利用异构蜂窝网络中的双重连接

N. Prasad, S. Rangarajan
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引用次数: 12

摘要

我们考虑允许双重连接的异构蜂窝网络(HetNets)上的网络效用最大化问题。双连接(DC)是一项针对新兴的实际HetNet部署的功能,该功能将包括传输节点之间的非理想(更高延迟)连接,最近已被引入LTE-Advanced标准。DC允许宏节点和另一个(通常是微型或微型)节点同时为用户提供服务,并且在服务节点之间需要相对粗糙的协调。对于这样一个支持数据中心的HetNet,我们全面分析了在所有可行的关联中确定一个最优用户关联的问题,该问题在每个用户速率约束下最大化加权和速率系统效用。在这里,在任何可行的关联中,每个用户都可以与任何一个宏节点(在给定的宏节点集合中)和位于所选宏节点覆盖区域内的任何一个微节点相关联(即配置为从其中接收数据)。我们表明,值得注意的是,这个问题可以被转换为一个非单调的次模集函数最大化问题,这允许我们构造一个常因子近似算法。然后,我们考虑了比例公平(PF)系统的效用,并描述了比例公平的最优资源分配。这使我们能够构建一个有效的算法来确定一个最优的关联,直到一个可加常数。然后通过数值结果验证算法的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Exploiting dual connectivity in heterogeneous cellular networks
We consider network utility maximization problems over heterogeneous cellular networks (HetNets) that permit dual connectivity. Dual connectivity (DC) is a feature that targets emerging practical HetNet deployments that will comprise of non-ideal (higher latency) connections between transmission nodes, and has been recently introduced to the LTE-Advanced standard. DC allows for a user to be simultaneously served by a macro node as well as one other (typically micro or pico) node and requires relatively coarser level coordination among serving nodes. For such a DC enabled HetNet we comprehensively analyze the problem of determining an optimal user association that maximizes the weighted sum rate system utility subject to per-user rate constraints, over all feasible associations. Here, in any feasible association each user can be associated with (i.e., configured to receive data from) any one macro node (in a given set of macro nodes) and any one pico node that lies in the chosen macro node's coverage area. We show that, remarkably, this problem can be cast as a non-monotone submodular set function maximization problem, which allows us to construct a constant-factor approximation algorithm. We then consider the proportional fairness (PF) system utility and characterize the PF optimal resource allocation. This enables us to construct an efficient algorithm to determine an association that is optimal up-to an additive constant. We then validate the performance of our algorithms via numerical results.
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