Optimal Function Split via Joint Optimization of Power Consumption and Bandwidth in V-RAN

This paper studies Dual site processing in Virtualized Radio Access Network (V-RAN) and it recommends the amount of processing in the dual sites for the functional splits which are proposed by ETSI. This leads to ease of management and flexibility of the operation and increases processing and power efficiencies. To recommend the amount of processing in both sites, the power consumption at several percentages of functional splits is identified to compromise the tradeoff between the midhaul capacity and power consumption. Furthermore, Joint optimization of power consumption and midhaul capacity is performed to validate and recommend the optimal split function

Optimum Functional Splits for Optimizing Energy Consumption in V-RAN

A virtualized radio access network (V-RAN) is considered one of the key research points in the development of 5G and the interception of machine learning algorithms in the Telecom industry. Recent technological advancements in Network Function Virtualization (NFV) and Software Defined Radio (SDR) are the main blocks towards V-RAN that have enabled the virtualization of dual-site processing instead of all BBU processing as in the traditional RAN. As a result, several types of research discussed the trade-off between power and bandwidth consumption in V-RAN. Processing at remote locations instead of BBU reduces mid-haul bandwidth at the expense of power consumption and vice versa. As a result, the integration of NFV and SDR in V-RAN facilitates dynamic power consumption and processing whenever relaxation is needed. This paper studies several functional splits proposed by ETSI in the NFV of the dual-site network. In addition, network performance is analyzed in terms of data rate, power consumption, and energy efficiency (EE) optimization. Furthermore, the combined optimization of power consumption and mid-haul bandwidth are investigated, and optimal operating parameters are recommended for similar network operators. Thus, regulators/operators can adjust their networks with these parameters to achieve the best performance. Additionally, the UEs switching scheme is introduced to sleep some RRHs in low-density traffic to lessen power consumption

A Comprehensive Survey on Resource Allocation for CRAN in 5G and Beyond Networks

The diverse service requirements coming with the advent of sophisticated applications as well as a large number of connected devices demand for revolutionary changes in the traditional distributed radio access network (RAN). To this end, Cloud-RAN (CRAN) is considered as an important paradigm to enhance the performance of the upcoming fifth generation (5G) and beyond wireless networks in terms of capacity, latency, and connectivity to a large number of devices. Out of several potential enablers, efficient resource allocation can mitigate various challenges related to user assignment, power allocation, and spectrum management in a CRAN, and is the focus of this paper. Herein, we provide a comprehensive review of resource allocation schemes in a CRAN along with a detailed optimization taxonomy on various aspects of resource allocation. More importantly, we identity and discuss the key elements for efficient resource allocation and management in CRAN, namely: user assignment, remote radio heads (RRH) selection, throughput maximization, spectrum management, network utility, and power allocation. Furthermore, we present emerging use-cases including heterogeneous CRAN, millimeter-wave CRAN, virtualized CRAN, Non- Orthogonal Multiple Access (NoMA)-based CRAN and fullduplex enabled CRAN to illustrate how their performance can be enhanced by adopting CRAN technology. We then classify and discuss objectives and constraints involved in CRAN-based 5G and beyond networks. Moreover, a detailed taxonomy of optimization methods and solution approaches with different objectives is presented and discussed. Finally, we conclude the paper with several open research issues and future directions

Delay-Aware Green Hybrid CRAN

As a potential candidate architecture for 5G systems,cloud radio access network (CRAN) enhances the system’s capacityby centralizing the processing and coordination at the centralcloud. However, this centralization imposes stringent bandwidthand delay requirements on the fronthaul segment of the networkthat connects the centralized baseband processing units (BBUs)to the radio units (RUs). Hence, hybrid CRAN is proposed toalleviate the fronthaul bandwidth requirement. The concept ofhybrid CRAN supports the proposal of splitting/virtualizing theBBU functions processing between the central cloud (centraloffice that has large processing capacity and efficiency) and theedge cloud (an aggregation node which is closer to the user,but usually has less efficiency in processing). In our previouswork, we have studied the impact of different split points onthe system’s energy and fronthaul bandwidth consumption. Inthis study, we analyze the delay performance of the end user’srequest. We propose an end-to-end (from the central cloud tothe end user) delay model (per user’s request) for differentfunction split points. In this model, different delay requirementsenforce different function splits, hence affect the system’s energyconsumption. Therefore, we propose several research directionsto incorporate the proposed delay model in the problem ofminimizing energy and bandwidth consumption in the network.We found that the required function split decision, to achieveminimum delay, is significantly affected by the processing powerefficiency ratio between processing units of edge cloud and centralcloud. High processing efficiency ratio ( 1) leads to significantdelay improvement when processing more base band functionsat the edge cloud.QC 20170803</p