TLBO-based Resource Allocation scheme in 5G H-CRAN

Abstract

In the direction of resource allocation in 5G and beyond networks, Device-to-Device (D2D) communication is proven to be a promising technology and improves the system throughput. At the same time, the reuse of cellular user's resource block by multiple D2D users introduces interference, which ultimately degrades the system's throughput. Hence, in this paper, we have proposed an efficient resource allocation scheme using Teacher Learner Based Optimization (TLBO) in the context of Heterogeneous Cloud Radio Access Networks (HCRAN) so that the system performance is improved. At first, the cellular user's resource block is assigned to the D2D users based on the calculated data rate at the corresponding cellular user. Consequently, TLBO is applied to this assignment matrix to obtain the optimum assignment/allocation of the cellular user's resource blocks to D2D users. The simulation results demonstrate the efficiency of the proposed scheme compared to the existing related schemes.