Improvement of energy efficiency by dynamic load consolidation in C‐RAN

• Published in: International journal of communication systems 2022-04, Vol.35 (6), p.n/a
• Main Authors: Aktar, Mst. Rubina, Anower, Md. Shamim
• Format: Article
• Language: English
• Subjects: 5G mobile communication; Algorithms; Cellular communication; Consolidation; C‐RAN; Dynamic loads; Energy consumption; Energy efficiency; load consolidation; Optimization; Power consumption; Radio; Signal processing; Subsystems; Traffic capacity
• ISSN: 1074-5351; 1099-1131
• DOI: 10.1002/dac.5087

Summary The Fifth Generation (5G) network is the next step in the evolution of cellular networks, which are anticipated to encounter a remarkable growth in traffic. To meet this traffic requirement, the network capacity must be increased, which would inevitably necessitate the expansion of additional base stations (BSs). Moreover, the expenses and energy consumption of BSs are excessively high. The highly complex signal processing in baseband units contributes to a substantial amount of energy consumption. Consequently, cloud radio access network (C‐RAN) has been demonstrated as an effective approach to overcoming 5G wireless challenges through an energy‐efficient means. C‐RAN architecture has a baseband unit (BBU) pool that consists of the number of BBUs and remote sites, which are called remote radio heads (RRHs). As a sharing of ancillary subsystems into one location, BBU pooling has a significant impact on reducing power consumption. However, C‐RAN necessitates a novel paradigm of energy consumption for resource optimization. In this article, a C‐RAN with a dynamic load consolidation algorithm depending on traffic condition is presented to jointly take the power consumption and energy efficiency targeting to decrease power consumption and increase energy efficiency. To capture the energy consumption of C‐RAN, a new energy consumption scheme considering the BBU cloud, optical link, and radio side power has been proposed that optimizes the BBU resources. Numerical results come about based on simulation settings illustrate that the presented model accomplishes an improved energy‐efficient performance with respect to the referred baseline RAN system scheme. Following the proposed network, a server cloud manager (CM) is placed in the BBU pool which handles all the operations and also maintains track of network traffic load. Then, a load consolidation algorithm based on load conditions is placed on the CM. Thereafter, four performance metrics, namely, power consumption, energy efficiency, energy efficiency gain, and numbers of active BBUs, are implemented in the designed network, and it accomplishes an improved energy‐efficient performance when compared to a reference network.