Evaluation of reconfigurable intelligent surface-assisted underwater wireless optical communication system

RP Naik, WY Chung - Journal of Lightwave Technology, 2022 - opg.optica.org
RP Naik, WY Chung
Journal of Lightwave Technology, 2022opg.optica.org
Reconfigurable intelligent surfaces (RISs) are an emerging technology aimed to enhance
the energy and spectrum efficiency of wireless communication links by reconfiguring the
propagation environment of radio-frequency (RF)/optical waves. Planar phased meta-
material surfaces or reflect-arrays for RF RIS and multiple smart mirrors have been used for
activating optical RIS. In this article, we analyze the underwater optical wireless
communication (UWOC) system performance in terms of bit error rate (BER), outage …
Reconfigurable intelligent surfaces (RISs) are an emerging technology aimed to enhance the energy and spectrum efficiency of wireless communication links by reconfiguring the propagation environment of radio-frequency (RF)/optical waves. Planar phased meta-material surfaces or reflect-arrays for RF RIS and multiple smart mirrors have been used for activating optical RIS. In this article, we analyze the underwater optical wireless communication (UWOC) system performance in terms of bit error rate (BER), outage probability (OP) and channel capacity (CC) under the influence of underwater turbulence, beam attenuation, pointing errors and occlusion or blockage due to obstacles. A RIS-assisted UWOC proposed to mitigate the effects obstacles, pointing errors and turbulence and improve the system performances. The probability density function and cumulative distribution functions of RIS elements based UWOC system are evaluated over the underwater turbulence, pointing errors and blockage due to obstacles. The novel closed-form expressions for BER under binary phase shift keying and binary frequency shift keying modulation schemes using with and without coherent detection, OP, and CC for intensity modulation-direct detection and heterodyne detection cases are obtained and plotted according to the number of RIS elements with respect to the average signal-to-noise ratio. The numerical BER results are validated with the Monte-Carlo simulations.
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