Radio resource management for cloud-RAN networks with computing capability constraints

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Abstract
Featured by centralized processing and cloud-based infrastructure, cloud radio access network (C-RAN) has emerged as a promising solution to handle the data proliferation in future wireless networks. However, the attractive capacity enhancement brought by large-scale centralized processing comes along with increased computing resource requirement in the baseband unit (BBU) pool. Thus, computing resource as another dimension of manageable resource needs to be considered in resource allocation and C-RAN system design. In this paper, we first characterize the relationship between PHY transmission characteristics and the required computing resource in the BBU pool. Based on this, we propose a feasible algorithm to maximize the network sum-rate under limited computing resource constraint, which is a binary-integer non-linear programming (BINLP) problem with non-convex constraints in nature. Numerical results show the significant impact of computing resource on both user-RRH association strategy and the achievable sum-rate performance.

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