Abstract-Breaking the fronthaul capacity limitations is vital to make cloud radio access network (C-RAN) scalable and practical. One promising way is aggregating several remote radio units (RRUs) as a cluster to share a fronthaul link, so as to enjoy the statistical multiplexing gain brought by the spatial randomness of the traffic. In this letter, a tractable model is proposed to analyze the fronthaul statistical multiplexing gain. We first derive the user blocking probability caused by the limited fronthaul capacity, including its upper and lower bounds. We then obtain the limits of fronthaul statistical multiplexing gain when the cluster size approaches infinity. Analytical results reveal that the user blocking probability decreases exponentially with the average fronthaul capacity per RRU, and the exponent is proportional to the cluster size. Numerical results further show considerable fronthaul statistical multiplexing gain even at a small to medium cluster size.

Functional split is a promising technique to flexibly balance the processing cost at remote ends and the fronthaul rate in cloud radio access networks (C-RAN). By harvesting renewable energy, remote radio units (RRUs) can save grid power and be flexibly deployed. However, the randomness of energy arrival poses a major design challenge. To maximize the throughput under the average fronthaul rate constraint in C-RAN with renewable powered RRUs, we first study the offline problem of selecting the optimal functional split modes and the corresponding durations, jointly with the transmission power.We find that between successive energy arrivals, at most two functional split modes should be selected.Then the optimal online problem is formulated as an Markov decision process (MDP). To deal with the curse of dimensionality of solving MDP, we further analyze the special case with one instance of energy arrival and two candidate functional split modes as inspired by the offline solution, and then a heuristic online policy is proposed. Numerical results show that with flexible functional split, the throughput can be significantly improved compared with fixed functional split. Also, the proposed heuristic online policy has similar performance with the optimal online one, as validated by simulations. Index TermsFunctional split, energy harvesting, cloud radio access network (C-RAN), fronthaul, Markov decision process (MDP). PDCPHigh RLC Low RLC High MAC Low MAC High PHY Low PHY Low PHY High PHY Low MAC High MAC Low RLC High RLC PDCP Uplink Downlink BBU RRU RF RF Fig. 1. Illustration of baseband functions with multiple candidate split modes. I. INTRODUCTION Cloud radio access network (C-RAN) [2], which centralizes the baseband functions at the baseband units (BBUs), can efficiently reduce the complexity of the remote radio units (RRUs), and thus the operation and deployment costs. Centralized baseband processing also enables efficient cooperative signal processing to increase the network capacity. In C-RAN, the fronthaul network transports the baseband signals between the BBUs and the RRUs. However, for fully centralized C-RAN, i.e., all baseband functions are centralized at the BBUs, the fronthaul rate requirement is high, which poses a major design challenge on C-RAN. For example, in a single 20MHz LTE antenna-carrier system, 1Gbps fronthaul rate is required with the standard CPRI interface [3]. To support massive MIMO and other emerging technologies, the required fronthaul rate will be too high to bear. Different from fully centralized C-RAN, by placing some baseband and network functions at RRUs, functional split is a promising technique to reduce the fronthaul rate requirement [4], [5]. There are multiple candidate functional split modes corresponding to different split points on the chain of baseband functions, as illustrated in Fig. 1. For each mode, the functions placed at the right side of the corresponding vertical dashed line are placed at the RRU, while the others are centralized at the BBU. The fronthaul rate requi...

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Abstract-The radio access networks (RANs) need to support massive and diverse data traffic with limited spectrum and energy. To cope with this challenge, software-defined radio access network (SDRAN) architectures have been proposed to renovate the RANs. However, current researches lack the design and evaluation of network protocols. In this paper, we address this problem by presenting the protocol design and evaluation of hyper-cellular networks (HyCell), an SDRAN framework making base station (BS) operations globally resource-optimized and energy-efficient (GREEN). Specifically, we first propose a separation scheme to realize the decoupled air interface in HyCell. Then we design a BS dispatching protocol which determines and assigns the optimal BS for serving mobile users, and a BS sleeping protocol to improve the network energy efficiency. Finally, we evaluate the proposed design in our HyCell testbed. Our evaluation validates the feasibility of the proposed separation scheme, demonstrates the effectiveness of BS dispatching, and shows great potential in energy saving through BS sleeping control.

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