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Joint Optimization of Communication Latency and Resource Allocation in Cloud Radio Access Networks

机译:云无线电接入网中通信时延和资源分配的联合优化

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This paper addresses a constrained resource allocation problem in Cloud Radio Access Networks (C-RAN). This problem consists in determining the best strategies to assign antennas (Remote Radio Head - RRH) demands to available edge data centers (pool of BaseBand Units - BBU) when jointly optimizing communication latency and resource consumption. Telecommunications Service Providers (TSPs) need new algorithms that enable to jointly reduce their OPEX and CAPEX when embracing C-RAN technology. This paper proposes a mathematical model based on an integer linear programming formulation, to optimally solve the constrained resource allocation problem. To scale and handle much larger number of antennas and edge data centers in acceptable times, a faster and more efficient algorithm based on matroid theory is provided. Simulation results show the scalability of our algorithms and quantify the potential benefits of the discussed approaches in the context of C-RAN.
机译:本文解决了云无线电接入网络(C-RAN)中的受限资源分配问题。这个问题在于确定在共同优化通信延迟和资源消耗时,将天线(远程无线头-RRH)需求分配给可用边缘数据中心(基带单元池-BBU)的最佳策略。电信服务提供商(TSP)需要新的算法,以便在采用C-RAN技术时能够共同降低其OPEX和CAPEX。本文提出了一种基于整数线性规划公式的数学模型,以最优地解决资源分配受限的问题。为了在可接受的时间内缩放和处理大量天线和边缘数据中心,提供了一种基于拟阵理论的更快,更高效的算法。仿真结果表明了我们算法的可扩展性,并在C-RAN的背景下量化了所讨论方法的潜在利益。

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