International audienceCloud-Radio Access Network (C-RAN) is a new emerging technology that holds alluring promises for Mobile network operators regarding capital and operation cost savings. However, many challenges still remain before full commercial deployment of C-RAN solutions. Dynamic resource allocation algorithms are needed to cope with significantly fluctuating traffic loads. Those algorithms must target not only a better quality of service delivery for users, but also less power consumption and better interference management, with the possibility to turn off RRHs that are not transmitting. To this end, we propose in this paper a dynamic two-stage design for downlink OFDMA resource allocation and BBU-RRH assignment in C-RAN. Specifically, we first model the resource and power allocation problem in a mixed integer linear problem for real-time fluctuating traffic of mobile users. Then, we propose a Knapsack formulation to model the BBU-RRH assignment problem. Simulation results show that our proposal achieves not only a high satisfaction rate for mobile users, but also minimal power consumption and significant BBUs savings, compared to state-of-the-art schemes
In this paper, we address the problem of downlink resource allocation and admission control for an Orthogonal Frequency Division Multiple Access (OFDMA)-based Cloud Radio Access Network (C-RAN). Specifically, we formulate the resource allocation and admission control for mobile users in C-RAN as an optimization problem, subject to constraints on mobile users data rate requirements, maximum transmission power and fronthaul links capacity. By dropping the non-linear constraint and reformulating the problem linearly using the framework of the well-known big-M method, we propose a two-stage algorithm that can efficiently solve it. To satisfy the strict timing requirement of wireless communications in such a system, a time constraint was added to our algorithm. Numerical results demonstrate the good performance of our proposal in terms of number of accepted users and total transmission power, when compared with state-ofthe-art methods used for the control admission task in C-RAN.
As Mobile Network Operators (MNOs) are shifting towards Cloud-Radio Access Network (C-RAN), they have to upgrade their infrastructure to not only support higher processing capacities but also to be more resilient. We consider the problem where a MNO is faced with the choice of selecting virtualized Baseband Units (BBUs) from various cloud service providers, that are each characterized with distinct failure probabilities and prices. We propose to solve the BBU selection problem, formulated as an Integer Linear Program (ILP) subject to BBU capacity and virtualization cost using the Branch-and-Price algorithm. We present several schemes depicting which optimization goal the MNO can foster the most: BBU processing power minimization, resiliency, traffic handling or all. Simulation results demonstrate the good performance of our algorithm to solve the BBU selection problem for all schemes, while also emphasizing the advantages of a particular one that can realize more than 10% in virtualization cost savings.
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