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Adaptive CNN-based private LTE solution for fair coexistence with Wi-Fi in unlicensed spectrum

Merkebu Tekaw Girmay (UGent) , Vasilis Maglogiannis (UGent) , Dries Naudts (UGent) , Jaron Fontaine (UGent) , Adnan Shahid (UGent) , Eli De Poorter (UGent) and Ingrid Moerman (UGent)
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Abstract
Recently, the expansion of wireless network deployments is resulting in increased scarcity of available licensed radio spectrum. As the domain of wireless communications is progressing rapidly, many industries are looking into wireless network solutions that can increase their productivity. Private LTE is a promising wireless network solution as it can be customised independently without the control of a mobile network operator while providing reliable and spectrum efficient services. For this reason, the deployment of Private LTE in the unlicensed spectrum and its coexistence with Wi-Fi is becoming a popular topic in research. In this paper, we propose a coexistence scheme for private LTE network in unlicensed spectrum that enables a fair spectrum sharing with co-located Wi-Fi networks. This is achieved by exploiting various LTE frame configurations consisting of different combinations of downlink, uplink, special subframe and muted subframes. The configuration of a single frame is decided based on a rule based algorithm that exploits Wi-Fi spectrum occupancy statistics that is obtained from a technology recognition system which is based on a Convolutional Neural Network. The performance of the proposed private LTE scheme and its coexistence with Wi-Fi is investigated for different traffic scenarios showcasing how the proposed scheme can lead to a harmless coexistence of LTE and Wi-Fi.
Keywords
Private adaptive LTE, Wi-Fi, CNN, Technology Recognition, AI/ML, Fair Coexistence

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MLA
Girmay, Merkebu Tekaw, et al. “Adaptive CNN-Based Private LTE Solution for Fair Coexistence with Wi-Fi in Unlicensed Spectrum.” IEEE INFOCOM 2020 - IEEE CONFERENCE ON COMPUTER COMMUNICATIONS WORKSHOPS (INFOCOM WKSHPS), IEEE, 2020, pp. 346–51, doi:10.1109/infocomwkshps50562.2020.9162663.
APA
Girmay, M. T., Maglogiannis, V., Naudts, D., Fontaine, J., Shahid, A., De Poorter, E., & Moerman, I. (2020). Adaptive CNN-based private LTE solution for fair coexistence with Wi-Fi in unlicensed spectrum. In IEEE INFOCOM 2020 - IEEE CONFERENCE ON COMPUTER COMMUNICATIONS WORKSHOPS (INFOCOM WKSHPS) (pp. 346–351). Toronto, Canada: IEEE. https://doi.org/10.1109/infocomwkshps50562.2020.9162663
Chicago author-date
Girmay, Merkebu Tekaw, Vasilis Maglogiannis, Dries Naudts, Jaron Fontaine, Adnan Shahid, Eli De Poorter, and Ingrid Moerman. 2020. “Adaptive CNN-Based Private LTE Solution for Fair Coexistence with Wi-Fi in Unlicensed Spectrum.” In IEEE INFOCOM 2020 - IEEE CONFERENCE ON COMPUTER COMMUNICATIONS WORKSHOPS (INFOCOM WKSHPS), 346–51. IEEE. https://doi.org/10.1109/infocomwkshps50562.2020.9162663.
Chicago author-date (all authors)
Girmay, Merkebu Tekaw, Vasilis Maglogiannis, Dries Naudts, Jaron Fontaine, Adnan Shahid, Eli De Poorter, and Ingrid Moerman. 2020. “Adaptive CNN-Based Private LTE Solution for Fair Coexistence with Wi-Fi in Unlicensed Spectrum.” In IEEE INFOCOM 2020 - IEEE CONFERENCE ON COMPUTER COMMUNICATIONS WORKSHOPS (INFOCOM WKSHPS), 346–351. IEEE. doi:10.1109/infocomwkshps50562.2020.9162663.
Vancouver
1.
Girmay MT, Maglogiannis V, Naudts D, Fontaine J, Shahid A, De Poorter E, et al. Adaptive CNN-based private LTE solution for fair coexistence with Wi-Fi in unlicensed spectrum. In: IEEE INFOCOM 2020 - IEEE CONFERENCE ON COMPUTER COMMUNICATIONS WORKSHOPS (INFOCOM WKSHPS). IEEE; 2020. p. 346–51.
IEEE
[1]
M. T. Girmay et al., “Adaptive CNN-based private LTE solution for fair coexistence with Wi-Fi in unlicensed spectrum,” in IEEE INFOCOM 2020 - IEEE CONFERENCE ON COMPUTER COMMUNICATIONS WORKSHOPS (INFOCOM WKSHPS), Toronto, Canada, 2020, pp. 346–351.
@inproceedings{8673059,
  abstract     = {{Recently, the expansion of wireless network deployments is resulting in increased scarcity of available licensed radio spectrum. As the domain of wireless communications is progressing rapidly, many industries are looking into wireless network solutions that can increase their productivity. Private LTE is a promising wireless network solution as it can be customised independently without the control of a mobile network operator while providing reliable and spectrum efficient services. For this reason, the deployment of Private LTE in the unlicensed spectrum and its coexistence with Wi-Fi is becoming a popular topic in research. In this paper, we propose a coexistence scheme for private LTE network in unlicensed spectrum that enables a fair spectrum sharing with co-located Wi-Fi networks. This is achieved by exploiting various LTE frame configurations consisting of different combinations of downlink, uplink, special subframe and muted subframes. The configuration of a single frame is decided based on a rule based algorithm that exploits Wi-Fi spectrum occupancy statistics that is obtained from a technology recognition system which is based on a Convolutional Neural Network. The performance of the proposed private LTE scheme and its coexistence with Wi-Fi is investigated for different traffic scenarios showcasing how the proposed scheme can lead to a harmless coexistence of LTE and Wi-Fi.}},
  author       = {{Girmay, Merkebu Tekaw and Maglogiannis, Vasilis and Naudts, Dries and Fontaine, Jaron and Shahid, Adnan and De Poorter, Eli and Moerman, Ingrid}},
  booktitle    = {{IEEE INFOCOM 2020 - IEEE CONFERENCE ON COMPUTER COMMUNICATIONS WORKSHOPS (INFOCOM WKSHPS)}},
  isbn         = {{9781728186955}},
  issn         = {{2159-4228}},
  keywords     = {{Private adaptive LTE,Wi-Fi,CNN,Technology Recognition,AI/ML,Fair Coexistence}},
  language     = {{eng}},
  location     = {{Toronto, Canada}},
  pages        = {{346--351}},
  publisher    = {{IEEE}},
  title        = {{Adaptive CNN-based private LTE solution for fair coexistence with Wi-Fi in unlicensed spectrum}},
  url          = {{http://dx.doi.org/10.1109/infocomwkshps50562.2020.9162663}},
  year         = {{2020}},
}

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