2019 IEEE Global Communications Conference (GLOBECOM) 2019
DOI: 10.1109/globecom38437.2019.9013586
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Non-Orthogonal Multiple Access for Mobile VLC Networks with Random Receiver Orientation

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Cited by 12 publications
(18 citation statements)
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“…Tsiropoulou et al [88] have investigated problematics of non-orthogonal multiple acces (NOMA) vs. orthogonal frequency division multiple access (OFDMA) approach [89][90][91]. According to her, NOMA offers us multiple advantages, such as considerable interference mitigation or simultaneous bandwidth utilization.…”
Section: Light-to-medical Devicesmentioning
confidence: 99%
“…Tsiropoulou et al [88] have investigated problematics of non-orthogonal multiple acces (NOMA) vs. orthogonal frequency division multiple access (OFDMA) approach [89][90][91]. According to her, NOMA offers us multiple advantages, such as considerable interference mitigation or simultaneous bandwidth utilization.…”
Section: Light-to-medical Devicesmentioning
confidence: 99%
“…In research by Oviedo and Cao et al [16,17], when the transmit signal to interference plus noise ratio is not low, the expected NOMA capacity increase following GRPA is greater than the OMA capacity with the same resource allocation conditions, which can be regarded as the guaranteed-QoS data rate. In research by Yapici et al [18], comprehensive numerical results verified the superiority of NOMA-VLC in achieving a satisfactory QoS target rate by random receiver orientation. Vertical angle information can compensate for loss in user rates by incorporating suitable power allocation coefficients, which are inversely proportional to the channel quality of the respective NOMA user.…”
Section: Introductionmentioning
confidence: 89%
“…By considering the proportional fairness [96], authors of [152] showed that the formulated problem was of non-convex type, but could be converted to a convex problem that could be solved using a dual decomposition method. Authors of [153] evaluated and compared the NOMA and OMA schemes, when the users change their locations and their vertical orientation. Instead of reporting the full CSI that increases the computational complexity, they used limited-feedback schemes to categorize users based on their mean vertical angle and mean distance, and this might be most appropriate to simplify the implementation.…”
Section: Noma In Vlcmentioning
confidence: 99%