Mixed mmWave RF/FSO Relaying Systems Over Generalized Fading Channels With Pointing Errors

• Published in: IEEE photonics journal Vol. 9; no. 1; pp. 1 - 14
• Main Authors: Trinh, Phuc V., Truong Cong Thang, Pham, Anh T.
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 01.02.2017; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Asymptotic series; Atmospheric modeling; Computer architecture; Exact solutions; Fading channels; Fifth-generation (5G) backhaul networks; free-space optics (FSO); Microprocessors; Millimeter waves; millimeter-wave radio frequency (mmWave RF); mixed RF/FSO systems; Málaga channel; Outages; pointing errors; Radio frequency; Rician channel; Rician channels; Signal fading; Signal to noise ratio
• ISSN: 1943-0655; 1943-0655; 1943-0647
• DOI: 10.1109/JPHOT.2016.2644964

This paper studies the performance of mixed millimeter-wave radio-frequency (mmWave RF), free-space optics (FSO) systems in a highly scalable and cost-effective solution for fifth-generation (5G) mobile backhaul networks. The mmWave RF and FSO fading channels are, respectively, modeled by the Rician and the generalized Malaga (M) distributions. The effect of pointing errors due to the misalignment between the transmitter and the receiver in the FSO link is also included. Novel accurate closed-form expressions for the cumulative distribution function, the probability density function, and the moment generating function (MGF) in terms of Meijer's G functions are derived. Capitalizing on these new results, we analytically derive precise closed-form expressions for various performance metrics of the proposed system, including the outage probability, the average bit error rate (ABER), and the average capacity. Additionally, new asymptotic results are provided for the outage probability, the MGF, and the ABER in terms of simple elementary functions by applying the asymptotic expansion of the Meijer's G function at high signal-to-noise ratios (SNRs). Numerical results further validate the mathematical analysis by Monte-Carlo simulations.