Two-Level Allocation for H-CRAN Architecture Based in Offloading

The accelerated growth of data and applications are significant challenges for the next generation of mobile networks. Amongst them, it is highlighted the necessity for a coexistence of new and old patterns during the transition between architectures. Thus, this paper has investigated solutions for offloading into a hybrid architecture, also known as H-CRAN (Heterogeneous Cloud Radio Access Network Architecture), that centralizes processing and searches for a better use of network resources. The optimization strategy was performed through the evolutive algorithm PSO (Particle Swarm Optimization) and another based on FIFO (First In, First Out), for benchmarking purposes. Maximum Bits Rate average and number of users with or without connections were used as a measurement of performance. Through the results, it was noticed an improvement of approximately 60% in the Maximum Bit Rate, when compared to the traditional approach, enabling a better service to the users.