## 1 Introduction  
According to a recent prediction [1], the mobile data traffic will increase 10 times from 2017 to 2022, and more than 50 billion devices will be connected to the existing infrastructure by 2020. A transition from the static radio access networks (RANs) to flexible and reconfigurable networks through the virtualizations and cloudification was highly desirable to anticipate the traffic demands of future 5G cellular networks. Recently, cloud radio access networks (C-RANs) have been proposed, which are enhancements of classical RAN architectures through the cloudification and virtualizations techniques to comply with the requirements of envisioned 5G mobile networks. In C-RANs, the base station functionalities are split into distributed units known as the remote radio heads (RRHs) and central units known as the baseband units (BBUs), which are virtualized and pool at a central cloud [2]. The C-RANs approach brings several advantages for the network operators, including a reduction in the operational, management, and energy costs, as well as effective implementations of the coordinated multipoint (CoMP) transmission and reception schemes for the inter-cell interference mitigations [3]. With the virtualization of base station functionalities, the scalability of RAN architectures has been improved, and the spectral efficiency of the operator's network can be increased. Furthermore, a number of RRHs can be installed at the cell sites by simply connecting with the BBU pool, which reduces the cost of deploying expensive baseband processing units nearer to the RRHs at the cell sites [4]. The 3 rd generation partnership project (3 GPP) [5] defined the eight functional splits for the C-RANs in order to connect the RRHs and the BBU pool. A chosen functional split uniquely defines the properties of the system design such as the complexity, costs, latency, data rates, throughputs, and achievable statistical multiplexing gains. In a low-level functional split, which has the maximum benefits of performance and cost efficiency, all the higher layer functions are moved into the BBU pool, and only the radio frequency (RF) functions are employed in the RRHs at a cell site [6]. This requires a high-speed communication link between the RRHs and the BBU pool, which is referred to as the mobile fronthaul (MFH). The fronthaul segment is connected to the core network through the backhaul links [7]. Figure 1 depicts the considered MFH networks of the C-RANs architecture. A MFH carries the digitized in-phase and quadrature (IQ) samples of baseband signals through the common public radio interface (CPRI) [8]. The CPRI is a non-packetized protocol that was specifically designed for the fronthaul networks by the leading telecom vendors, and cannot be integrated with other packetized transmissions unless a circuit (e.g., a wavelength) is reserved for it [9]. In this work, we consider a recent evolution of CPRI that is eCPRI (enhanced-CPRI) [10], which can packetize the IQ samples within Ethernet frames and is fully compatible with Ethernet systems. The eCPRI-based MFH networks are expected to deliver the throughputs of 10 Gbps, packet delay variations (PDVs) within 100 ns, and end-to-end (E2E) latency of less than 250 \(\upmu\)s for all the RRHs streams [11; 12]. The aforementioned requirements can only be fulfilled with the expensive and extremely high-capacity optical links. However, the cost of deploying such optical fronthaul bridged networks significantly increased the capital expenditure (CAPEX) and operational expenses (OPEX) for the network operators. As a result, the cost benefits of the C-RANs architecture could not be realized [13]. Thus, the implementation of low-cost MFH becomes a challenging issue in the C-RANs [14]. The 10 gigabit Ethernet systems can be more economical and remunerative solutions as compared to the optical networks to carry the eCPRI traffic in the MFH.