Digital Signal Processing


Modeling and Evaluation of Radio over Fiber Communication Systems on Employing Nanophotonic Devices

Authors: Sai Venkatesh Balasubramanian, Ganapathy R, Porsezian K, Easwaran M, Joshva RG

Radio over Fiber refers to a technology whereby light is modulated by a radio signal and transmitted over an optical fiber link to facilitate wireless access. The present work purports to the modeling of radio over fiber systems in the MATLAB environment on employing specially designed photonic crystal fibers, consisting of subwavelength-core dielectric photonic nanowires embedded in their cladding, as optical channels between the main central station and the set of base stations and silicon photonic based electro-optic modulators. Data transmission at terahertz frequencies using orthogonal frequency division multiplexing schemes with cyclic error control coding along with digital modulation schemes such as amplitude shift keying and binary phase shift keying have been implemented. Different carrier signals such as solitons, similaritons, square, and sine waves are considered. In simulating the radio over fiber system, three different media are considered. In the first stage of signal propagation, photonic crystal fibers embedded with photonic nanowires in their cladding are considered and signal propagation through them is numerically modeled using the predictor-corrector symmetrized split step Fourier method. In the second stage, electrical transmission lines that are modeled as microstrips using S-parameters are considered. In the last stage of signal propagation, wireless channel modeled using additive white Gaussian noise and multipath fading, is considered. The performance of the aforementioned communication system is reviewed using standard metrics such as bit error rate and eye diagrams. It is shown that solitons are more robust carriers for terahertz communications compared to the other carriers and that it is possible to achieve a relatively distortion free communication system even amidst the worst possible SNR levels.

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[v1] 2015-10-28 09:16:04

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