# Advances in Improving Energy Efficiency of Fiber-Wireless Access Networks: A Comprehensive Overview
## 4 Energy Efficiency Analyses of Radio-over-Fiber Networks
### Approaches for Improving the Energy Efficiency of Cloud Radio Access Networks
#### 4.2.2 Techniques for Improving Energy Efficiency in Cloud Radio Access Networks  
Since energy efficiency has become one of the main concerns when designing RAN, some initial research analyses have been published with respect to improving the EE of C-RAN networks and they are summarized in Table 3. In the case of the latest 5G mobile cellular networks, the heterogeneous C-RAN (H-CRAN) architecture is composed of a small number of macro BSs and the large number of small BSs (micro, pico, femto) in combination with algorithms for the effective allocation of radio resources in centralized and integrated BBU pools is considered as a promising approach for minimizing network energy consumption. However, to support the expected increase in the number of UDs, wireless services and applications in the future, the number of network elements (the RRUs on the front-end side and the BBUs on the back-end side) will also increase, and the need for improving the RAN's EE will remain. One additional issue with C-RAN architecture is that all of its BBUs are always active, even when user traffic is low. This leads to the high energy consumption of the BBU pool. To address this issue, the authors in ref. [76] proposed a method for estimating BBUs' resource-utilization rate. The method takes into account the data rate requirement, the number of mobile UDs, the RRU bandwidth and the transmission power between the RRU and mobile UDs (Table 3). They also presented the combine and remove (CnR) algorithm for deciding when to switch BBUs off and on. The proposed algorithms were developed with the aim of maximizing the number of sleeping BBUs while maintaining the QoS. The simulation results showed that when compared with traditional RANs, the proposed scheme can save the energy consumption of the BBU pool and the overall RAN system. In the C-RAN, the BBU pool serves a large number of RRU units (Figure 9) and by effectively coordinating the BBUs, network performance in terms of power consumption can be optimized. In order to minimize power consumption caused by communication overhead between the BBUs and RRUs, the authors in ref. [79] presented a scheme for the association of the BBU and the RRU based on graph partitioning and rejoining (Table 3). By using a partition and rejoin scheme, the authors assigned the BBUs to RRUs based on both the individual resource requirements of the RRUs and their communication with each other. The simulation results showed that the algorithm proposed in ref. [79] could reduce power consumption in the BBU pool with linear computational complexity. In ref. [80], the authors presented a power-control algorithm that utilizes mobility prediction to improve EE in the 5G H-CRAN (Table 3). The proposed algorithm predicts the movement of user equipment in vehicular mobility situations and performs RRU switching based on the prediction results. The authors proposed an RRU-switching approach using Markov mobility prediction and a gradient-optimized transmission power method. The simulation results indicated that the proposed algorithm performed better regarding EE compared with existing RRU-switching algorithms.