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An intelligent optimization algorithm for joint MCS and resource block allocation in LTE femtocell downlink with QoS guarantees

机译:一种智能优化算法,具有QoS保证LTE Femtocell下行链路的联合MCS和资源块分配的智能优化算法

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In this paper, we address the problem of joint Resource Block (RB) allocation and Modulation-and-Coding Scheme (MCS) selection for LTE femtocell DownLink (DL). We first formulate the problem as an Integer Linear Program (ILP) whose objective is to minimize the number of allocated RBs of a closed femtocell, while guaranteeing minimum throughput for each user. In view of the NP-hardness of the ILP, we then propose an intelligent optimization algorithm called ACO- HM algorithm with reduced polynomial time complexity. In the ACO-HM algorithm, the Ant Colony Optimization (ACO) algorithm is to allocate appropriate RBs to mobile users, while the Harmonic Mean (HM) method is to select a better MCS than the MINimum/MAXimum MCS selection schemes (MINIMAX). Simulation results show that compared with the ACO-MIN algorithm and the ACO-MAX algorithm, the proposed ACO- HM algorithm achieves better performance with fewer RBs and provides Quality-of-Service (QoS) guarantees.
机译:在本文中,我们解决了LTE Femtocell下行链路(DL)的联合资源块(RB)分配和调制和编码方案(MCS)选择的问题。 我们首先将问题称为整数线性程序(ILP),其目的是最小化闭合毫微微小区的分配RB的数量,同时保证每个用户的最小吞吐量。 鉴于ILP的NP - 硬度,我们提出了一种称为ACO-HM算法的智能优化算法,具有减少的多项式时间复杂度。 在ACO-HM算法中,蚁群优化(ACO)算法是将适当的RB分配给移动用户,而谐波平均值(HM)方法是比最小/最大MCS选择方案(MIMIMAX)选择更好的MCS。 仿真结果表明,与ACO-MIN算法和ACO-MAX算法相比,所提出的ACO-HM算法具有更好的RBS性能,提供服务质量(QoS)保证。

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