PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.
Effects of oceanic channels degrade the performance of underwater optical communication (UOC) systems based on orbital angular momentum (OAM) multiplexing. Considering both oceanic turbulence and water attenuation, a more comprehensive channel model is proposed. We derive the expressions of bit error rate (BER) and aggregate capacity of UOC-OAM systems. We also investigate the system performance with wavelengths of 400-700 nm . The numerical simulation results show that the blue-green wavelength is not always the best choice to provide large channel capacities for UOC-OAM systems. For large chlorophyll-a concentration channel, due to the strong attenuation the optimal wavelength is shifted toward red wavelength region. Meanwhile, with increasing of oceanic turbulence strength, the frequency bandwidth decreases and systems with larger wavelength show better performance. These results will be beneficial to the design and application of UOC-OAM systems.
Xiaoli Yin,Zhaoyuan Zhang,Xiaozhou Cui,Huan Chang, andLihang Wang
"Performance analysis of orbital angular momentum multiplexing systems with different wavelengths under oceanic channels", Proc. SPIE 11427, Second Target Recognition and Artificial Intelligence Summit Forum, 114272H (31 January 2020); https://doi.org/10.1117/12.2552351
ACCESS THE FULL ARTICLE
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.
The alert did not successfully save. Please try again later.
Xiaoli Yin, Zhaoyuan Zhang, Xiaozhou Cui, Huan Chang, Lihang Wang, "Performance analysis of orbital angular momentum multiplexing systems with different wavelengths under oceanic channels," Proc. SPIE 11427, Second Target Recognition and Artificial Intelligence Summit Forum, 114272H (31 January 2020); https://doi.org/10.1117/12.2552351