无线多载波网络中资源分配的多服务器调度框架
A Multi-server Scheduling Framework for Resource Allocation in Wireless Multi-carrier Networks
AI总结：
本文提出一种基于多服务器调度框架的跨层资源分配算法，通过MPGPS及其变体实现分组交换OFDM网络中多用户同时调度与功率、频谱效率的联合优化。
摘要：
多用户资源分配近来已被认为是增强OFDM（正交频分复用）系统功率和频谱效率的有效方法。然而，它不能直接应用于当前的分组交换网络，因为（i）大多数现有的分组调度方案基于单服务器模型，不能同时服务多个用户；（ii）MAC（媒体访问控制）分组调度和PHY（物理层）资源分配的传统分离设计导致资源利用效率低下。在本文中，我们提出了一种基于新颖的多服务器调度框架的跨层资源分配算法，以在分组交换OFDM网络中实现整体高系统功率效率。我们的贡献有四个方面：（i）我们提出并分析了一种MPGPS（多服务器分组化通用处理器共享）服务纪律，该纪律同时服务多个用户并促进多用户资源分配；（ii）我们提出了一种基于MPGPS的联合MAC-PHY资源分配方案，该方案将分组调度、子载波分配和功率分配整合在一个统一的框架中；（iii）通过研究多用户分集与排队性能之间的基本权衡，我们提出了一种A-MPGPS（自适应MPGPS）服务纪律，以在功率效率和排队性能之间取得平衡；（iv）我们将MPGPS扩展为O-MPGPS（机会性MPGPS）服务纪律，以进一步提高资源利用效率。
英文摘要：
Multiuser resource allocation has recently been recognized as an effective methodology for enhancing the power and spectrum efficiency in OFDM (orthogonal frequency division multiplexing) systems. It is, however, not directly applicable to current packet-switched networks, because (i) most existing packet-scheduling schemes are based on a single-server model and do not serve multiple users at the same time; and (ii) the conventional separate design of MAC (medium access control) packet scheduling and PHY (physical) resource allocation yields inefficient resource utilization. In this paper, we propose a cross-layer resource allocation algorithm based on a novel multi-server scheduling framework to achieve overall high system power efficiency in packet-switched OFDM networks. Our contribution is four fold: (i) we propose and analyze a MPGPS (multi-server packetized general processor sharing) service discipline that serves multiple users at the same time and facilitates multiuser resource allocation; (ii) we present a MPGPS-based joint MAC-PHY resource allocation scheme that incorporates packet scheduling, subcarrier allocation, and power allocation in an integrated framework; (iii) by investigating the fundamental tradeoff between multiuser-diversity and queueing performance, we present an A-MPGPS (adaptive MPGPS) service discipline that strikes balance between power efficiency and queueing performance; and (iv) we extend MPGPS to an O-MPGPS (opportunistic MPGPS) service discipline to further enhance the resource utilization efficiency.
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