A Contemporary Survey on Free Space Optical Communication: Potential, Technical Challenges, Recent Advances and Research Direction
In order to meet demand from IoT devices, 5G and beyond new Optical wireless communication (OWC) systems covering an ultra-wide range of unlicensed spectrum (in particular near infrared) has garnered substantial interest for a variety of applications. Concerns regarding link reliability due to environmental factors, atmospheric turbulence, pointing errors and scintillation. These issues can be mitigated both through research and development as well as combination FSO/RF hybrid and radio over FSO (RoFSO) systems to compensate for the limitations of a specific system. To this end a variety of research has been undertaken over the past decade, with this article serving as a detailed overview of the wavelengths and technologies used in various forms of OWC.
The types of OWC technologies can be divided into three categories, Infrared, visible light and ultraviolet. Light Fidelity (LiFi) and FSO use all three types for various uses, while VLC and Optical Camera Communication (OCC) operate using visible light.
Mitigation techniques for challenges for FSO technology are discussed, such as Aperture Sizing, Adaptive Optics, Relay Transmission, Modulation, FSO channel modeling, background noise reduction, time, frequency and space/site diversity, coherency detection, sub-carrier multiplexing (SCM) and hybrid FSO such as WiFo (WiFi-FSO).
Radio over FSO allows for simultaneous data transmission of broadband RF signals in a bidirectional path over a FSO link. a electro-optic modulator is used to convert the RF signal into optical, and then demodulated and converted back into radio signals on the receiving end.
Multi-user FSO refers to when multiple users can simultaneously send and receive data while using FSO technology. This can be accomplished using techniques such as time division multiple access (TDMA) where users are given specific time slots of frequency division multiple access (FDMA) where each user is assigned a specific frequency range. Managing multiple users introduces considerations such as quality of service, signal interference and management overhead. When multiple users are transmitting different signals, Blind source separation (BSS) is a technique that can be used to extract the original information from mixed signals. Users may be distributed randomly over space, causing the strength of different channels to fade independently.
MIMO FSO systems utilizing spatial diversity offer inherent advantages such increased signal redundancy and as a result transmission reliability. MIMO systems are also more resistant to turbulence induced fading compared to SISO links. precoding techniques such as dirty paper coding (DPC) zero-forcing beamforming (ZFBF) and random unitary beamforming (RUB) are used to control inter-user interference in MIMO transmissions.
FSO Transmission in the Transmission Control Protocol (TCP) transmission control involves considerations such as re-transmission, re-routing, cross layer design and delay tolerant networking. the Automatic Repeat Request (ARQ) re-transmission protocol can be used to ensure data reliability, with variants including Selective Repeat ARQ (SR-ARQ), Cooperate Diversity ARQ, Modified Diversity ARQ (C-ARQ) and Hybrid ARQ (H-ARQ), with MC-ARQ found to perform best in terms of power efficiency and reducing transmission delay, and C-ARQ performs well in combating turbulence induced fading.
In order to re-route data over FSO links to improve reliability during weather conditions, techniques such as autonomous dynamic path reconfiguration and hybrid routing schemes that combine proactive and reactive routed can be used. These systems however do increase processing delays and network costs.
QoS can be a challenge due to delay fluctuations, data packet rejection ratios and overheads. Strategies for improving QoS include using efficient scheduling and buffer algorithms, tight error control, and appropriate channel access policies. For example, a QoS-based buffer scheme has been shown to minimize packet rejection rate under strong atmospheric conditions in hybrid RF/FSO networks.
Next Generation FSO communication networks potentially include applications such as HDTV signals, military, 5G communication and IoT/IoE wireless services, with devices used for fiber infrastructure such as 100 Gb/s mach-zender modulators (MZM) and wavelength division multiplexing potentially being applied to FSO systems. Channel estimation is a challenge due to high costs and power consumption. Deep learning is one proposed solution, in order to generate perfect probabalistic channel models for received data implements and fast response to input data analysis. Machine learning has been used in optical performance monitoring and is becoming a hot topic in the advancement of future FSO networks.
The unlicensed and wide nature of optical bands allows for the requirements of traffic demands to be met as an alternative to RF systems, with FSO benefits including high connectivity/capacity, security and low power consumption. While there are also challenges with FSO systems, ongoing research provides indications as to potential effective mitigation measures.