Energy Efficiency and Quality of Services in Virtualized Cloud Radio Access Network

Cloud Radio Access Network (C-RAN) is being widely studied for soft and green fifth generation of Long Term Evolution - Advanced (LTE-A). The recent technology advancement in network virtualization function (NFV) and software defined radio (SDR) has enabled virtualization of Baseband Units (BBU) and sharing of underlying general purpose processing (GPP) infrastructure. Also, new innovations in optical transport network (OTN) such as Dark Fiber provides low latency and high bandwidth channels that can support C-RAN for more than forty-kilometer radius. All these advancements make C-RAN feasible and practical. Several virtualization strategies and architectures are proposed for C-RAN and it has been established that C-RAN offers higher energy efficiency and better resource utilization than the current decentralized radio access network (D-RAN). This project studies proposed resource utilization strategy and device a method to calculate power utilization. Then proposes and analyzes a new resource management and virtual BBU placement strategy for C-RAN based on demand prediction and inter-BBU communication load. The new approach is compared with existing state of art strategies with same input scenarios and load. The trade-offs between energy efficiency and quality of services is discussed. The project concludes with comparison between different strategies based on complexity of the system, performance in terms of service availability and optimization efficiency in different scenarios

Soft-Defined Heterogeneous Vehicular Network: Architecture and Challenges

Heterogeneous Vehicular NETworks (HetVNETs) can meet various quality-of-service (QoS) requirements for intelligent transport system (ITS) services by integrating different access networks coherently. However, the current network architecture for HetVNET cannot efficiently deal with the increasing demands of rapidly changing network landscape. Thanks to the centralization and flexibility of the cloud radio access network (Cloud-RAN), soft-defined networking (SDN) can conveniently be applied to support the dynamic nature of future HetVNET functions and various applications while reducing the operating costs. In this paper, we first propose the multi-layer Cloud RAN architecture for implementing the new network, where the multi-domain resources can be exploited as needed for vehicle users. Then, the high-level design of soft-defined HetVNET is presented in detail. Finally, we briefly discuss key challenges and solutions for this new network, corroborating its feasibility in the emerging fifth-generation (5G) era

Understanding the Computational Requirements of Virtualized Baseband Units using a Programmable Cloud Radio Access Network Testbed

Cloud Radio Access Network (C-RAN) is emerging as a transformative architecture for the next generation of mobile cellular networks. In C-RAN, the Baseband Unit (BBU) is decoupled from the Base Station (BS) and consolidated in a centralized processing center. While the potential benefits of C-RAN have been studied extensively from the theoretical perspective, there are only a few works that address the system implementation issues and characterize the computational requirements of the virtualized BBU. In this paper, a programmable C-RAN testbed is presented where the BBU is virtualized using the OpenAirInterface (OAI) software platform, and the eNodeB and User Equipment (UEs) are implemented using USRP boards. Extensive experiments have been performed in a FDD downlink LTE emulation system to characterize the performance and computing resource consumption of the BBU under various conditions. It is shown that the processing time and CPU utilization of the BBU increase with the channel resources and with the Modulation and Coding Scheme (MCS) index, and that the CPU utilization percentage can be well approximated as a linear increasing function of the maximum downlink data rate. These results provide real-world insights into the characteristics of the BBU in terms of computing resource and power consumption, which may serve as inputs for the design of efficient resource-provisioning and allocation strategies in C-RAN systems.Comment: In Proceedings of the IEEE International Conference on Autonomic Computing (ICAC), July 201