Wireless packet and ad hoc networking

广泛的无线分组和自组织网络应用被视为数据通信的下一次革命。这种应用需要设备、系统和计算机工程级别的先进无线使能技术，特别是对于在没有预先建立的基础设施的情况下运行的自组织网络。众所周知，这种高度灵活且在很大程度上不协调的无线网络的信息承载能力是严格有限的，并且以低于节点数量的速度增长。为了使这类网络高效，需要将最合适和最先进的信号处理方法应用于这些网络的物理层。此外，使用已知的无线分组协议(如802.11和802.16)进行的实验表明，现有的接入方法不适合大型非协调自组织网络。新的协议策略需要最大限度地利用单个节点的物理层能力，本项目从两个角度解决这些问题：i)设计和验证新的信号处理方法，特别是联合检测和干扰消除方法。它们被设计为接近任何给定节点的理论最大信息流。Ii)基于业务和信号统计的新型协议的设计和实现，以用最少的控制消息来维持高链路吞吐量和可靠性，从而允许网络配置动态改变而不损害网络性能。一个重要的组成部分是这两个研究目标的有效集成，以证明总体网络效率。

Widespread wireless packet and ad hoc networking applications are seen as the next revolution in data communications. Such applications require advanced wireless enabling technologies at the device, system, and computer engineering levels, in particular for ad hoc networks that are to operate without a preestablished infrastructure.It is well known that the information carrying capacity of such highly flexible and largely uncoordinated wireless networks is strictly limited and grows with a rate less than the number of nodes. In order to make such networks efficient, the most appropriate and advanced signal processing methods need to be applied to the physical layer of these networks.Additionally, experiments with known wireless packet protocols such as 802.11 and 802.16 have shown that current accessing methods are inadequate for large uncoordinated ad-hoc networks. New protocol strategies need to be developed which make maxium use of the physical layer capabilities of the individual nodes.This project addresses these issues from two angles: i) designing and verifying novel signal processing methods, in particular joint detection and interference cancellation methods. These are designed to approach the theoretical maximum information flow at any given node. ii) The design and implementation of novel protocols which are based on traffic and signal statistics to maintain high link throughputs and reliability with a minimum of control messages, thus allowing the network configuration to change dynamically without compromising network performance. An important component is the efficient integration of these two research objectives to demonstrate overall network efficiency.