Energy-Efficient Resource Allocation In Massive MIMO Empowered Cloud-Radio Access Networks

Cloud-Radio Access Network (C-RAN)has been considered as one of the enabling network architectures towards the implementation of the fifth genera-tion wireless systems. Combining with advanced radio, wireless and computing techniques, C-RAN provides great potential to improve the network capacity,spectrum efficiency, energy efficiency and operational flexibility. Therefore,C-RAN has attracted considerable attention from both academia and industry.In this thesis, we review the architecture and some of the physical layer signal processing issues of C-RAN. The functional split and limited-capacity fronthaul impose physical layer issues and signal processing opportunities, e.g., chan-nel state information acquisition, effective compress-and-forward methods and intelligent resource allocation schemes. Moreover, some emerging 5G tech-niques which can be supported by/or integrated with C-RAN architecture, such as software-defined networking heterogeneous networking, communication at millimeter wave frequencies and full-duplex radio are discussed. Furthermore,this thesis focuses on the energy-efficiency power allocation of massive multi-input multi-output empowered C-RAN.Firstly, challenges of energy efficiency design in C-RAN are highlighted in the context. The state-of-the-art of energy efficiency is shown with detailed explanation. Network centric and user-centric energy efficiency approaches are discussed. Energy efficiency solutions for massive multi-input multi-output and C-RAN are highlighted in the contexts. Differences between conventional radio access network and C-RAN power consumption are discussed. Radio remote head selection problem is also discussed. Secondly, energy efficiency power allocation in C-RAN with data-sharing strategy is designed. The closed form expression is derived with maximum ratio transmission precoding. The energy efficiency maximization problem formulated with per radio remote head power constraint and minimum quality-of-service requirement for each user. Finally,the conclusion and future directions are also presented, where mobile edge com-puting and caching, multi-dimensional resource management and physical layer security are highlighted.