The accelerated data and apps growth represents significant challenges to
the next generation of mobile networks. Amongst them, it is highlighted the necessity
for a co-existence of new and old patterns during the transition of 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 a better use of the network resources. The
strategy of optimization was analyzed through the evolutive algorithm PSO (Particle
Swarm Optimization), in order to find a suboptimal solution to the allocation
of two levels (TLA) in the H-CRAN architecture and another one based on FIFO
(First In, First Out), for benchmarking purposes. SNR (Noise Interference Signal)
average, Maximum Bit Rate, the number of users with or without connections and
number of connections in RRHs and macro were used as performance measurements.
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.
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