Soluções para coexistência de sistemas LTE e wi-fi em ambientes multicelulares
The growth of mobile internet access from fourth generation (4G) devices, combined with increasing usage of smartphones, the upcoming fifth generation (5G) and massive usage of multimedia services, make the demand for mobile traffic reach high levels and the need for bandwidth grows. However, the...
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| Formato: | Dissertação |
| Idioma: | pt_BR |
| Publicado em: |
Universidade Federal do Rio Grande do Norte
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| Endereço do item: | https://repositorio.ufrn.br/jspui/handle/123456789/29947 |
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| Resumo: | The growth of mobile internet access from fourth generation (4G) devices, combined
with increasing usage of smartphones, the upcoming fifth generation (5G) and massive
usage of multimedia services, make the demand for mobile traffic reach high levels and
the need for bandwidth grows. However, the electromagnetic spectrum utilized by these
applications is limited, creating scarcity in the face of demand, besides the high costs and
bureaucracy for granting new bands. To overcome this problem, one of the solutions is to
leverage the unlicensed spectrum, for it is free of charges, presents some of its portions
with bandwidth higher than the licensed spectrum, and portions with underused profile,
indicating less probability of interference between technologies. In this context rises the
LTE-U and LTE-LAA technologies with modifications in the medium access mechanism
of LTE for leveraging the unlicensed spectrum in the Industrial, Scientific and Medical
(ISM) 5 GHz band. These technologies must coexist with the most successful and
consolidated technology already using this portion of the spectrum, the Wi-Fi. However,
each technology implements its access mechanism, then studies must be done to point
out impacts that each of these technologies has when coexist. Besides the coexistence
study, the application of machine learning techniques to automatically adjust the medium
access parameters, controlling the generated impact of one technology into another must
be realized. Studies in such a scenario and with single-cell environments have already
been explored in literature, remaining the challenge of new solutions targeting multi-cell
environments. For all it has been exposed, this work has the following goals: (1)
The coexistence study of LTE-U and Wi-Fi technologies in a multi-cell scenario, with
co-channel and inter-RAT (same technology) interference; (2) The application of machine
learning algorithms (reinforcement learning) to adjust the parameters targeting optimizing
the medium access for one, or both technologies, and consequently reach improvements
in the coexistence measured in the form of data rates and decreasing packet losses. |
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