ITR: Cross-Layer Optimization For 4G Wireless Networks: Heavy-Tailed Traffic, Multiuser Channels, and Pseudocells
ITR: Cross-Layer Optimization For 4G Wireless Networks: Heavy-Tailed Traffic, Multiuser Channels, and Pseudocells
批准号:
0220118
负责人:
Upamanyu Madhow
金额:
$45.0万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2002
资助国家:
美国
项目状态:
已结题
起止时间:
2002-09-15 至 2007-08-31
中文摘要
这个项目涉及无线网络理论和实践的一些基本方面。采用一种综合方法,将物理层创新与介质访问控制和调度的新协议结合起来,同时考虑到应用需求和传输协议动态,以解决所确定的研究问题。考虑了两个主要的研究重点。在第一个研究重点中,“伪蜂窝”无线网络的概念结合了蜂窝网络和自组织网络的最佳特性,被认为是即插即用第四代(4G)无线网络的范例。这种灵活的架构显然对于在紧急情况下快速建立无线网络至关重要,在这种情况下,固定或甚至移动基站部署在方便(但未优化)的站点,以服务移动缓慢和快速的用户。然而,它也是我们实现无线链路速度量子飞跃愿景的关键因素,通过超越当前1- 2ghz的蜂窝频段到10s GHz频段的大带宽。这种频带的路径损耗很高,一方面迫使使用密集的基站网络,另一方面又使频率重用更加积极。该研究的重点是在分组的伪蜂窝基础设施上支持混合用户移动性,以及混合实时和非实时应用程序。这种设置不同于传统的蜂窝网络,因为蜂窝大小很小,并且蜂窝可能有大量重叠。它不同于无线局域网(wlan),因为它允许快速移动用户,尽管小区规模小。与传统的分层结构(即,为快速移动的用户提供大单元,为缓慢移动的用户提供覆盖在小单元上)处理一系列移动性不同,考虑采用以移动为中心的方法,该方法结合了切换和基于保留的媒体访问控制,以允许灵活部署。要研究的一个新想法是在保留通道上支持优先级,以便允许(例如,正在进行实时呼叫的高度移动用户)在进入新的伪cell时快速保留资源,从而隐式地实现切换。另一个重要的问题是预留信道的收发器优化,这需要解决多用户通信中的新问题。第二个研究重点是由众所周知的观察引起的,即互联网流量具有重尾分布,这通常要求比传统的马尔可夫流量模型更保守的资源配置。由于过度供应在资源受限的无线环境中没有吸引力,因此考虑的方法是采用一种新的服务质量(QoS)框架,该框架允许积极的资源利用,通过快速服务于大部分事务(短事务),并惩罚导致重尾的一小部分长事务。实现这一目标的调度规则与流行的轮循或公平队列调度程序非常不同,并且在三十多年前的队列理论文献中被考虑过。本项目首次(据我们所知)探讨了这些结果对重尾互联网流量的影响。调度策略被扩展到共享无线信道,公平性与系统效率相权衡,后者决定了看到最佳信道的用户应该获得链路访问权。为了有效地支持重尾交通,这种权衡预计将偏向于效率。调度和TCP连接的动态(TCP是大多数事务运行的Internet数据传输协议)之间的交互进行了探索,请记住,由于重复超时和速率削减,缺乏网络资源的TCP连接可能会被锁定在网络之外。最后,我们探讨了调度对移动性的依赖性,将优先级分配给高度移动性的用户(他们在给定的伪蜂窝中逗留期间访问链路的机会较小),同时考虑到总体QoS和公平性。我们开发的调度方法高度重视整个系统的效率,因此非常适合统一费率定价,这可以说是促进无线数据网络使用增长的有效机制。
英文摘要
This project addresses some fundamental aspects of the theory and practice of wireless networking. An integrated approach, combiningphysical layer innovations with new protocols for medium access control and scheduling, while accounting for application requirements and transport protocol dynamics, is employed for solving the research problems that are identified. Two major research thrusts are considered. In the first research thrust, the concept of ``pseudocellular'' wireless networks, which combine the best features of cellular and ad hoc networks, is considered as a paradigm for plug-and-play fourth generation (4G) wireless networks. Such a flexible architecture is clearly critical for quick set-up of wireless networks in emergency situations, in which stationary, or perhaps even mobile, base stations are deployed at convenient (but not optimized)sites to serve both slow-moving and fast-moving users. However, it is also a key ingredient of our vision of achieving a quantum jump in wireless link speeds, by going beyond the current cellular frequency bands of 1-2 GHz to the large bandwidths available in frequency bands in the 10s of GHz. The path loss in such bands is high, forcing the use of a dense network of base stations on the one hand, and enabling more aggressive frequency reuse on the other. The focus of the research is to support a mix of user mobilities, and a mix of real-time and non real-time applications, over a packetized pseudocellular infrastructure. This setting differs from conventional cellular networks, in that the cell sizes are small, and cells may have substantial overlap. It differs from wireless Local Area Networks (WLANs), in that it allows for rapidly mobile users despite the small cell sizes. Instead of a conventional hierarchical structure (i.e., large cells for fast-moving users, overlaid on small cells for slow-moving users) to deal with a range of mobility, a mobile-centric approach, which combines handoffs and reservation-based medium access control, is considered to allow for flexible deployment. A novel idea to be investigated is the support of priorities on the reservation channel, so as to allow, for example, highly mobile users with real-time calls in progress to rapidly reserve resources when entering a new pseudocell, thus implicitly achieving a handoff. Another important issue is transceiver optimization of the reservation channel, which requires solution of new problems in multiuser communications.The second research thrust is motivated by the well-known observation that Internet traffic has a heavy-tailed distribution, which typically calls for more conservative resource provisioning than for traditional Markovian traffic models. Since overprovisioning is unattractive in resource-constrained wireless environment, the approach considered is toemploy a new Quality of Service (QoS) framework that allows foraggressive resource utilization, by serving the bulk of thetransactions (which are short) rapidly, and penalizing the small fraction of long transactions that contribute to the heavy tails. Scheduling disciplines that achieve this goal are very different frompopular round robin or fair queueing schedulers, and were considered in the queueing theory literature more than three decades ago. The implication of these results for heavy-tailed Internettraffic is explored for the first time (to the best of our knowledge) in this project. The scheduling strategy is extended to a shared wireless channel, where fairness is traded off against systemefficiency, with the latter dictating that users seeing the best channels are the ones that should get link access. The tradeoff is expected to be biased towards efficiency in order to supportheavy-tailed traffic effectively. The interaction between scheduling and the dynamics of TCP connections (TCP is the Internet data transport protocol on top of which most transactions run) is explored, keeping in mind that a TCP connection that is starved of network resources can get locked out of the network due to repeated timeouts and rate cutbacks. Finally, the dependence of scheduling on mobility is explored, with the concept of assigning priority to highly mobileusers (who have a smaller chance of getting access to the link during their sojourn in a given pseudocell), while keeping overall QoS and fairness in mind. The scheduling methods we develop place a high importance on overall system efficiency, and are therefore well-suited to flat rate pricing, which is arguably an effective mechanism of promoting usage growth in wireless data networks.
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