also give some promising directions for future research in related fields.","lang":"eng"}],"doi":"10.1109/mwc.001.1900280","type":"journal_article","date_updated":"2022-01-06T06:52:48Z","publication":"IEEE Wireless Communications","page":"24-30","language":[{"iso":"eng"}],"publication_status":"published"}