無線電存取網路虛擬化旨為將基礎建設與無線電資源的抽象化與共享化，其實現軟體無線電技術，將基地台區分為硬體遠端射頻元件RRH (remote radio head) 與軟體基頻元件BBU (baseband unit) ，可以大幅將地降低佈署與營運的成本、節約能源並且提高資源使用效率，故其為達成5G行動通訊網路高效率與低延遲之嚴格要求的關鍵技術。本論文針對雲端無線電存取網路虛擬化，利用USRP (Universal Software Radio Peripheral) 硬體，結合開源軟體OpenAirInterface，並且導入開源容器技術Docker，實作可攜帶和低價的5G雲端無線電存取網路虛擬化實驗平台，完整地包含BBU資源池、與核心網路等元件。

在此實驗平台中，我們透過輕量化的Docker動態開關容器而能有效率地配置BBU給RRH。前端網路透過封包化的Ethernet來支援點對多點傳輸，降低佈署成本與提高使用效率。此低價的實驗平台可供學術界驗證5G電信網路中雲端無線電存取網路上所設計的機制與開發的理論模型，包含底層的干擾控制、節能設計、存取控制、負載平衡、網路架構設計、流量控制等。整體規劃不僅將深入探討滿足5G行動通訊技術所需的關鍵特性，並在此實驗平台上試驗各種可能的解法與可行性。

The aim of radio access network virtualization is abstracting, sharing for infrastructure and radio resources. It implements software-defined radio technology by dividing base station into remote radio heads (RRH) and baseband unit (BBU). It is a key technique to reach requirements for high efficiency and low latency for 5G mobile communication network by reducing the cost of deployment and operations, and enhancing the efficiency of using resources. The article focuses on cloud radio access network virtualization, uses USRP (Universal Software Radio Peripheral) hardware with open-source software OpenAirInterface, and imports open-source container technology Docker to implement portable, inexpensive and energy-saving 5G cloud radio access network virtualization experiment platform including BBU pool, EPC (Evolved Packet Core Network) , etc.

We can efficiently configure BBU to RRH by dynamic opening container via Docker in experiment platform. With packaged Ethernet fronthaul that supports multipoint transmission, it can reduce the cost of deployment and enhance the efficiency of using resources. The low price experiment platform provides academia to verify mechanisms and theoretical models of cloud radio access network for 5G telecommunications networks, including interference control on the low layer, the design of energy-saving, access control, load balancing, flow control, etc. Our plan is to explore key features required by 5G mobile communication technology and to test every possible solution with feasibility in the experimental platform.

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