A new technique for transmitting information through multimode fiber-optic cables is presented. This technique sends parallel channels through the fiber-optic cable, thereby greatly improving the data transmission rate compared with that of the current technology, which uses serial data transmission through single-mode fiber. An artificial neural network is employed to decipher the transmitted information from the received speckle pattern. Several different preprocessing algorithms are developed, tested, and evaluated. These algorithms employ average region intensity, distributed individual pixel intensity, and maximum mean-square-difference optimal group selection methods. The effect of modal dispersion on the data rate is analyzed. An increased data transmission rate by a factor of 37 over that of single-mode fibers is realized. When implementing our technique, we can increase the channel capacity of a typical multimode fiber by a factor of 6.
© 2001 Optical Society of America
(060.0060) Fiber optics and optical communications : Fiber optics and optical communications
(060.2330) Fiber optics and optical communications : Fiber optics communications
(060.2350) Fiber optics and optical communications : Fiber optics imaging
(060.4230) Fiber optics and optical communications : Multiplexing
(200.4260) Optics in computing : Neural networks
Ronald K. Marusarz and Mohammad R. Sayeh, "Neural Network-Based Multimode Fiber-Optic Information Transmission," Appl. Opt. 40, 219-227 (2001)