RBF-SVM Based Resource Allocation Scheme for 5G CRAN Networks

Cloud Radio Access Network (CRAN) is one of the possible solutions to provide high data rates for next generation users (fifth generation). Additionally, CRAN also reduces the operational (OPEX) and capital (CAPX) cost. In the current cellular system (up to fourth generation), resource allocation is allocated by base station (BS) based on channel state information (CSI). This increases the overhead as well as operational and capital cost. Therefore, in this paper, a CRAN based resource allocation scheme for fifth generation (5G) network is presented. The proposed scheme consider the user position in spite of CSI. The proposed resource allocation scheme applies machine learning technique. Specifically, radio basis function-support vector machine (RBF-SVM) machine learning technique is applied for allocating the resource block. The Numerical result shows that proposed scheme gives the significant result over the random forest based resource allocation scheme and other machine learning based resource allocation scheme.