2019
DOI: 10.1109/twc.2019.2920132
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Terminal Orientation in OFDM-Based LiFi Systems

Abstract: Light-fidelity (LiFi) is a wireless communication technology that employs both infrared and visible light spectra to support multiuser access and user mobility. Considering the small wavelength of light, the optical channel is affected by the random orientation of a user equipment (UE). In this paper, a random process model for changes in the UE orientation is proposed based on data measurements. We show that the coherence time of the random orientation is in the order of hundreds of milliseconds.Therefore, an… Show more

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Cited by 48 publications
(43 citation statements)
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References 40 publications
(111 reference statements)
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“…In other words, random angles are generated using the statistics in Table I (Gaussian for walking and Laplace for sitting), and then, the channel gain can be obtained using (4) and (5). The same method as described in [35] is used to obtain the coherence time of α, β and γ. The values are presented in Table I.…”
Section: A Random Orientation Modelingmentioning
confidence: 99%
“…In other words, random angles are generated using the statistics in Table I (Gaussian for walking and Laplace for sitting), and then, the channel gain can be obtained using (4) and (5). The same method as described in [35] is used to obtain the coherence time of α, β and γ. The values are presented in Table I.…”
Section: A Random Orientation Modelingmentioning
confidence: 99%
“…The analysis of indoor mobile channels is challenging for several reasons. First, it involves numerous factors such as mobile device orientation [ 7 , 8 , 9 , 10 , 11 , 12 ], distance dependency [ 13 ], shadowing [ 14 , 15 , 16 ], and others. Another aspect is related to reliable simulation of human movement; while realistic human motion simulations are possible, their combination with rigorous channel characterization is still challenging [ 17 , 18 ].…”
Section: Introductionmentioning
confidence: 99%
“…This is attributed to the simplicity of the adopted model and also to the lack of proper channel models for the mobility and orientation of VLC devices in indoor scenarios. Nevertheless, several measurement-based channel models for VLC system were derived recently for various environments, such as indoor VLC systems [131]- [137], VLC-based vehicular communication [138] and underwater VLC systems [139], [140].…”
Section: Incorporating Realistic and Measurements Based Vlc Channementioning
confidence: 99%