Optimized load balancing by dynamic BBU-RRH mapping in C-RAN architecture

Cloud Radio Access Network (C-RAN) is one of the key architectures for the next generation of mobile networks (5G) that aim at centralized processing and management, collaborative radios and cloud computing in real time. These features enable the architectures to make a rational adjustment to the connection between remote radio heads (RRHs) and baseband units (BBUs) dynamically. This is important since if this feature is neglected, it can cause difficulties such as blocked calls and low-quality connections. This study investigates this area and proposes an optimized mapping model for RRH-BBU that seeks a more equitable and effective balancing. The Key Performance Indicator (KPI) of blocked calls was used for this to measure the quality of service (QoS). A particle Swarm algorithm (PSO) was created to minimize the number of blocked calls and additionally balancing the processing load between the BBUs. Scenario from literature was employed that consists of 19 RRHs distributed in a geographic area, which can be mapped in a BBU pool that manages two BBUs with three sectors each. The initial configuration on average, led to 80 blocked calls. The results obtained by the PSO show that there was a reduction of up to 100% of blocked calls, as well as a more equitable load distribution between the BBUs. Additionally, realistic scenarios with different user profiles were also included, since they demonstrate that these factors have a direct impact on the load generated in the BBUs and hence, affect their balance.