Optimized Radio-over-Fiber-based cellular backhauling strategy using genetic algorithms and Pareto fronts

Abstract

Radio-over-Fiber (RoF)-based cellular backhauling consitutes a promising solution to realize a cost-effective evolution of radio access networks towards higher radio-cells densification. In this paper, we recall the main characteristics of an innovative cellular backhauling all-optical network architecture called Generic Radio-over-Fiber Access Network (GeRoFAN) aiming to federate 4G system radio cells. However, the transport of multiple radio channels over an analog RoF link is subject to optical crosstalk and intermodulation distortions causing a decrease of the wireless system capacity. Supported by an analytical modeling of the relevant optical transmission limitations, we propose an impairment-aware radio cellular backhauling strategy for GeRoFAN able to maximize the radio cellular capacity while achieving an efficient use of optical resources. This optimization problem is solved through Pareto-based Genetic Optimization (PaGeO), a multi-objective meta-heuristic based on evolutionary algorithms and exploiting the concept of Pareto front. Numerical results indicate that PaGeO, applied to LTE cellular system, outperforms alternative backhauling strategies by achieving an excellent compromise between preserving the radio capacity of the system and the number of required optical channels. We also highlight how the optimal backhauling strategy calculated using PaGeO enables GeRoFAN to take full benefit from overlaying several radio channels per cell site.