Artificial Bee optimization aided joint user association and resource allocation in HCRAN

Abstract

Heterogeneous cloud radio access network (HCRAN) is a versatile network that leverages the heterogeneous base-station (BS) deployment scheme of Heterogeneous Networks (HetNets) and the centralized baseband signal processing functionalities of cloud RAN (CRAN). Due to dissimilarities between the traditional mobile systems and HCRAN, the currently available power-efficient networking mechanisms of traditional mobile systems cannot fully support HCRAN. Thus, these mechanisms are not feasible for the efficient reduction of energy consumption in HCRAN. In this paper, a multi-carrier orthogonal frequency division multiplexing (OFDMA) based joint user association and resource allocation problem is solved to optimize the HCRAN energy efficiency. The joint user association and resource allocation is a complex problem because the resource allocation to users depends on the RRH-User association. Therefore, a new mechanism is used to generate the initial random solution in the modified Artificial Bee Colony (ABC) algorithm and proposed to address the joint user association and resource allocation problem without decomposing it into two sub-problems. Simulation results show that the ABC algorithm provides a better energy efficiency improvement compared to the existing algorithms.