A new fault detection method using machine learning in analog radio-on-fiber MIMO transmission system

抄録

In this letter, we propose a new fault detection method in a wired-wireless multiple-input and multiple-output (MIMO) transmission over an analog radio-on-fiber (A-RoF) network. The A-RoF architecture makes the configuration of the remote node simple, however, lots of radio frequency (RF)-band analog devices are used in it, such as semiconductor fiber laser, optical fiber link, photo-detector and electrical amplifiers, and the methodology for detecting the fault on these devices has not been discussed. Conventional methods require dedicated devices for sending fault messages via out-of-band wireless data transmission, which increases the hardware requirement of the whole system configuration. This letter proposes a machine learning approach in an A-RoF-based MIMO transmission without any additional devices.