云接入网络中基于容量最大化的射频拉远头选择算法设计

Optimized RRHs Selection Algorithm Design for Throughout Maximization in Cloud Radio Access Network

不同于传统的LTE-Advanced网络,云接入网络(C-RAN)通过前程链路将复杂数据处理从射频拉远头(RRH)转移至基带单元池(BBU Pool)。然而,由于C-RAN前程链路容量有限,系统总吞吐量并不一定能显著提升。在本文中,我们通过优化RRHs选择实现吞吐量的最大化。更准确地说,本文在前程容量约束条件下设计了一种选择活动RRHs集的优化算法,以实现系统容量的最大化。此外,本文分别推导了低信噪比(Low SNR)与高信噪比(High SNR)下,选择RRHs数目的渐进最优的闭合表达式。仿真结果表明,比起其他方案,本文所提出的RRH选择方案能够在有限的前程容量限制与任意给定RRHs数量下,有效实现吞吐量的提升。

Unlike traditional LTE-Advanced networks,cloud access network(C-RAN)transfers complex baseband data processing from the radio frequency heads(RRHs)to the baseband unit pool(BBU Pool)over the fronthaul link.However,due to the limited capacity of the fronthaul link,the overall throughput gain may not be significantly achieved.In this paper,we aim to maximize throughput by optimizing RRH selection.More precisely,this paper designs an optimization algorithm to select the active RRHs set under the fronthaul constraints to maximize the system capacity.In addition,this paper derives the asymptotically optimal closed-form expressions for the number of selected RRHs under low signal-to-noise ratio(SNR)and high SNR conditions.Simulation results show that the RRH selection scheme proposed in this paper can improve the throughput effectively under fronthaul constraint and any given number of RRHs.