Due to the significant increase in data traffic and the large number of devices using Internet Protocol (IP), operators and researchers are seeking solutions to meet the growing demand. One of the most attractive solutions is Heterogeneous Cloud Radio Access Networks (H-CRAN), which has the capability to address current generation problems and bring various improvements, such as centralized processing and greater energy efficiency. The central challenge lies in the complexity of managing and optimizing these resources efficiently, especially in highdemand scenarios with dense device populations. However, the orchestration of resources such as radio, mapping between radio and BaseBand Unit (BBU), and load balancing in the BBU
pool remains critically important. This thesis presents a framework aimed at reconfiguring the mobile network in areas affected by the variability of tidal effect traffic, ensuring high availability, energy savings, and improved data processing efficiency. The results obtained were compared with other approaches in the literature and demonstrated that the proposed framework optimizes the resources of the Peak Remote Radio Head (PRRH) and the BBU without compromising the user’s minimum QoS. The findings highlight a reduction of up to 9% in
the number of active antennas over a 24-hour period and emphasize that the proposed solution consumes up to 14% less energy than the primary reference in this thesis.
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